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JMIR Preprints
A preprint server for pre-publication/pre-peer-review preprints intended for community review as well as ahead-of-print (accepted) manuscripts
Abstract
Current conversational triage systems built on large language models (LLMs) are computationally intensive and inherently opaque, often drifting toward premature diagnostic claims that raise governance and medico legal concerns1. In contrast, we introduce the first-of-its-kind Bayesian Iterative Convergence (BIC) framework, which redefines intake dialogue as a probabilistic evidence-gathering process rather than a semantic mimicry exercise. Unlike transformer-based architectures that prioritize linguistic richness, BIC leverages iterative clarification and patient verification to converge on structured symptom descriptors with auditable logic. Bayesian symptom convergence approach—augmented with attribute level refinement and patient verification—combines to construct a lean, auditable alternative that holds a strict boundary at structured symptoms.
This paradigm minimizes reliance on exhaustive language interpretation, reduces computational overhead, and embeds transparency through explicit, reviewable reasoning steps. By holding a strict boundary at symptom structuring—while enabling human-in-the-loop diagnosis or accountable downstream AI—our approach establishes a lean, ethically aligned alternative to diagnosis-first dialogue. We detail its conceptual architecture, illustrate micro-level mechanics (e.g., uncertainty-driven question selection), and demonstrate real-world applicability through two case studies: (1) chest pain, where precision is critical, and (2) evolving colorectal symptoms, where longitudinal iteration reveals patterns. This work challenges prevailing design norms and sets a new benchmark for domain-specific medical AI systems that prioritize accuracy, explainability, and governance compliance over linguistic mimicry. The result is a path for medical AI that is computationally efficient, explainable by construction, and operationally aligned with human in the loop diagnosis—where precision precedes diagnosis.
Legal and Intellectual Property Disclosure
The authors declare that a provisional patent application has been filed covering specific technical aspects of the approach described in this manuscript, including (but not limited to) mechanisms for question prioritization, belief updating, convergence scoring, data structures, and audit instrumentation. To avoid premature public enablement, detailed implementation information—such as numeric thresholds, mathematical formulations, parameter values, internal data schemas, dependency modelling strategies, and optimization heuristics—has been intentionally omitted from this version. Comprehensive technical details may be made available to qualified reviewers or collaborators under appropriate confidentiality agreements. This disclosure is provided to ensure transparency while safeguarding intellectual property and patient safety.
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Abstract
Current conversational triage systems built on large language models (LLMs) are computationally intensive and inherently opaque, often drifting toward premature diagnostic claims that rais...
Abstract
Current conversational triage systems built on large language models (LLMs) are computationally intensive and inherently opaque, often drifting toward premature diagnostic claims that raise governance and medico legal concerns1. In contrast, we introduce the first-of-its-kind Bayesian Iterative Convergence (BIC) framework, which redefines intake dialogue as a probabilistic evidence-gathering process rather than a semantic mimicry exercise. Unlike transformer-based architectures that prioritize linguistic richness, BIC leverages iterative clarification and patient verification to converge on structured symptom descriptors with auditable logic. Bayesian symptom convergence approach—augmented with attribute level refinement and patient verification—combines to construct a lean, auditable alternative that holds a strict boundary at structured symptoms.
This paradigm minimizes reliance on exhaustive language interpretation, reduces computational overhead, and embeds transparency through explicit, reviewable reasoning steps. By holding a strict boundary at symptom structuring—while enabling human-in-the-loop diagnosis or accountable downstream AI—our approach establishes a lean, ethically aligned alternative to diagnosis-first dialogue. We detail its conceptual architecture, illustrate micro-level mechanics (e.g., uncertainty-driven question selection), and demonstrate real-world applicability through two case studies: (1) chest pain, where precision is critical, and (2) evolving colorectal symptoms, where longitudinal iteration reveals patterns. This work challenges prevailing design norms and sets a new benchmark for domain-specific medical AI systems that prioritize accuracy, explainability, and governance compliance over linguistic mimicry. The result is a path for medical AI that is computationally efficient, explainable by construction, and operationally aligned with human in the loop diagnosis—where precision precedes diagnosis.
Legal and Intellectual Property Disclosure
The authors declare that a provisional patent application has been filed covering specific technical aspects of the approach described in this manuscript, including (but not limited to) mechanisms for question prioritization, belief updating, convergence scoring, data structures, and audit instrumentation. To avoid premature public enablement, detailed implementation information—such as numeric thresholds, mathematical formulations, parameter values, internal data schemas, dependency modelling strategies, and optimization heuristics—has been intentionally omitted from this version. Comprehensive technical details may be made available to qualified reviewers or collaborators under appropriate confidentiality agreements. This disclosure is provided to ensure transparency while safeguarding intellectual property and patient safety.
Background: Validated measurement tools that focus solely on assessing adolescents´ involvement in their treatment are scarce. Objective: We aimed to validate five Patient-Reported Outcome (PRO) ques...
Background: Validated measurement tools that focus solely on assessing adolescents´ involvement in their treatment are scarce. Objective: We aimed to validate five Patient-Reported Outcome (PRO) questions regarding patient involvement among adolescents with type 1 diabetes. Methods: 447 adolescents (11-18 years of age) completed a short survey including five PRO questions regarding patient involvement. Twenty participants were interviewed cognitively. The PRO questions' content validity, feasibility, internal consistency, and construct validity were analyzed. Results: Assessment of content validity revealed that most participants encountered no or minor difficulties comprehending the PRO questions. Specifically, all participants demonstrated a satisfactory cognitive understanding of three of the five PRO questions. However, the terms "appropriate" and "experiences" posed a challenge for 3 out of 20 subjects. The feasibility, internal consistency, and construct validity analyses uncovered only two limitations in validity. Firstly, the clinical utilization of the questions limits anonymity, potentially introducing bias. Secondly, adolescents below 15 years had more difficulties with the item "I talked to the healthcare staff about the questions or concerns I had." Conclusions: The PRO questions are valid for measuring patient involvement among adolescents with type 1 diabetes. Respondents stated that the PRO questions were easy to understand, relevant, and comprehensive. However, employing these PRO questions in both clinical settings and research demands thoughtful considerations regarding their application and setup, particularly when considering the age of respondents and circumstances. It is worth noting that these PRO questions might hold validity challenges for application among adolescents below 15 years with type 1 diabetes.
This multicentric retrospective observational study investigates factors associated with the risk of non-initiation and dropout in the use of blended therapy (BT) among inpatients. In this study, data...
This multicentric retrospective observational study investigates factors associated with the risk of non-initiation and dropout in the use of blended therapy (BT) among inpatients. In this study, data from 278 inpatients were analysed to examine the influence of sociodemographic variables, comorbidities, and symptom severity on the uptake and continued use of BT. Multivariate regression analyses were conducted to identify significant predictors of non-initiation and dropout. The results indicate that different factors are associated with each. Specifically, increasing age was linked to a lower risk of non-initiation (OR (per year age difference) = 0.98, 95% CI [0.96, 1.00], p = 0.013), while the presence of a comorbid anxiety disorder was associated with a reduced risk of dropout (OR = 0.23, 95% CI [0.08, 0.66], p = 0.007). The age-related finding aligns with existing literature suggesting that older adults show higher willingness to continue with internet-based treatment. Explanations for this could be having more realistic expectations regarding treatment, greater persistence, or the likelihood that only intrinsically motivated older adults choose to even engage in digital therapies. Regarding comorbid anxiety disorders, previous literature provides no consistent conclusions about its role in dropout. However, the lower dropout rates observed in this subgroup may reflect specific personality traits or indicate that these patients benefit more from the highly structured nature of BT. It is possible that the modules offered on the platform are particularly well-suited to addressing core mechanisms of anxiety disorders, thereby enhancing perceived relevance and user engagement. In conclusion, the findings highlight the importance of identifying patient characteristics that predict successful engagement with BT. Tailoring the use of BT to those more likely to adhere may support more effective and resource-conscious implementation in clinical inpatient settings.
Background: Ecological momentary assessment (EMA) is a tool that captures emotional states, experiences, and behaviors in real or near-real time. Using continuous glucose monitoring (CGM) data and EMA...
Background: Ecological momentary assessment (EMA) is a tool that captures emotional states, experiences, and behaviors in real or near-real time. Using continuous glucose monitoring (CGM) data and EMA in unison may be beneficial to understand associations between psychosocial factors and momentary glucose levels. An in-depth understanding of these relationships is crucial for future interventions targeting psychosocial factors in chronic diseases such as diabetes mellitus. Objective: The goal of this scoping review was to summarize the objectives, methodologies, and outcomes of studies analyzing concurrent psychosocial EMA and CGM data. Methods: This study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. One-hundred and six studies were identified from PubMed, Embase, and EBSCOhost from May 2009-Jan 2025. Thirteen original research articles that collected and analyzed simultaneous EMA and CGM data were included. Methodological data abstracted included study characteristics, EMA protocols and outcomes, CGM outcomes, and integrated EMA and CGM study objectives. Results: Studies primarily recruited adult (92%) populations with type 1 diabetes (T1DM) (69%). EMA delivery protocols and outcomes varied significantly and included emotion, self-care behaviors, disordered eating behaviors, interpersonal interactions, cognition, sleep, workload, and impacts of hypoglycemia. Most (69%) studies analyzed blinded CGM data and CGM outcomes included both standardized and non-standardized glucose outcomes. Integrated EMA and CGM data answered study objectives including evaluating impacts of psychosocial and lifestyle factors on momentary glucose metrics; the influence of momentary glucose on emotional states, mood, personal behaviors, sleep, and cognition; and study protocol or mobile application optimization among others. Conclusions: The combination of EMA and CGM data provides an opportunity to elucidate the relationship between psychological and behavioral factors with momentary glucose. In this review, we describe a broad range of study characteristics, protocols, outcome measures, and objectives using these novel combined methodologies. Clinical Trial: Not applicable
Background: Type 2 diabetes (T2D) remains one of the most underdiagnosed chronic conditions worldwide, despite its major contribution to cardiovascular and metabolic morbidity. Workplace-based prevent...
Background: Type 2 diabetes (T2D) remains one of the most underdiagnosed chronic conditions worldwide, despite its major contribution to cardiovascular and metabolic morbidity. Workplace-based prevention strategies offer an opportunity to enhance early detection, particularly among employed adults with limited access to regular medical screening. In France, the Union Prévention Santé pour la Fonction publique (UROPS) has implemented a systematic glucose-screening program for civil servants to identify individuals at risk of T2D or prediabetes. Objective: This study aimed to assess the effectiveness of a systematic diabetes screening program as a preventive public health measure, by determining the rate of newly detected diabetes cases and characterizing associated cardiometabolic risk factors within a large population of French public-sector employees. Methods: A retrospective observational study was conducted using data from a glucose screening program between January 2022 and February 2025. Participants with postprandial blood glucose >1.40 g/L were included in a follow-up cohort. Sociodemographic, clinical, and biological data were collected. Comparisons were performed using χ² or Fisher’s exact test for categorical variables and Student’s t-test for continuous variables (R software, v4.3.3; significance p<0.05). Results: Among 16,785 screened participants, 981 (5.8%) were eligible for follow-up, and 134 were included in the cohort. Of these, 70 (52.2%) completed follow-up, with 12.9% having confirmed diabetes after medical assessment. Confirmed diabetics were mostly men (77%, p<0.05). Overweight (37.6%) and obesity (25.6%) were frequent, as were sedentary lifestyle (61.6%) and family history of diabetes (63.2%). Conclusions: Systematic glucose screening in an occupational or social health context effectively identifies individuals at risk of diabetes or prediabetes. The results support the integration of such programs into preventive health strategies to enhance early detection and reduce long-term complications.
Background: Computerized clinical decision support (CDS) has the potential to improve patient outcomes by offering evidence-based guidance at the point of care—enhancing guideline adherence and diag...
Background: Computerized clinical decision support (CDS) has the potential to improve patient outcomes by offering evidence-based guidance at the point of care—enhancing guideline adherence and diagnostic accuracy—and supports system-level outcomes by enabling predictive analytics for more efficient resource planning. Prior work has identified factors that affect adoption, such as clinicians’ expectations of usefulness, ease of use, alignment with workflows, and resources to support utilization. However, CDS adoption is not static and changes according to dynamic systems of behaviors and workflows, requiring a deeper understanding of how evolving conditions affect implementation and outcomes. Objective: To explore dynamic factors influencing CDS adoption, we examined the implementation of “Unplanned readmission model version 1”, developed by Epic Medical Records System, at Duke University Health System (DUHS) using group model building and system dynamics modeling. Methods: We first conducted group model building workshops with staff (case managers, physical and occupational therapists, hospitalist faculty physicians, and resident physicians) who participate in decisions about discharging patients. Study team members guided participants to identify and connect variables in causal loop diagrams. We coded workshop transcripts in software designed for system dynamics analysis to identify themes, aggregated them into a causal loop diagram, and reviewed them with participants to converge on a common model. A team member applied equations to the pathways and test data to simulate conditions leading to full, limited, or no adoption of a tool. Results: We identified key balancing loops driven by external pressure (e.g., CMS penalties) that motivated initial adoption and reinforcing loops based on perceived internal benefits to sustain use. While institutional incentives led to early training and tool use, efforts declined due to staff turnover, competing priorities (e.g., COVID-19), and workflow changes. Reinforcing loops emerged when staff described clinical utility, such as improved discharge planning and team communication. However, staff also suggested that these loops were often weak, due to difficulty linking the use of the tool to outcomes in real time. Simulation modeling showed that while strong external pressure and rapid training led to initial success, interest in using the tool waned as workflows improved and readmission rates approached CMS goals. When conflicting priorities were introduced, adoption stalled earlier, and fewer staff were trained. In contrast, when internal motivation was strengthened, by reducing the amount of evidence needed to perceive success, individual interest remained high even as institutional attention declined, sustaining tool use and further reducing readmissions. Conclusions: External pressure to improve can be a strong motivator for initial adoption, but in the face of conflicting demands for attention, it can fall short of sustained long-term tool use. Tools are more likely to have extensive and sustained use when those using the tools can perceive internal benefits.
Background: Drug-induced parkinsonism (DIP) predominantly occurs due to antipsychotic drugs (APDs) blocking dopamine D2 receptors (D2R). Despite assessing drug mechanisms and side effects, in vitro as...
Background: Drug-induced parkinsonism (DIP) predominantly occurs due to antipsychotic drugs (APDs) blocking dopamine D2 receptors (D2R). Despite assessing drug mechanisms and side effects, in vitro assays fail to fully reflect real-world clinical outcomes. This study developed novel in vitro metrics to more accurately predict real-world DIP. Objective: This study aimed to develop novel in vitro metrics to more accurately predict real-world DIP. Methods: We focused on eight APDs (haloperidol, amisulpride, clozapine, olanzapine, quetiapine, risperidone, ziprasidone, and aripiprazole) and measured key in vitro parameters, including the D2R and serotonin 2A receptor inhibition constants (Ki), D2R reversal rate (Kr), and blood-brain barrier penetration rate (BBBpr). The six composite DIP risk metrics were calculated by combining these factors. The real-world DIP risk was assessed using data from the Seoul National University Hospital Common Data Model (2002–2021). After 1:1 propensity score matching, each APD cohort was compared with selective serotonin reuptake inhibitor controls, and Cox proportional hazards regression was performed to estimate the hazard ratios (HRs) for DIP. Results: Among the 324,449 patients, 109,436 selective serotonin reuptake inhibitor users and 28,945 APD users formed eight matched cohorts. Haloperidol showed the highest DIP risk (HR 4.56; 95% confidence interval [CI], 2.29–9.07), whereas aripiprazole exhibited the lowest risk (HR 2.11; 95% CI, 1.56–2.86). The composite metric (pKr × BBBpr) displayed the strongest correlation with real-world DIP risk (R2 = 0.95); however, aripiprazole was an outlier, likely owing to its partial agonistic properties. Conclusions: Combining receptor-binding kinetics with BBB penetration provides a robust in vitro predictor of clinical DIP risk and underscores assessing receptor kinetics alongside central nervous system accessibility for drug safety evaluations.
Background: The European Health Data Space Regulation is a European Union (EU) initiative aimed at promoting the sharing and safe use of health data across the EU. Its creation is based on the Europea...
Background: The European Health Data Space Regulation is a European Union (EU) initiative aimed at promoting the sharing and safe use of health data across the EU. Its creation is based on the European Digital Strategy for Data (EC). COM/2020/66) and allows the European Community (EC) to fulfil its objectives of improving public health, reducing health inequalities, and promoting a more social Europe. Objective: To summarise the available scientific evidence on the application of the European Health Data Space Regulation and identify the primary challenges and successes of its implementation Europe. Methods: A comprehensive literature search conducted on May 22, 2025, identified 321 references. After removing 149 duplicates, 172 records remained for the title and abstract screening. Of these, 68 were excluded because they did not meet the study's inclusion criteria. The remaining 114 full-text articles were retrieved for a detailed assessment of eligibility. A total of 114 studies were assessed for eligibility. Data were extracted using a predetermined form, including various parameters such as author, year, and outcomes. Results: : A total of 45 studies were included in this review. Three overarching themes emerged: Governance and Regulatory Policies (45 studies), Technologies and Infrastructure (38 studies), and Stakeholder Participation (31 studies). As several studies addressed multiple themes, these categories are not mutually exclusive. The findings indicate that the successful implementation of the European Health Data Space (EHDS) hinges on the synergistic interaction among governance mechanisms, technological infrastructures, and stakeholder engagement. Conclusions: These findings underscore the potential of evidence to the successful implementation of EHDS requires coordinated efforts to align policies, enhance interoperability, and address legal and security challenges. Clear governance, stakeholder involvement, and robust data systems are key to fostering trust and ensuring effective deployment. Despite these challenges, the EHDS holds great potential for enhancing healthcare and research through secure cross-border data sharing.
Background: In South Korea, where plain packaging has not been adopted, tobacco packaging remains primarily a marketing tool for the tobacco industry, using texts, colors, and imagery to attract consu...
Background: In South Korea, where plain packaging has not been adopted, tobacco packaging remains primarily a marketing tool for the tobacco industry, using texts, colors, and imagery to attract consumers. Among these, flavor cues are especially important as they enhance product appeal. Cigarette sticks also serve as marketing through features such as colors and capsule indicators. Objective: We aimed to examine the packaging of tobacco products, with a focus on flavor cues and additives in products. Methods: This surveillance study was conducted in November 2024 using an adapted Tobacco Pack Surveillance System protocol (TPackSS). Tobacco products were purchased from convenience stores located in Seoul, supplemented by cross-referencing with national market monitoring data. Of 353 identified products, 214 (150 cigarettes and 64 heated tobacco products [HTPs]) were collected. Flavor cues were categorized by pack design features, while additives were identified through sensory analysis of product components. Results: Among the collected products, 63.6% had both flavor cues (68.0% of CCs and 95.3% of HTPs) and flavor additives (59.3% of CCs and 84.4% of HTPs), while 20.6% had neither. Pack color was the most common cue and additives were most often delivered through crushable capsules. HTPs used a wider range of flavoring methods, including flavoring in tobacco leaves and inner wrappers. Conclusions: Tobacco packaging and stick design in South Korea remain important marketing channels. Flavor cues and additives are widely used in tobacco products, particularly in HTPs. These findings highlight the need for plain packaging and flavor bans on tobacco products.
Background: The transition from simulation-based learning to the clinical environment is a pivotal stage in undergraduate nursing education. This period can influence students’ psychological well-be...
Background: The transition from simulation-based learning to the clinical environment is a pivotal stage in undergraduate nursing education. This period can influence students’ psychological well-being, adaptability, and sense of belonging within the clinical setting which is a dimensions essential to professional learning and patient safety. Although simulation aims to prepare students for clinical realities, the extent to which it supports their emotional and social readiness for real practice remains unclear. Objective: The primary objective of this scoping review is to map existing literature addressing the well-being, adaptability, and sense of belonging of undergraduate nursing students as they transition from the simulation lab to the clinical environment. Secondary objectives include identifying educational interventions or strategies that foster these dimensions and highlighting gaps and directions for future research. Methods: The review will follow the Joanna Briggs Institute (JBI) methodology for scoping reviews and the PRISMA-ScR reporting guidelines. A systematic search will be conducted in PubMed, CINAHL, APA PsycINFO, and ScienceDirect for studies published between 2015 and 2025 in English or French. Eligible studies will include empirical (quantitative, qualitative, or mixed-method) and review papers exploring nursing students’ experiences of transitioning from simulation-based to real clinical settings. Two reviewers will independently screen titles, abstracts, and full texts, extract relevant data, and synthesize findings using thematic analysis. Results: Data collection and analysis are expected to be completed by June 2026. Results will summarize current definitions, measures, and interventions related to students’ well-being, adaptability, and belonging, as well as identify evidence gaps and conceptual trends in literature. Conclusions: This scoping review will offer a comprehensive synthesis of how undergraduate nursing students experience the transition from simulation-based learning to clinical practice, with a particular focus on psychosocial dimensions such as well-being, adaptability, and sense of belonging. By identifying key factors and interventions that support these dimensions, the findings will inform the development of targeted educational strategies and contribute to enhancing transition frameworks within nursing education.
Background: Wearable accelerometers have become integral to mobile health (mHealth) research, particularly for delivering real-time physical activity (PA) monitoring and applications in interventions...
Background: Wearable accelerometers have become integral to mobile health (mHealth) research, particularly for delivering real-time physical activity (PA) monitoring and applications in interventions such as Just-in-Time Adaptive Interventions (JITAIs). One critical yet underexplored factor in real-time PA monitoring is epoch length, which is the time interval over which raw accelerometry data are aggregated to classify activity intensities and levels. Shorter epochs (e.g., 1 second) enhance precision but increase computational and battery demands, while longer epochs (e.g., 60 seconds) reduce data burden but may miss brief activity bouts. Although previous studies have examined epoch effects using post-processed data, limited evidence exists regarding their influence on real-time, wrist-based PA estimates, especially for moderate-to-vigorous PA (MVPA). Identifying an optimal epoch length for real-time PA measurement remains a critical gap in supporting scalable and efficient mHealth interventions. Objective: This study determined the impact of varying epoch lengths on real-time MVPA estimates derived from a wrist-worn accelerometer to identify an optimal epoch that balances measurement accuracy with practical feasibility for mHealth applications. Methods: Twenty adults (Age: 32.5 ± 15.1 years) completed a series of carefully selected simulated free-living activities in a controlled laboratory setting. Participants wore the MotionSense HRV wristband, which computed real-time Euclidean Norm Minus One (ENMO) values, and a COSMED K5 indirect calorimetry for metabolic reference. ENMO values were aggregated into 5-, 10-, 15-, 30-, and 60-second epochs. MVPA was classified using validated ENMO cut-points. Epoch-level MVPA estimates were compared against the 1-second reference using mean absolute percent error (MAPE), Pearson’s correlations, Bland-Altman (BA) plots, and equivalence testing with a ±10% equivalence zone. Results: MVPA estimates from all epoch lengths were statistically equivalent to the 1-second standard. The 15-second epoch demonstrated the best trade-off between accuracy and efficiency, with minimal bias (0.05 min), low MAPE (6.3%), and strong correlation (r = 0.97). However, indicators of individual-level error increased with longer epochs; MAPE increased to 9.5% at 60 seconds, and the limits of agreement widened (from ± 2.9 min at 15s to ± 4.9 min at 60s), suggesting greater potential misclassifications in estimating MVPA with longer epochs. Conclusions: Although MVPA estimates using the MotionSense HRV wristband were robust across all epoch lengths, findings from this study suggest that a 15-second epoch provides an optimal balance between measurement precision and processing efficiency, making it well-suited for mHealth interventions, such as JITAIs that rely on timely activity detection.
Background: Background: Sepsis is defined as a life-threatening condition caused by a dysregulated host immune response to infection, often resulting in organ dysfunction. The heterogeneous nature and...
Background: Background: Sepsis is defined as a life-threatening condition caused by a dysregulated host immune response to infection, often resulting in organ dysfunction. The heterogeneous nature and clinical presentation, overlapping with other acute conditions, often leads to diagnostic delays of sepsis, and consequently, to unacceptably high morbidity and mortality levels. Objective: This scoping review aims to identify and synthesise studies that use electronic medical record (EMR) data to develop or validate artificial intelligence (AI)-based models for the early detection or prediction of sepsis. Methods: Peer-reviewed studies published between March 2016 and February 2024 that use EMR data to develop, test, or evaluate AI or machine learning models for predicting sepsis or septic shock will be included. Adult participants (>18) will be included with no restriction on geographical location in this study. This scoping review will be guided by the updated JBI (formerly Joanna Briggs Institute) methodology. The search strategy will include relevant keywords and MeSH terms related to sepsis, electronic health records, and machine learning. Major electronic databases, including MEDLINE, PUBMED, EMBASE, CINAHL, and Cochrane Database of Systematic Reviews/Central Register of Controlled Trials, will be searched. Titles, abstracts, and full texts will be screened by two reviewers independently, with discrepancies resolved by consensus. Results: We will use publicly available data. No primary data will be collected. Ethical approval will not be required. Conclusions: Results will be extracted into a full report to be submitted to a peer-reviewed scientific journal and disseminated to stakeholders and partners in appropriate formats.
Background: Background: As individuals with HIV live longer, many now face the health consequences of aging and multimorbidity, known as disability. Exercise can mitigate disability, however, engageme...
Background: Background: As individuals with HIV live longer, many now face the health consequences of aging and multimorbidity, known as disability. Exercise can mitigate disability, however, engagement in exercise among adults living with HIV varies. Technology-based interventions, such as telerehabilitation, may help mitigate geographical, financial and time barriers to community-based exercise (CBE). However, little is known about the experiences with technology uptake and usage among adults living with HIV. Understanding these experiences is essential to inform design of inclusive, accessible, and sustainable online interventions. Objective: Objectives: Our aim was to describe experiences with technology uptake and usage among adults aging with HIV participating in a six-month online community-based exercise (CBE) intervention, and explore how these experiences changed over time, from baseline to post-intervention. Methods: Methods: We conducted a longitudinal qualitative descriptive study using interview data from adults living with HIV engaged in a CBE intervention study in Toronto, Canada. Participants engaged in a six-month online CBE intervention consisting of thrice weekly exercise, supervised biweekly with online personal coaching sessions, weekly group exercise classes, and monthly self-management education sessions (via Zoom). Technology included Zoom software and webcam; Sweat for Good YMCA App and YMCA Virtuagym Website; and participants wore a wireless physical activity monitor (Fitbit Inspire 2) throughout. Participants completed interviews at baseline and post-intervention. We conducted a group-based content analysis of interview transcripts, focusing on digital access, setup, usage, and perceptions of technology. Questionnaire data describing digital literacy and access to technology provided additional context to the interview data. Results: Results: Eleven participants completed at least one interview. We analyzed 19 interview transcripts from 11 participants (six women, five men; median age 52 years). Experiences with technology uptake and usage among adults aging with HIV were characterized by four components: i) preparations for technology (technology set up); ii) interactions with technology (preferences for different types of technology, preferences for mode of delivery, ease of usage); iii) facilitators and satisfaction with technology (facilitators to technology uptake and usage and satisfaction with technology); and iv) challenges and frustrations with technology (barriers technology uptake and usage, frustrations with technology). Experiences with technology across participants were influenced by intrinsic contextual factors (prior exposure with technology) and extrinsic contextual factors (COVID-19 pandemic, technological and social support). Conclusions: Conclusion: Experiences with technology among adults aging with HIV engaging in an online CBE intervention varied from increasing ease of use, to increasingly burdensome over time. Results highlight the need to incorporate personal preferences, and ongoing technological support when implementing online CBE with adults aging with HIV. Clinical Trial: NCT05006391
Background: Healthy aging encompasses maintaining physical functions, promoting mental health, and preventing mental illness. In recent years, the prevalence of mental disorders among senior citizens...
Background: Healthy aging encompasses maintaining physical functions, promoting mental health, and preventing mental illness. In recent years, the prevalence of mental disorders among senior citizens has gradually increased. How to evaluate and regulate emotions in an effective way has become an important issue to improve the level of mental health. The rise of the silver-haired economy has promoted the transformation of the consumption concept of senior citizens, and they gradually show interest and acceptance of electronic technology products, such as commercial electronic fitness games (Exergame) that combine entertainment and fitness. Objective: Existing research focuses on the improvement of commercial exergames on the physical and cognitive functions of senior citizens, while research on their mood state and mental health promotion is relatively scarce. This research aims to explore the impact of exergames on the emotional experience of senior citizens and provide novel ideas and application directions for healthy aging. Methods: This study included a total of 30 senior citizens (age range: 60-89 years old) who had no cognitive impairment and could move independently. They were randomly divided into two groups. The intervention group (n=15) conducted exergame training, using the Nintendo Switch game Ring Fit Adventure. The comparison group (n=15) carried out traditional indoor exercise. Both groups of sample sets focus on the four dimensions of aerobic exercise, muscle exercise, balance exercise, and flexibility exercise. The exercise cycle is four weeks, twice a week, with eight sessions. The Brunel Mood Scale is employed to assess participants’ mood states(anger, confusion, depression, fatigue, tension, vigor). Using a repeated-measure study design to compare the mood changes of the participants from the front to the back test under different experimental conditions. Results: Significant group x time interaction effects were found for confusion[F(7,28)=7.37, p<.001, η²=0.208]; depression[F(7,28)=5.90, p<.001, η²=0.174]; fatigue[F(7,28)=6.59, p<.001, η²=0.191]; tension[F(7,28)=3.03, p=.005, η²=0.098]; vigor[F(7,28)=14.23, p<.001, η²=0.337]. There was no statistically significant interaction between groups and time points in terms of anger (p>0.05). Confusion, depression, and fatigue in the intervention group were generally lower than those in the comparison group, while tension and vigor were higher than those in the comparison group. Conclusions: Research results show that both commercial exergames and traditional indoor sports can help improve the acute mood state of senior citizens. The training method based on exergames is more effective in reducing confusion, depression, and fatigue, and increasing vigor. This study explores the potential of commercial exergames for improving the mood state of senior citizens as a non-drug intervention method. Clinical Trial: The protocol was registered on Chinese Clinical Trial Register (Registration Number: ChiCTR2500111853). This study was approved by the Institutional Review Board of Zhejiang University in China (Approval Number: cmic20250934).
Background: Virtual reality (VR) provides an accessible, standardized environment to objectively evaluate functional cervical movement control by leveraging built-in head-tracking and game-based tasks...
Background: Virtual reality (VR) provides an accessible, standardized environment to objectively evaluate functional cervical movement control by leveraging built-in head-tracking and game-based tasks. Making such tools available through VR app stores can bridge the lab-to-clinic gap and enable remote administration, allowing clinicians to establish baselines and track therapy response over time with repeated, comparable measurements. Objective: This study aimed to (a) develop a novel VR serious game designed for the assessment of neck movement control and kinematics and (b) to evaluate its reliability, side effects, sense of presence, perceived mental workload and usability. Methods: A multidisciplinary team developed an immersive VR serious game using Unity engine and Meta Quest 3 headsets. The game places users in a space station scenario where they destroy meteorites/space debris by precise head movements over 4 minutes. A descriptive, observational repeated-measures reliability study was conducted with 49 asymptomatic participants (aged 18-65 years). Participants completed three sessions separated by one week to assess test-retest reliability. Variables analyzed included final score, meteorites destroyed/failed, and maximum level reached. Reliability was measured using intraclass correlation coefficients. Side effects (Simulator Sickness Questionnaire), presence (Igroup Presence Questionnaire), mental workload (NASA Task Load Index), and usability (System Usability Scale) were evaluated. Results: The present study allowed for the development of a novel serious game designed to assess neck movement control. It is freely available for use by clinicians or researchers through Meta Quest 3 VR headsets. Forty-five participants completed the protocol (25 men, 20 women; mean age 27.49±10.74 years). The final score showed good reliability (ICC=0.788). The game demonstrated high usability (86.09±13.67), negligible side effects (SSQ: 2.04±2.84), moderate presence levels (IPQ total: 3.43±1.03), and high but acceptable mental workload (NASA-TLX: 61.94±12.85). No major adverse events occurred during 135 game sessions. Conclusions: The novel VR serious game demonstrated good reliability, safety, and usability for neck movement control assessment in asymptomatic individuals. Future research should investigate its application in clinical populations with pain to establish discriminative validity and responsiveness before determining clinical utility.
Background: Adolescent and young adult (AYA) cancer survivors experience unique psychosocial needs during and after treatment. Mobile health (mHealth) interventions are an emerging area of research to...
Background: Adolescent and young adult (AYA) cancer survivors experience unique psychosocial needs during and after treatment. Mobile health (mHealth) interventions are an emerging area of research to help address unmet psychosocial needs. However, few studies have examined provider perspectives on the design-to-implementation pipeline. Objective: Guided by the Consolidated Framework for Implementation Research (CFIR), our study aimed to examine provider perspectives on facilitators and barriers to implementing mHealth apps in routine clinical care. Methods: AYA oncology providers participated in a semi-structured 1:1 interview on facilitators and barriers to incorporating mHealth apps as psychosocial standard of care. We conducted a directed content analysis of the interviews utilizing a standardized CFIR codebook and construct definitions, with codebook adaptations for mHealth innovations and the AYA cancer population. Results: A total of 20 providers (Mage = 39, SDage = 7.0; 80% female; 70% non-Hispanic White) representing various medical and psychosocial roles participated in the interviews. The data were analyzed with 16 CFIR constructs. We identified the following facilitators to mHealth implementation across 4 CFIR domains: (1) Innovation: alignment with patient needs, patient-centered co-design, strong research evidence, user-friendly design; (2) Outer Setting: shared commitment to addressing mental health needs, openness to mHealth use; (3) Inner Setting: openness to training on mHealth use; (4) Individuals: engaging key implementation partners such as bedside nurses and social workers, strong clinical team buy-in. We identified the following barriers to mHealth implementation across 3 CFIR domains: (1) Innovation: associated costs for patients; (2) Outer Setting: heavy clinical workloads; (3) Inner Setting: lack of cross-team collaboration and communication, clinical workflow integration. Conclusions: Our findings highlight key considerations for mHealth co-design, the adoption of mHealth apps into routine care, implementation strategies, and provider training opportunities in the context of AYA cancer care. Partnering with AYA patients, families, and providers will be crucial for developing and implementing mHealth apps with the ultimate goal of advancing universally accessible evidence-based digital health care.
Background: Personal health record systems (PHRs) have been introduced to support patient empowerment by giving individuals direct access to their personal health information and other key health syst...
Background: Personal health record systems (PHRs) have been introduced to support patient empowerment by giving individuals direct access to their personal health information and other key health system resources. MyHealthNB is a province-wide PHR in New Brunswick, Canada, that allows residents to view lab results, medication lists, immunization records, imaging reports, and a range of digital health resources. As PHRs continue to expand, it is essential to understand how PHRs like MyHealthNB impact outcomes related to patient empowerment. Objective: This study uses MyHealthNB as a case example to examine empowerment-related impacts of PHRs on citizens. Building on a conceptual framework linking patient enablement, empowerment, involvement, and engagement, the study is guided by two questions: (1) What perceived impacts of PHR use emerge across enablement, empowerment, involvement, engagement, and cost-related outcomes? (2) Which impacts of PHR use are most prevalent, how are they interrelated, and what characteristics predict variation in these impacts? Methods: An exploratory sequential mixed methods study design was employed. Phase 1 involved qualitative interviews with citizens to explore perceived impacts of using MyHealthNB, analyzed using rapid qualitative analysis. Findings informed a Phase 2 cross-sectional survey that measured MyHealthNB users’ self-reported impacts across enablement, empowerment, involvement, engagement, and cost-related outcomes. Survey data were analyzed using descriptive statistics, t-tests, mediation analysis, and multivariable linear regressions to examine impacts, impact pathways, and impact predictors. Results: Data from 32 interviewees and 885 survey respondents were analyzed. The qualitative analysis showed that MyHealthNB supported a progression from improved access to health information (enablement), to increased confidence (empowerment), to more active participation in health management and healthcare decisions (involvement and engagement). The survey analysis confirmed significant positive impacts across all 21 outcomes measured that spanned enablement, empowerment, involvement, engagement, and cost-related outcomes (P< .05). Mediation analysis revealed that empowerment played a key role in explaining how enablement through MyHealthNB led to increased involvement and engagement in health and healthcare behaviours. Regression models identified key predictors of MyHealthNB impacts, which included satisfaction with MyHealthNB, having a family doctor, provider support of MyHealthNB, digital literacy, and MyHealthNB use frequency. Conclusions: PHRs can improve outcomes related to patient empowerment, behaviour change, and health system benefits. The advantages of PHR use were most prominent when individuals had access to primary care, received support from healthcare providers, and had confidence using digital technologies. Although some users experienced stress or uncertainty from using the PHR, these responses did not detract from its overall value. To fully realize the promise of PHRs, implementers should invest in digital literacy support and strengthen primary care access and integration. Clinical Trial: N/A
Background: Digital health interventions (DHIs) are a potential tool to address communication challenges in primary care by improving engagement, adherence, and chronic disease self-management. Howeve...
Background: Digital health interventions (DHIs) are a potential tool to address communication challenges in primary care by improving engagement, adherence, and chronic disease self-management. However, Germany’s digital health infrastructure remains underdeveloped compared to other OECD countries. Designing fit-for-purpose and context-sensitive tools requires a deep understanding of patient needs, using participatory approaches that actively involve end-users and relevant stakeholders to ensure the tools are better tailored to their needs. Behavioural science frameworks such as the Behaviour Change Wheel (BCW), can further support this process. Such technologies, developed using co-creation and behaviour change frameworks, can improve health outcomes for underserved patient populations, such as migrants, by addressing their unique needs. This study explores how co-creation and behavioural science can inform the adaptation of a digital preparedness tool for primary care patients with intercultural backgrounds. Objective: This study aimed to gain insight into international students’ experiences with primary care in Germany and explore whether adapting an existing digital patient preparedness intervention could address communication challenges. Using co-creation methods and the Behaviour Change Wheel (BCW), we identified key design specifications and behaviour change levers to inform tool development. Methods: A mixed-methods design was used to identify design specifications for a DHI across four co-creation workshops with 12 students at an international university in Germany. Quantitative data were used for descriptive insights, and qualitative data were analysed using qualitative content analysis. Workshops were informed by the BCW and the Health CASCADE co-creation methods selector tool. Results: Co-creators reported feeling misunderstood, anxious, and ill-informed during primary care interactions, with system-level barriers compounding communication difficulties. Despite this, many engaged in preparatory behaviours (e.g., note-taking) to manage uncertainty and structure their consultations. Feedback on an existing digital intervention was mixed: while co-creators appreciated its intent, structured lesson formats were seen as too time-consuming. Participants preferred a concise, interactive design. Communication prompts, appointment scheduling, and personalised feedback were frequently requested features, though tool adoption was seen as contingent on addressing broader system-level frustrations. Conclusions: In addition to identifying the needs of the target group and the design requirements for an effective digital intervention, the study also demonstrates how co-creation methods can be integrated with the BCW to inform the development of digital health tools for clinical settings. Migrants’ negative experiences, often stemming from unclear communication, perceived indifference, and difficulty navigating the complexities of a foreign healthcare system, may be mitigated through co-designed, personalised digital interventions. Frequently requested features, such as appointment scheduling, clinic directories, test result access, and interactive tools like chatbots, could help bridge gaps caused by limited healthcare access, language barriers, and intercultural differences.
Background: The analysis of symptom relationship is clinically essential in sleep medicine. Network modeling for sleep symptoms offers an interesting perspective to model and quantify symptom architec...
Background: The analysis of symptom relationship is clinically essential in sleep medicine. Network modeling for sleep symptoms offers an interesting perspective to model and quantify symptom architecture. Notably, the perceived causal networks (PECAN) method represents a way to systematically collect how individuals themselves perceive the causal influence of their symptoms. However, its applicability remains limited by the difficulty of collecting data from a large number of subjects. Objective: Based on the “theorAIzer” framework, we developed a LLM-based PECAN using a pretrained large language model (LLM) to evaluate perceived causal relationships between sleep symptoms. We hypothesized that the causal structure derived from large corpora could support the systematic mapping of symptom interrelations within a collective latent space, by mobilizing this distributed memory through network analysis. Methods: Twenty-nine sleep symptoms were selected. Using the theorAIzer framework with prompt ensembling, a pretrained LLM (ChatGPT, July 2025 version; OpenAI) was queried to assess perceived causal relations by determining directionality, weight, and valence. Networks were visualized after regularization with graphical LASSO and model selection by eBIC; strength-type centrality was calculated, and robustness assessed with bootstrap resampling (N = 2,000). Results: The LLM-based PECAN comprised 29 nodes and 46 directed, weighted and valenced edges. Insomnia maintaining, insomnia initiating, and insomnia early were strongly linked to non-restorative sleep (respectively at w=0.77, 0.75, 0.68), which in turn had cascading effects on daytime sleepiness (w=0.70) and fatigue (w=0.72). Centrality analysis revealed hub-like symptoms such as non-restorative sleep (z=3.16), daytime sleepiness (z=1.96), fatigue (z=1.86), cognitive symptoms (z=1.84), and sleep inertia (z=1.32). Network robustness analysis indicated a stability coefficient of 0.55, supporting robustness of edges and centrality metrics. Conclusions: The resulting network reproduced well-established associations between sleep symptoms observed in clinical and epidemiological studies. In the future, the comparison between collective LLM-based and individualized PECAN networks could allow more precise modeling of a digital twin of a specific patient grounded in perceived causal networks of sleep symptoms. Clinical Trial: Not applicable
Background: Robust and adaptive artificial intelligence (AI) governance frameworks are essential to ensure the responsible, sustainable and effective integration of AI-based technologies in health sys...
Background: Robust and adaptive artificial intelligence (AI) governance frameworks are essential to ensure the responsible, sustainable and effective integration of AI-based technologies in health systems (HS). Over the past decade, numerous frameworks for governing AI in HS have been developed to foster accountability, support implementation and mitigate risks such as bias, compromised quality of care, data breaches and adverse financial impacts. However, current frameworks often fail to reflect the multidimensional and dynamic nature of AI governance in HS. Objective: This study had two objectives: (1) To review and synthesize existing AI governance frameworks for HS; and (2) To propose an Integrative AI Governance Model that identifies key components to guide AI-related policy, practice and research in HS. Methods: We conducted a systematic review of AI governance frameworks for HS published from November 2014 to July 2025. Sources included eight academic databases (PubMed, MEDLINE, Embase, ACM Digital Library, Web of Science, Scopus, Social Sciences Abstracts and PsycINFO), grey-literature databases, and the web portals of international organizations. Inclusion criteria covered peer-reviewed articles and reports proposing a framework, guideline, standard or position statement on the governance of AI in HS. We excluded abstracts, letters to the editor, commentaries, essays, viewpoints, conference proceedings, and articles in languages other than English, French, Spanish or Portuguese. Two reviewers independently selected papers, assessed framework quality using the Appraisal of Guidelines for Research and Evaluation for Health Systems (AGREE-HS), and extracted data. A thematic analysis was then conducted. Results: A total of 18 AI governance frameworks for HS were identified. Most were published between 2022 and 2024 and were rated as moderate or low quality. The frameworks targeted four levels: international (n = 3), national (n = 4), local (n = 3) and organizational (n = 8). The composition of actors within governance structures varied across levels. Six key governance processes in HS emerged as critical: (1) Needs and/or problem identification; (2) Data governance; (3) Risk assessment and management; (4) Validation and/or evaluation; (5) Maintenance and monitoring; and (6) Integration. Four pivotal relational mechanisms were identified: (1) Ethical principles and/or values; (2) Education and training; (3) Standards and regulations; and (4) Communication. Barriers and challenges included poor alignment across interconnected policy domains and governance levels, the substantial resources required for effective implementation, and the ongoing demands of continuous monitoring of AI-based technologies. Conclusions: The findings highlight key elements of AI governance, including structures, processes and relational mechanisms, distributed across the international, national, local and organizational levels. The proposed Integrative AI Governance Model for HS aims to inform constructive policy and practice discussions on how to ensure the responsible, sustainable and effective integration of AI-based technologies into HS. Clinical Trial: The protocol for the systematic review has been registered on the Open Science Framework (OSF) and is available at: https://doi.org/10.17605/OSF.IO/MCBTS
The accurate segmentation of the human brain is essential for early detection of several diseases like Dementia and Alzheimer’s. Accurately pinpointing the anatomical structure of the brain is cruci...
The accurate segmentation of the human brain is essential for early detection of several diseases like Dementia and Alzheimer’s. Accurately pinpointing the anatomical structure of the brain is crucial for precise and dependable diagnostic approaches in various biomedical fields. However, current methods, whether manual or semi-automated, are often time-consuming. Classifying and segmenting of tissues in the brain can shed light on how the tissue contents will vary in order to facilitate early diagnosis. This study aims to implement machine learning algorithms for detection of Dementia and Alzheimer’s diseases by classifying brain tissues using Magnetic Resource Imaging (MRI) images. The proposed research is carried out by using dataset of 300 samples with different attributes, applying various machine learning algorithms like canny edge detection, thresholding, K-Means clustering and Fuzzy C means clustering. The dataset was pre-processed, segmented, and classified using multiple performance metrics. It is observed that Fuzzy C means Clustering demonstrated achieves better performance than edge detection, thresholding, and K-Means clustering techniques in terms of the jaccard index for both white and grey matter. Fuzzy C means Clustering achieves the maximum classification accuracy of 97.82%. This shows the effectiveness of Fuzzy C means Clustering in classifying brain tissue and predicting diseases like Dementia and Alzheimer’s. This study's findings advocate for the Fuzzy C means Clustering algorithm as an auspicious model for classifying the brain tissue and predicting brain diseases like Dementia and Alzheimer’s using MRI images
Background: As the number of cancer survivors continues to grow, optimizing long-term survivorship care models has become increasingly important. Telehealth has the potential to improve access to heal...
Background: As the number of cancer survivors continues to grow, optimizing long-term survivorship care models has become increasingly important. Telehealth has the potential to improve access to healthcare for survivors; however, studies evaluating telehealth in this population remain limited. Additionally, concerns persist regarding equity in technology access and digital literacy. Objective: This study aimed to examine demographic factors and patient attitudes influencing telehealth use among cancer survivors compared to the general population. Methods: Adult participants were identified from the nationally representative database Health Information National Trends Survey 6 (HINTS 6). Multivariate logistic regression was used to calculate the predictors of telehealth use among cancer survivors. Chi-square tests compared the prevalence of reported reasons of not using telehealth in the last 12 months between cancer survivors and the general population. Results: A total of 239,557,883 individuals were included in this study, 7.7% of whom are cancer survivors. Older age was associated with lower telehealth use (adjusted odds ratio [aOR]=0.11; 95% CI: 0.02–0.59 for patients aged ≥65, compared to those under 40 years old). Higher education (aOR=2.55; 95% CI: 1.24–5.27) and heart disease history (aOR=2.52; 95% CI: 1.20–5.28) were associated with increased telehealth use. Employed (aOR=0.46; 95%CI: 0.22-0.97) and retired (aOR=0.37; 95%CI: 0.18-0.77) cancer survivors were less likely to use telehealth than unemployed individuals. Of the non-users, over 60% reported that telehealth options were not offered, and 80% preferred in-person visits. Technical issues and privacy concerns were not major factors in utilizing telehealth. Conclusions: Despite greater telehealth use among cancer survivors, a negative association between older age and telemedicine utilization persists. Efforts should focus on improving access for older cancer survivors and addressing employment-related factors, patient attitudes, and telehealth availability. Future studies should explore personalized approaches to enhance cancer survivors’ healthcare experiences.
Objective: To compare different approaches to using the electronic health record (EHR) to build a cohort of Hemophagocytic Lymphohistiocytosis (HLH) patients, and to evaluate characteristics and outco...
Objective: To compare different approaches to using the electronic health record (EHR) to build a cohort of Hemophagocytic Lymphohistiocytosis (HLH) patients, and to evaluate characteristics and outcomes of patients meeting the HLH-2004 diagnostic criteria who received HLH-directed therapies to those who did not.
Methods: Three approaches to cohort development in the EHR were taken by identifying patients with: (1) an HLH-specific ICD-10 code, (2) an HLH-specific treatment plan, and (3) meeting the HLH-2004 clinical criteria for diagnosis of HLH. Among patients who met the HLH-2004 criteria, we evaluated the characteristics and outcomes of patients who received HLH-directed therapies to those who did not. HLH treatment was defined as either any chemotherapy, or HLH-specific therapy (dexamethasone, methylprednisolone, anakira, ruxolitinib, cyclosporine, etoposide or emapalumab).
Results: We identified 388 patients with possible HLH across the three cohorts. An HLH ICD-10 diagnosis (n=220) and meeting five or more clinical criteria (n=245) were much more common than a HLH treatment plan (n=42). Among the patients meeting HLH-2004 clinical criteria, 193 (79%) received HLH-directed therapy. There was no difference in any specific HLH criteria between those who did and did not receive HLH-directed therapy. In-hospital mortality was very high among both groups and was 15.0% among those who received HLH-directed therapy and 13.5% among those who did not receive HLH-directed therapy. Among 1325 patients with an elevated ferritin and fever, only 252 (19%) met >5 clinical criteria.
Conclusions: Constructing HLH cohorts from EHR data is challenging, with diagnosis codes, treatment plans, and clinical criteria each capturing distinct but overlapping populations.
Background: Background: The internet has deeply penetrated all aspects of our social lives. It has served as a vital platform for social, economic, and cultural activities among individuals, and data...
Background: Background: The internet has deeply penetrated all aspects of our social lives. It has served as a vital platform for social, economic, and cultural activities among individuals, and data are rarely available to analyze the trends of networks in China and online health services. Objective: Objective:The aim of this study was to determine the development of the Internet, trends, and Internet medicine using a comprehensive analysis of public data from 2014 to 2025. Methods: Methods:Data were retrieved from the official website of the China Internet Network Information Center (CNNIC) from June 2014 to June 2025. The study was conducted in 31 province/autonomous regions/municipalities, excluding Hong Kong, Macau, and Taiwan. The participants were citizens older than 6 years who had a telephone or mobile phone. The CNNIC conducted a stratified two-stage sampling survey using a computer-aided telephone access system. Results: Results: From 2014 to 2025, an increasing trend was observed in the number of Internet users and Internet penetration rate in China, and it showed an upward trend towards the number of Internet users,both in urban and rural areas. A consistent increasing trend was detected in the number of mobile internet users. In contrast, desktops and laptops showed a declining trend. The number of online health users in China showed an “V-shape” change from 2020 to 2025. At the end of 2025, the total number of online medical users reached approximately 393 million, representing 35.0% of all Internet users. Conclusions: Conclusions: The Internet in China continues to develop significantly and steadily, with an increasing number of Internet and online medical users in both urban and rural areas. The findings suggest that policymakers and physicians should further promote Internet-based healthcare with new approaches, such as short videos, to realize the overall health of the general population. Clinical Trial: None.
Background: Globally, digital health interventions (DHIs) enhance HIV care through technology, especially among women living with HIV (WLHIV), who face unique Challenges that affect their treatment. T...
Background: Globally, digital health interventions (DHIs) enhance HIV care through technology, especially among women living with HIV (WLHIV), who face unique Challenges that affect their treatment. This study assessed the feasibility of integrating DHIs into HIV care in Kisumu by examining their acceptability among WLHIV and identifying factors that influence their intention to use these tools. Objective: (1) To determine the feasibility of integrating digital health interventions into care for
women living with HIV in Kisumu.
(2) To identify factors that influence the adoption of Digital health interventions. Methods: A cross-sectional survey based on the Unified Theory of Acceptance and Use of Technology
2 (UTAUT2) was administered to evaluate the acceptability of SMS, teleconsultations, online support groups, and health applications. Summary statistics quantified acceptability, multivariate regression models examined associations between UTAUT2 constructs and behavioral intention, and Analysis of Variance identified sociodemographic predictors. Results: A total of 385 WLHIV (mean age 35·8 years) participated. Behavioral intention to use all four DHIs was high, with more than 80% rating their willingness at ≥4 on a five-point scale. Performance expectancy, hedonic motivation, habit, and price value were significant predictors of intention (p < 0·05). Higher education level was strongly associated with increased intention (p < 0·001), while older age was associated with reduced intention Conclusions: WLHIV in Kisumu demonstrated a strong willingness to adopt digital health tools in their routine care. The intention to use DHIs was primarily influenced by perceived usefulness, affordability, enjoyment, and familiarity with similar technologies. These results support the integration of digital health solutions into HIV care for women in this setting.
AI-powered therapy chatbots and virtual companions are rapidly entering mental health care. For attention-deficit/hyperactivity disorder (ADHD), they promise timely psychoeducation, behavioral coachin...
AI-powered therapy chatbots and virtual companions are rapidly entering mental health care. For attention-deficit/hyperactivity disorder (ADHD), they promise timely psychoeducation, behavioral coaching between visits, and structured inputs for measurement-based care across clinics, schools, and homes. Yet practical guardrails—especially for minors—have not kept pace with deployment. This Viewpoint advances a nurse-led, risk-tiered framework to guide safe, effective, and equitable integration of therapy chatbots into ADHD services. Drawing on ADHD care guidelines, emerging AI governance instruments, and lessons from digital health implementation, we identify six persistent gaps: risk classification and predetermined change control plans for adaptive models; child-specific safeguards, including content safety, age gating, and reliable crisis escalation; equity-by-design procurement and reimbursement; interoperable outcomes and safety reporting; workforce readiness with human-in-the-loop oversight led by nursing; and privacy-preserving real-world evidence (RWE). We present a three-layer framework aligning policy levers, implementation enablers, and outcomes, and we compare five complementary policy options: status quo self-regulation; risk-tiered regulation with PCCPs; voluntary certification with public procurement criteria; reimbursement for nurse-delivered digital ADHD care; and a federated RWE and safety surveillance network. A phased roadmap details preparation, sandbox pilots, scale-up with guardrails, and continuous learning, alongside a concise evaluation set spanning access and equity, safety signals, clinical and functional outcomes, experience, and economic value. Taken together, risk-tiered governance, procurement aligned with transparency and age-appropriate design, financing for nurse-led integration, and federated RWE can accelerate safe, equitable adoption of therapy chatbots for youth with ADHD while the evidence base matures.
Background: Hepatitis B virus (HBV) and hepatitis C virus (HCV) are significant global health concerns, particularly prevalent in low- and middle-income countries (LMICs). In China, a significant numb...
Background: Hepatitis B virus (HBV) and hepatitis C virus (HCV) are significant global health concerns, particularly prevalent in low- and middle-income countries (LMICs). In China, a significant number of international migrants from LMICs reside, many of whom are at high risk of HBV/HCV infection with few test utilization. Previous studies presented Pay-it-forward (PIF) strategy has proven effective in promoting sexually transmitted infections (STIs) test in various populations. This study aims to evaluate the effectiveness of a PIF intervention in promoting HBV/HCV testing among international migrants from LMICs in China. Objective: Aims to evaluate the impact of a pay-it-forward (PIF) intervention in promoting hepatitis B virus (HBV) and hepatitis C virus (HCV) testing among international migrants from low- and middle-income countries (LMICs) residing in China. Methods: A two-arm cluster randomized controlled trial will be conducted in Guangzhou, China. Participants will be recruited from a public hospital serving a large migrant community. Eligible participants will be randomly assigned to either the PIF intervention arm or the control arm in a 1:1 ratio. Participants in the intervention arm will receive free HBV/HCV tests donated by previous participants and will have the opportunity to donate to support future tests. The control arm will receive standard medical services with self-paid testing. The primary outcome is the proportion of participants tested for both HBV and HCV. Data will be collected through a self-administered questionnaire and hospital records, and analyzed using generalized estimating equations to account for clustering effects. Results: The data collection has been completed, and the information of 100 participants was included to the data analysis. Conclusions: This study is innovative in targeting international migrants from LMICs in China and employing the PIF strategy to promote HBV/HCV testing. The PIF intervention is expected to increase testing rates by addressing financial barriers and fostering a sense of community support. The findings will contribute to the understanding of HBV/HCV testing promotion among this understudied population, with potential implications for public health policy and practice. Clinical Trial: ChiCTR2400082560. Registered on 1st April 2024.
Background: Aging is inherently linked to increased vulnerability to adverse events, with falls being a primary concern for public health. Falls are the leading cause of severe injury and death among...
Background: Aging is inherently linked to increased vulnerability to adverse events, with falls being a primary concern for public health. Falls are the leading cause of severe injury and death among individuals over 65 years, significantly impacting their health, quality of life, and mobility 1,2. This growing issue significantly burdens healthcare systems, requiring extensive resources for hospitalization, rehabilitation, and long-term care 3. These challenges require innovative solutions that can effectively mitigate falls risk and improve the safety, independence, and quality of life for older adults while also easing the strain on healthcare systems 4.
Several factors increase the risk of falls in older adults, including aging, low muscle mass due to physical inactivity, smoking, alcohol consumption, and malnutrition 5,6. Comorbidities such as diabetes, hearing loss, cognitive decline, poor sleep, chronic pain, and depression further exacerbate falls risk, leading to frailty and mobility limitations 7. Additionally, many older individuals live alone, which increases the likelihood of delayed help after a fall 8.
Declines in physical, cognitive, and sensory functions significantly raise fall risk, making it increasingly important to identify innovative solutions to prevent falls and promote healthy aging 9. As Professor Bernard Isaacs (1924-1995) remarked, "A child takes one year to acquire independent movement and ten years to acquire independent mobility. An older adult can lose both in a single day." This highlights the potentially fatal consequences of falls, which can severely compromise mobility and independence 2. Recent technological advancements have introduced valuable tools for geriatric healthcare, offering solutions that improve quality of life, promote autonomy, and optimize healthcare delivery for older individuals 10.
Technologies such as wearable devices (smartwatches and health sensors), telemedicine, robotic assistance, and health management systems play a central role in monitoring vital signs, facilitating early detection of health issues, and enabling remote care 11,12 In addition, technologies for rehabilitation, such as exoskeletons and exercise applications, provide support for physical activity, aiding in the prevention of falls and enhancing recovery 13,14. Building on the advent of the Internet of Things and Artificial Intelligence, the spectrum of possible solutions and applications continues to grow, with increasing the potential to monitor and predict fall risk and to enhance rehabilitation procedures 15.
Despite these advances, challenges remain, including the accessibility of technologies, their integration into existing care systems, and the need for personalized solutions 16. The lack of coordination among various technological platforms can reduce efficiency and complicate the interpretation of data, while cost and usability can limit access for many individuals 17. Moreover, ensuring that non-pharmacological interventions (e.g. exercise-based technology) are tailored to the unique needs of each individual is essential for long-term success 18.
The search for innovative solutions in public health is driven by the growing challenges of the aging population, particularly in fall prevention, chronic disease management, and overall well-being 19. As life expectancy increases, the prevalence of debilitating conditions also rises, requiring sophisticated and personalized approaches 20. Innovations such as wearable devices and remote monitoring systems offer the potential to enhance care quality, by enabling more precise and effective interventions. However, their adoption depends on accessibility, economic feasibility, and ease of use—especially for older adults with varying levels of digital literacy 21.
The effectiveness of these solutions must be rigorously validated through dedicated studies to ensure improved health outcomes and reduced long-term healthcare costs. Effective technologies can prevent unnecessary complications and hospitalizations, while personalized interventions, based on precise data and continuous monitoring, address the specific needs of each individual 20,22. Digital technologies can offer accessible, customized solutions that overcome the limitations of traditional approaches, promoting safer and healthier aging 23.
Collaboration between healthcare professionals, developers, and final users' contributions may also be important to ensure that solutions are relevant, effective, and sustainable in the long term 24. Identifying and addressing limitations during the research and development process can reduce barriers to adoption and improve implementation, increasing the likelihood that fall prevention technologies will be successfully integrated into care strategies for the aging population 9.
Given these challenges, there is a growing need for innovative and sustainable solutions that address the multifaceted nature of fall prevention. This study aims to lay the foundation for the development of a web-based medical device and app platform that integrates digital technologies, physical-functional assessments, and user-centered approaches to predict and prevent falls in older adults. Objective: To explore, evaluate, and establish the foundation for Stage 1 of the Sustainable and Accessible Fall-Prevention Medical Device Technologies for Older Adults’ Health (S@FHe-RP).
Research Questions
I. What digital medical device technologies are currently available for predicting fall risk in older adults, and how do they compare in terms of functionality, usability, and effectiveness?
II. Which physical-functional assessments are commonly used to evaluate fall risk in older adults, and how can these be adapted or enhanced through medical device–based digital technologies?
III. How do end users, including healthcare professionals and nursing home staff, perceive the acceptability, feasibility, and functionalities of fall-prevention medical devices?
IV. Which bio-socio-demographic factors are essential for developing a reliable and accurate medical device–driven fall prediction model in long-term care facilities?
V. How can the integration of multidisciplinary and technological approaches, including medical device innovation, overcome the limitations of current fall-prevention strategies and support the development of sustainable solutions in long-term care facilities? Methods: This research protocol is structured into four interconnected studies (Stage 1–Stage 4), each designed to systematically align the research process with the overarching objectives of the project. Stage 1 involves a scoping review (Study 1) to identify and map existing digital technologies used to predict fall risk in older adults. Stage 2 (Study 2) focuses on a comprehensive systematic review comparing traditional and technology-adapted physical fitness assessment tests. Stage 3 (Study 3) explores the development of a statistical prediction model based on bio-sociodemographic indicators to estimate fall risk. Finally, Stage 4 (Study 4) integrates the end-users’ perspectives—health professionals and caregivers in long-term care settings—to inform the design and implementation of a sustainable, user-centered fall-prevention technology.
Together, these four stages create a cohesive framework that bridges evidence synthesis, model development, and practical application, ensuring scientific rigor and real-world relevance. The methodology follows recent approaches 25,26, integrating technological, clinical, and user-centered dimensions.
Project Design
A mixed-methods approach will be employed, comprising four complementary and consecutive studies to support the development of a low-cost, web-based app platform for fall prevention in older adults. This platform will comply with European medical device regulations, meeting validation criteria for medical devices 27. The research characterizes contemporary translational research, which involves effectively translating scientific knowledge into new health technologies 28. Furthermore, the development of this medical device will involve researchers from distinct areas of clinical, technological, and industrial sectors, following a User-Centered Design (UCD) approach 29.
Figure 1.
Module A: Scoping review of new digital technologies to predict falls
This phase involves a systematic scoping review of the literature across relevant databases, specialized journals, and grey literature, aiming to analyze studies examining new digital thecnologies used to predict fall risk in older adults. This study will adhere to established methodological guidelines, including the exploratory review framework by Arksey and O'Malley (as refined by 30), and the Joanna Briggs Institute (JBI) guidelines 31. Results will be reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines 32.
A reproducible four-step search strategy, as recommended by JBI 33, will be implemented across databases (see Table 1): Medline, Web of Science, SCOPUS, Cochrane Library, B-On, CINAHL, PsycINFO, Google Scholar, and Open Access Thesis and Dissertations. The search terms included: ((Falls prevention) OR (Fall risk)) AND (Elderly) AND (Digital technologies) AND (Long-term care)). The inclusion criteria, guided by the Joana Brigs framework 34, will include studies involving older adults (≥60 years) (Population), examining technological devices assessing fall risks related to gait performance (Concept), across various settings, countries, and sectors of the economy (Context).
Two reviewers will design the strategy, which will be reviewed by a third expert using the PRESS checklist 35. Selection criteria will include original research, systematic reviews, theses, grey literature, patents and prototypes from the last ten years. Quantitative studies (randomized controlled trials, non-randomized trials, quasi-experimental studies) and observational studies (descriptive, exploratory, and analytical designs) will be considered. The initial search will be conducted in English, and may be expanded to include Spanish and Portuguese depending on preliminary findings. Findings will summarize studies by PCC, answer research questions, and describe study characteristics.
Module B: Review of Traditional and Tech-Adapted Physical Fitness Tests
This comprehensive review will identify traditional and technology-adapted physical-functional tests (PFT) for fall risk assessment in older adults. The review will focus on the effectiveness, ease of use, accuracy, and implementation challenges. A systematic search across multiple databases (Medline via PubMed, Scopus, Web of Science, CINAHL) will target studies from the last decade using terms such as “fall risk assessment,” “functional test,” “older adults,” “physical test,” “digital adaptations,” and “technology for fall prevention.” Inclusion criteria include original research, systematic reviews, and relevant grey literature.
Results will follow PRISMA guidelines 36, Cochrane guidelines for systematic reviews, and the GRADE methodology for evaluating the quality of evidence 37. The PICO framework 38 will structure reporting: Population (≥ 60 years, including clinical subpopulations), Intervention (traditional and adapted PFTs), Comparison (traditional vs. digital/technological adaptations), and Outcome (effectiveness on fall risk assessment).
Module C: Fall risk prediction statistical model
This cross-sectional study is aimed to develop a predictive algorithm for fall risk based on bio-socio-demographic indicators. This study will involve approximately 300 institutionalized older adults from Coimbra, Portugal, levering data from the PRO-HMESCI project 39 project. Participants will provided informed consent, with ethical approval obtained from the Faculty of Sports Sciences and Physical Education Ethical Committee, University of Coimbra (code number: CE/FECDEFUC/0002013, CE/FCDEF-UC/00112024).
Collected data includes sociodemographic data (age, marital status, education), anthropometric measures (weight, height, BMI), cognitive status 40, state of depression 41, comorbidity index 42, functional fitness (e.g. upper and lower body muscle strength and balance), and falls history.
Advanced statistical techniques will be applied to identify significant patterns and relationships between bio-socio-demographic indicators and risk of falls in older adults. Bivariate analysis methods, such as the chi-square test and Pearson's correlation coefficient, will be used to explore associations between categorical and continuous variables. Multivariate logistic regression will be applied to identify the most significant factors contributing to fall risk 43 and construct the predictive model. Model validation will be performed using cross-validation techniques and Receiver Operating Characteristic (ROC) curve analysis to assess the accuracy and predictive power of the algorithm 44.
Module D: End-Users' Perspective study
The objective of this study is to validate the necessity, feasibility, and acceptance of a technology-based fall prevention product by healthcare professionals working in long-term care facilities. This study will adopt a mixed-methods approach, combining qualitative and quantitative techniques to evaluate the acceptance and perceived utility of a new technology-based solution for fall prevention in older persons in care facilities. It seeks to understand user perspectives, barriers, and facilitators, as well as institutional specificities related to long-term care, based on the UCD methodology 45.
The adapted Technology Acceptance Model (TAM) serves as the theoretical framework connecting the study's qualitative and quantitative assessement 46. Insights gathered through qualitative interviews will inform the contextual understanding of perceived usefulness, ease of use, and behavioral intention, which are central to the TAM framework 46. These constructs guide the design and evaluation of fall prevention technologies, as visualized in Figure 2, ensuring alignment with user needs and practical applications.
Participants include higher-education healthcare professionals (nurses, physicians, physiotherapists, gerontologists) with at least one year experience in long-term care. For the qualitative phase, theoretical saturation is expected to occur after 15–20 interviews, following similar previous studies 47. For the quantitative phase, the sample size will be calculated using G*Power, based on the sample size as shown in previous studies 48. Qualitative analysis will employ thematic content analysis using NVivo® 49; quantitative analysis will employ TAM-based questionnaire to evaluate variables such as perceived usefulness (10 items), perceived ease of use (11 items), behavioral intention (4 items), and demographic data (6 items) 50. Data collection will occur via online and in-person distribution, with follow-up to ensure response completeness. Descriptive and inferential statistical analyses will be conducted using SPSS.
Ethical Procedures
The research protocol was approved by the same committee under the project number CE/FCDEF-UC/00112024, which ensures compliance with ethical standards for research involving human participants. Procedures will comply with the European Union directives 51, and relevant guidelines from the International Organization for Standardization 52. Clinical studies will also adhere to the ethical principles outlined in the Declaration of Helsinki and the guidelines for Good Clinical Practice 53. As we are currently in Stage 1 of the project, the Portuguese regulatory body responsible for overseeing the evaluation authorization, and monitoring of medicines, medical devices, and health products in Portugal 54 approval is not required at this point, but it will be necessary in Stage 2 when developing and validating the platform prototype. Results: The study aims to significantly advance fall risk prevention by integrating traditional and technological approaches. A key outcome will be a comprehensive analysis of PFTs, both conventional and technology-adapted, to identify the most effective methods for assessing fall risk. By systematically comparing these approaches, the study will bridge the gap between traditional clinical assessments and emerging technologies 55, providing a roadmap for integrating innovative tools into routine practices and highlighting their complementary potential.
Additionally, the study will support the development and preliminary validation of low-cost, data-driven algorithm to predict fall risk in older adults. By combining bio-sociodemographic, clinical, and functional data, this tool will enhance clinical decision-making and enable timely , targeted interventions 56, with a strong emphasis on early screening and fall prevention 57.
The evaluation of existing fall risk assessment technologies will also play a central role, aiming to verify their reliability and accuracy. This assessment will help to identify strengths and limitations, guide future development, and establish benchmarks for next-generation tools. A particular focus on gait performance and fall risk will contribute to ongoing advancements in smart wearable devices and motion analysis technologies 14.
Moreover, the study will capture end-user perspectives, particularly from healthcare professionals working in long-term care facilities. It will explore factors influencing the adoption of fall prevention technologies, including barriers, facilitators, and overall acceptability. Applying the UCD approach will ensure that future solutions align with the real-world needs and preferences of those who use them 58.
Finally, this work will establish a solid foundation for developing a web-based medical device for fall-risk management. Following evidence generation and ethical ethical approval, the next phase will involve rigorous prototype testing to ensure safety, efficacy, and compliance with international standards, including EU and ISO guidelines 51. Conclusions: The research protocol aims to provide valuable insights into the development and adoption of fall prevention technologies for older adults using a user-centered design approach. By focusing on low-cost, sustainable, and accessible solutions, the study addresses the pressing need for equitable healthcare innovations—particularly in underserved and resource-limited contexts. The findings will contribute to enhancing fall prevention strategies and ensuring that future technologies are not only clinically effective but also aligned with real-world needs and preferences of their users.
Background: Severe tricuspid regurgitation (TR) is most commonly functional, related to left-sided heart disease or pulmonary hypertension. Carcinoid heart disease is a rare cause, and ovarian carcino...
Background: Severe tricuspid regurgitation (TR) is most commonly functional, related to left-sided heart disease or pulmonary hypertension. Carcinoid heart disease is a rare cause, and ovarian carcinoid tumors represent an uncommon source capable of producing isolated right-sided valvular lesions. Objective: To present an educational case of isolated severe TR revealing a probable ovarian carcinoid tumor and to discuss diagnostic reasoning, management, and prognosis in advanced high-risk TR. Methods: We analyzed the clinical, echocardiographic, and imaging findings of an 84-year-old woman admitted for right heart failure. Computed tomography, tumor marker assays, and risk scoring (TRI-SCORE) guided the etiologic and therapeutic approach. Results: Echocardiography revealed a dilated right ventricle with preserved systolic function, severe TR due to leaflet malcoaptation, and massive annular dilation (66 mm). Imaging showed a right latero-uterine cystic mass (53 × 56 mm) suspicious for ovarian neoplasm, with ascites and pericardial effusion. Tumor markers (CEA and CA19-9) were elevated. Given her high TRI-SCORE (≥6), surgical or percutaneous intervention was contraindicated. She was managed medically with high-dose diuretics and referred for oncologic evaluation. Conclusions: Ovarian carcinoid tumors can cause isolated right-sided valvular fibrosis via systemic serotonin release. In advanced high-risk TR, surgery is rarely beneficial, and optimized medical therapy remains the mainstay. This case highlights the importance of multidisciplinary evaluation and early recognition of rare cardio-oncologic presentations.
Background: Mental health disorders affect approximately one in five adults in the United States, yet nearly half of those who could benefit from treatment cannot access care due to provider shortages...
Background: Mental health disorders affect approximately one in five adults in the United States, yet nearly half of those who could benefit from treatment cannot access care due to provider shortages, cost, and stigma. Recent advances in machine learning and natural language processing have prompted interest in deploying artificial intelligence systems to augment clinical practice, automate administrative tasks, and expand treatment access. Objective: The objective of this review was to examine the impact of artificial intelligence on mental health professionals by analyzing current applications, benefits, and risks across three major domains: chatbot-based therapeutic tools, clinical documentation and automation, and diagnostic and clinical decision support systems (CDSS). Methods: A narrative literature review was conducted, analyzing peer-reviewed publications, professional organization position statements, and implementation studies focused on artificial intelligence applications in mental health practice. The review encompassed chatbot-based interventions, clinical documentation automation systems, and diagnostic support tools, with a focus on their efficacy, limitations, and implications for clinical practice. Results: The review found that AI-based interventions demonstrate small to moderate effectiveness in reducing depression and anxiety symptoms but show significant limitations including inappropriate crisis responses and reduced effectiveness compared to human therapists. AI documentation tools can reduce administrative burden but are vulnerable to hallucinations that insert fabricated information into clinical records. AI diagnostic support systems show preliminary promise but require further validation. Conclusions: While artificial intelligence applications demonstrate promise in reducing administrative burden and providing supplementary mental health support, substantial limitations persist in clinical effectiveness, crisis response capabilities, and reliability. Current evidence indicates artificial intelligence functions best as an augmentation tool requiring continuous clinical oversight rather than as standalone interventions or direct patient care. Future research directions are suggested to address these challenges, enhancing the reliability and applicability of artificial intelligence systems in mental health clinical practice.
Background: The Objective Structured Clinical Examination (OSCE) is a prevalent method for evaluating clinical competence in medical education. As OSCEs become increasingly standardized and resource-i...
Background: The Objective Structured Clinical Examination (OSCE) is a prevalent method for evaluating clinical competence in medical education. As OSCEs become increasingly standardized and resource-intensive, alternative evaluation methods are being explored, particularly owing to the limited availability of certified examiners. However, few studies have investigated whether wearable technologies can effectively support OSCE assessment. Wearable devices may present a viable solution for recording and assessing clinical skills from the examiner’s perspective. Objective: This pilot study, conducted in 2024, aimed to investigate the feasibility and utility of a neck-mounted wearable camera for recording OSCE scenarios and to evaluate the assessability of clinical performance based on the obtained footage. Methods: Nine experienced medical educators participated in a simulated OSCE scenario involving ECG lead placement. All participants completed the initial live assessment and post-use questionnaire, while 8 completed the subsequent video-based reassessment. The authors utilized video recordings from both a fixed camera and a neck-mounted camera (THINKLET®) to assess the evaluability of each OSCE item. Following a washout period, evaluators re-assessed the recorded sessions. The authors analyzed interrater agreement using percent agreement and Cohen’s κ coefficient. A post-evaluation questionnaire captured evaluators’ experiences with the wearable device. Results: Cohen’s κ ranged from 0.258 to 0.913 (mean: 0.67), indicating substantial overall agreement. Visibility of fine motor skills, particularly in ECG electrode placement, appeared to be enhanced when using the neck-mounted camera, as inferred from higher assessment completion rates compared to fixed-camera recordings (odds ratio = 11.69; P < .001). Evaluators reported generally positive experiences with the device, although some noted issues with comfort, posture restriction, and limited visibility at low angles. Conclusions: This pilot study suggested that neck-mounted wearable cameras may enhance flexibility and visual accuracy in OSCE assessment, supporting their potential role in supplementing current evaluation practices. Further research is needed to standardize usage and address technical challenges.
Background: Parental burnout is an under-recognised syndrome characterised by emotional exhaustion, detachment from children, and reduced parental efficacy. It is associated with sleep disturbance, ad...
Background: Parental burnout is an under-recognised syndrome characterised by emotional exhaustion, detachment from children, and reduced parental efficacy. It is associated with sleep disturbance, addictive behaviours, suicidal ideation, and increased risk of child neglect and family conflict. Despite its public-health relevance, evidence-based interventions remain limited, particularly in low- and middle-income contexts. Objective: To evaluate the efficacy and safety of a mindfulness- and compassion-based group program—Inter-Care for Parental Burnout (IBAP-PB) —designed to reduce burnout symptoms in teleworking mothers. Methods: A three-arm randomised controlled trial (IBAP-BP, active control, waitlist) was conducted across Chile (December 2022–March 2023) with nine-month follow-up. Participants (n = 593) were women ≥ 18 years teleworking ≥ 1 day/week and living with ≥ 1 child. Exclusion criteria were self-reported severe psychiatric disorders. Randomisation was computer-generated and centrally concealed; data analysts were blinded. The IBAP-BP group attended eight weekly two-hour online sessions plus daily home practice integrating mindfulness and compassion. The active control performed relaxation and reflective journaling matched for duration and structure. The primary outcome was parental burnout (Parental Burnout Assessment, PBA) at nine months; secondary outcomes were mindfulness, balance of risks/resources, and adverse effects. Modified intention-to-treat analyses and multilevel structural models assessed effects over time. Results: Of 665 enrolled participants, 343 completed follow-up. At nine months, IBAP-BP produced greater reductions in parental burnout than the waitlist (mean difference = −0.81, p < 0.05; d ≈ 0.6). No significant difference was found between IBAP-BP and the active control, which showed transient improvements up to three months. Effects remained robust in sensitivity analyses. Adverse events were rare and mild across all groups. Mediation analyses showed inconsistent associations between mindfulness facets and outcomes. Conclusions: The culturally adapted, online IBAP-BP programme is a feasible, safe, and effective approach for reducing parental burnout in working mothers, with effects sustained over nine months. Clinical Trial: ClinicalTrials.gov Identifier: NCT05833269
Background: Large language models (LLMs) such as ChatGPT are increasingly used to support health-related queries and
decision-making. However, these models can be “jailbroken” through adversarial...
Background: Large language models (LLMs) such as ChatGPT are increasingly used to support health-related queries and
decision-making. However, these models can be “jailbroken” through adversarial prompts that bypass safety filters
and elicit harmful or medically inappropriate responses. In healthcare contexts, such vulnerabilities pose serious
risks. Understanding how jailbreak susceptibility varies across languages is essential for developing robust
safeguards and promoting equitable access to safe health information. Objective: This study aims to systematically compare and contrast the vulnerability of a health LLM for jailbreaking across
three languages: English, Spanish, and Hindi (transliterated using the Latin alphabet) based on emoji and
permutation cipher attacks. Methods: We analyzed 1,000 input prompts per language, drawn from the BeaverTails dataset, across three harm categories:
self-harm, violence, and drug abuse. Each prompt was modified using emoji and permutation cipher techniques,
resulting in 6,000 input-output pairs. Model responses were evaluated by human coders to determine the success rate
of jailbreak attempts across languages and cipher types. Results: Hindi prompts showed the highest vulnerability, with 787 successful jailbreaks using emoji ciphers and 873 using
permutation ciphers. Spanish and English followed, with lower success rates across both cipher types. Differences in
jailbreak success across languages and cipher strategies were statistically significant. Additionally, attacks targeting
violence-related prompts were more successful overall than those targeting drug-related or self-harm content,
indicating variation in vulnerability by harm type. Conclusions: The findings of this formative study reveal that LLM safety performance varies substantially across languages and
harm categories, raising concerns about equitable protection in multilingual health communication. Disparities in
access to harmful content may contribute to downstream health risks. Strengthening multilingual content moderation
and developing language-aware safety mechanisms are critical steps toward safer and more inclusive health AI
systems.
Background: Background: Maternal health literacy plays a critical role in promoting maternal well-being and preventing adverse pregnancy outcomes, yet limited studies have focused on primigravida wome...
Background: Background: Maternal health literacy plays a critical role in promoting maternal well-being and preventing adverse pregnancy outcomes, yet limited studies have focused on primigravida women, particularly in low-resource settings like Egypt. The interplay between health literacy, partner support, and self-efficacy in preventing preterm birth is underexplored. Understanding these relationships is crucial for informing interventions that enhance maternal health outcomes. Objective: Aim of the Study
This study aims to examine the moderating role of partner support in the relationship between maternal health literacy and self-management self-efficacy in preventing preterm birth among primigravida women. Methods: Methods: A cross-sectional descriptive study was conducted using a two-stage random sampling approach, following the STROBE guidelines, with 288 primigravida women. Data collection tools included the Maternal Health Literacy Inventory in Pregnancy (MHLIP), Partner Support Scale, Self-Management Self-Efficacy Scale for Premature Birth Prevention (SMSE-PBP), and a socio-demographic questionnaire. Descriptive statistics, Pearson’s correlation, and multiple regression analyses were utilized. Results: Results: Participants exhibited moderate health literacy, excelling in health knowledge. Partner support strongly correlated with self-efficacy (r = 0.45, p < 0.01). Regression analysis revealed that health knowledge and partner support were significant predictors of self-efficacy (R² = 0.47, p < 0.001). Age, education level, and the number of antenatal visits were significant predictors of health literacy (R² = 0.39, p < 0.01). Conclusions: Conclusion: Maternal health literacy, partner support, and self-efficacy are crucial for positive pregnancy outcomes. Antenatal care should integrate these factors through targeted, culturally appropriate interventions, particularly in primary healthcare settings.
Background: Artificial intelligence (AI) is increasingly being utilized in many aspects of society, including healthcare and education. AI has the potential to enhance healthcare delivery, education,...
Background: Artificial intelligence (AI) is increasingly being utilized in many aspects of society, including healthcare and education. AI has the potential to enhance healthcare delivery, education, and administration. Healthcare trainees will increasingly be required to master these AI technologies. To teach trainees to effectively and ethically leverage AI technologies, educators must be appropriately trained and empowered to use these technologies. Objective: We developed a health professions education course to enable healthcare professionals to overcome their fears and concerns about integrating AI technologies into daily practice. The course was also designed to foster competency and facility with AI tools in educational, administrative, research, and clinical activities. Methods: Employing a multi-method approach, we analyzed data gathered from three different sources using Braun and Clarke’s six-phase reflexive thematic analysis. This involved familiarization with the data sources, generating initial codes, developing, refining, and defining the themes, and finally, writing up the results. Results: Our findings indicate that learners initially described misconceptions towards AI, frequently accompanied by negative and crippling affect, such as fear. It was only after experiential engagement with AI technologies that they were able to shift their perspectives and gain the confidence to integrate AI technologies in their daily practice. Conclusions: A brief six-week course on the use of AI technologies for healthcare professional educators, focused on experiential and peer-based learning, resulted in dramatic shifts in affect towards the technologies and their applications. It also propelled learners to shift increasingly outward in their discussion, application, and advocacy for AI technologies in their daily practice. Clinical Trial: Not Applicable
Background: Chronic diseases, notably behavioral health topics, impose a significant burden on health systems, especially among rural and Tribal communities, requiring reliable data-driven federal alg...
Background: Chronic diseases, notably behavioral health topics, impose a significant burden on health systems, especially among rural and Tribal communities, requiring reliable data-driven federal algorithmic decision modeling for investigating and prioritizing federal investments. Objective: To determine if initial algorithmic models can support high-priority federal decision requirements in behavioral health. Methods: Design: This original investigation developed and tested three geo-analytic decision models, applied to publicly-available U.S. data, including mortality data from 2018 to 2023 (Centers for Disease Control and Prevention), federal and Tribal behavioral health service operational data (Indian Health Service), and federal transportation data (U.S. Department of Transportation). Data analysis occurred from January 2025 to August 2025. Setting: Federal and Tribal health and safety systems. Participants: The analyses comprised of geographical areas that correspond to behavioral health needs and services among American Indians and Alaska Natives. Main Outcomes and Measures: Alcohol and drug related mortality, travel time and distance barriers to behavioral health services, and collocated factors in risk of human trafficking. Results: Nationally, 78 counties among 13 states were identified as prioritized investigation areas based on persistent and increasing alcohol or drug related deaths rates, where such crude death rates ranged from 1,197.8–1,848.7 per 100,000 AI/AN persons. An estimated 22,029 and 234,852 AI/AN persons were identified as residing in low physical access areas for behavioral health services within the American Southwest region during typical and non-typical business hours, respectively. Among the 80 AI/AN communities in the 300-mile study territory, risk indexes indicate 16 interpersonal risk exposure areas, representing an estimated 11,378 AI/AN persons, that require interagency studies to confirm the possibility of home separations and cases of interpersonal injuries. Conclusions: Algorithmic modeling of health and safety data can provide the geo-analytic evidence to support federal prioritization and investment decisions regarding complex needs and systems of health services.
Background: While smartwatches have revolutionized personal health monitoring, their utility for comprehensive cardiac assessment remains limited by single-lead electrocardiogram (ECG) acquisition. Th...
Background: While smartwatches have revolutionized personal health monitoring, their utility for comprehensive cardiac assessment remains limited by single-lead electrocardiogram (ECG) acquisition. This study introduces a novel software-based methodology to reconstruct a full 12-lead ECG from sequential smartwatch recordings, aiming for diagnostic comparability with conventional systems. Objective: We present a proof-of-concept clinical validation of this approach, addressing a critical unmet need in accessible cardiac diagnostics. Methods: A signal processing pipeline was developed to preserve ECG morphology across sequential smartwatch lead recordings, achieving synchronization via RR interval–based temporal resampling to generate a coherent 12-lead ECG. A clinical validation study was conducted in 20 patients with diverse cardiac pathologies and 2 healthy controls. Smartwatch-derived ECGs were compared with standard recordings. Diagnostic accuracy and visual interpretability were assessed by 85 healthcare professionals through a structured questionnaire. An independent arrhythmologist provided qualitative clinical validation for all cases. Results: The primary objective of reconstructing a 12-lead ECG from smartwatch signals was successfully achieved. Visual correlation scores between smartwatch-derived and conventional ECGs ranged from 77% to 91.4%, with a mean of 81%, indicating strong concordance. An average of 95.5% alignment in the electrical axis was observed. The highest diagnostic agreement was found in ischemic heart disease and bundle branch blocks, supporting clinical relevance. Conclusions: This study demonstrates proof-of-concept for reconstructing a 12-lead ECG from smartwatch-acquired signals with diagnostic comparability to conventional systems. This method expands smartwatch ECG capabilities, enabling accessible, advanced cardiovascular diagnostics and proactive patient monitoring. A European patent has been filed for this technology (reference:EP25382712.5).
Background:
Shifting surgeries from the stationary to the ambulatory setting is seen as a suitable way of increasing efficiency in the health care system. A significant increase in ambulatory proced...
Background:
Shifting surgeries from the stationary to the ambulatory setting is seen as a suitable way of increasing efficiency in the health care system. A significant increase in ambulatory procedures can therefore be observed internationally – particularly in the field of orthopedics. However, the interests and needs of patients are often insufficiently taken into account in this process. The "Power-AOP" research project was initiated to identify the associated challenges in the area of patient empowerment and to develop solutions. Using the field of orthopedics as an example, it investigates how the self-determination and participation of patients can be strengthened in the context of ambulatory surgery.
Methods:
Using a mixed methods approach, (health policy) recommendations will be developed that aim to strengthen patient empowerment in the context of ambulatory surgery. The project is scheduled to run for three years and comprises six work packages with a total of ten modules. In a first step, a scoping review will be carried out to map the existing literature. This will be followed by focus groups with patients and healthcare providers to gain deeper insights into their experiences and perspectives. The results will be quantified through a questionnaire-based survey. In order to identify a suitable patient population for this survey, an analysis of claims data will be conducted beforehand. The results will then be discussed and refined in two stakeholder workshops with key players in the health care system. In the final phase, a concept will be developed that contains actionable recommendations for strengthening patient responsibility in the context of ambulatory care.
Discussion:
This project will help to improve the patient empowerment in the context of ambulatory surgery. This allows patients to take a more active role in the process. On the one hand, this can lead to greater satisfaction with the process, particularly among patients. On the other hand, more active participation by patients can improve outcomes and avoid unnecessary readmissions or additional treatments.
Background: High-quality wound care requires early and effective interprofessional collaboration between medical, nursing, and pharmacy professionals. However, interprofessional education (IPE) in thi...
Background: High-quality wound care requires early and effective interprofessional collaboration between medical, nursing, and pharmacy professionals. However, interprofessional education (IPE) in this context remains limited in higher education. Immersive virtual reality (iVR) seems to be a promising IPE tool, enabling a standardized, realistic, and safe learning environment that allows multiple learners from different professions to train together. However, its educational effectiveness depends on an instructional design that supports learning while managing cognitive demands during immersive experiences. Objective: This study examined whether a newly developed interprofessional iVR wound-care training improves (1) procedural knowledge and (2) willingness to collaborate among medical, nursing, and pharmacy students, and how cognitive load relates to these outcomes. Methods: A within-subjects design with a pre- and posttest was implemented with 116 students from medicine, nursing, and pharmacy. Students completed two iVR sessions (~25 and 15 minutes) in interprofessional triads, addressing a pressure-ulcer case. The training integrated step-by-step scaffolding for the wound care task, and collaboration scripts to guide teamwork. Procedural knowledge and willingness to collaborate were assessed before and after the sessions, and cognitive load was measured after the sessions. Data were analyzed using repeated-measures ANCOVAs and a mediation model to test the preregistered effects. Results: Procedural knowledge increased significantly from pre- to posttest, F(1,107) = 26.19, p < .001, η² = .08. Cognitive load showed no significant effect on this gain. Willingness to collaborate did not change after the first session, F(1,80) = 3.55, p = .063, η² = .01, and was unaffected by cognitive load. Exploratory analyses showed that willingness to collaborate was significantly higher after the second session, t(64) = 3.16, p = .007, mean difference = 0.202). The effect on procedural knowledge and willingness to collaborate did not depend on the learner’s profession. Conclusions: These findings suggest that the iVR training effectively supported learning by providing clear structure and managing cognitive demands, enabling students from different professions to acquire procedural knowledge without being hindered by excessive cognitive load. The absence of cognitive load effects indicates that the instructional design, combining scaffolding and collaboration scripts, successfully balanced task complexity and guidance within the immersive environment. The delayed increase in collaboration willingness further suggests that attitudinal change requires sustained, repeated engagement in interprofessional contexts rather than a single exposure. Notably, no profession-related differences emerged in either procedural knowledge or willingness to collaborate, indicating that the iVR training supported learners equally across professional backgrounds. Overall, the results highlight the potential of iVR as a scalable, theory-based approach to IPE that can bridge disciplinary boundaries and prepare learners for effective teamwork in clinical practice.
Pretest–posttest pilot (n=38): WISEBOx reduced loot box purchasing at one month (32/38) and residual spending among those who continued purchasing. Further evidence is needed...
Pretest–posttest pilot (n=38): WISEBOx reduced loot box purchasing at one month (32/38) and residual spending among those who continued purchasing. Further evidence is needed
Background: This pilot randomized trial evaluated the immediate effects of a brief yoga intervention on physiological stress markers and emotional state in wellness tourism. Objective: To test whether...
Background: This pilot randomized trial evaluated the immediate effects of a brief yoga intervention on physiological stress markers and emotional state in wellness tourism. Objective: To test whether a 24-minute yoga session reduces salivary cortisol and salivary alpha-amylase, and increases heart rate (HR) and improves emotional states compared to waitlist control, while exploring individual variability. Methods: Methods: In a single-center, parallel-group, randomized waitlist-controlled pilot study (1:1 allocation), 19 participants were assigned to a 24-minute yoga session (n=10) or waitlist control (n=9). Primary outcome was change in salivary cortisol. Secondary outcomes included salivary alpha-amylase, HR, and emotional states (stress, calmness, concentration) via Apple Watch and Kansei Analyzer (EEG). Data were analyzed using t-tests and regression. Results: No significant differences in salivary cortisol or alpha-amylase were observed. Yoga increased HR during postures and meditation compared to control. Individual EEG analyses suggested stress reduction in some participants. Conclusions: Brief yoga may offer physiological and emotional benefits for wellness tourism, but larger trials are needed. Trial not registered due to pilot nature.
Background: South Australia’s public hospitals transitioned to the Sunrise (Altera Digital Health) electronic medical record (EMR) from 2010 but the new system lacked tools for near-real-time second...
Background: South Australia’s public hospitals transitioned to the Sunrise (Altera Digital Health) electronic medical record (EMR) from 2010 but the new system lacked tools for near-real-time secondary use of data to support clinical care, operations, and research. Objective: To design, implement, and evaluate a scalable Health Informatics System (HIS) within the Central Adelaide Local Health Network (CALHN) that securely integrates live EMR data and enables user-centred digital tools across clinical, coding, and operational domains. Methods: A cloud-native Health Informatics System (HIS) was developed on Microsoft Azure and Red Hat OpenShift using Terraform and ArgoCD for secure, reproducible deployment. Services employed CQRS, event-sourcing, and Apache Kafka for real-time data processing, with applications built in Scala.js and D3.js for responsive clinical interfaces. Governance frameworks aligned with SA Health’s Security Impact Assessment and Information Asset Classification processes and ensured compliance and safety. Clinical, corporate, and ethical committees oversaw EMR integration, data access, and research use. AI models were trained in secure, GPU-enabled environments with full audit trails. Sustainability was achieved through commercial agreements between CALHN, AusHealth, and HeartAI Pty Ltd, and was further supported by blended grant, professional services and equity funding. Results: Three sequential projects demonstrated coverage across key user groups:
1. Critical Care Informatics System extracted live EMR data for ward/bed-level displays, automated registry submissions and underwent iterative usability testing
2. CODEXA Clinical Coding Software system applied a custom Transformer based AI model to associate likely diagnostic codes using patient notes and estimate reimbursement amounts
3. The Patient Flow project is in the planning phases to establish a data-driven command centre for use in the Network Operations Centre Conclusions: A secure, scalable HIS can be deployed in a complex public health network through layered architecture, rigorous governance, and co-design with end users. The platform enabled real-time clinical displays, AI-assisted coding, and enterprise flow planning while maintaining safety and compliance. Clinical Trial: This trial is not registered.
Background: Loss of self-feeding ability due to severe upper extremity motor impairment (UEMI) limits independence, compromises nutrition, and reduces social participation. Robotic feeding devices are...
Background: Loss of self-feeding ability due to severe upper extremity motor impairment (UEMI) limits independence, compromises nutrition, and reduces social participation. Robotic feeding devices are an emerging category of assistive technology. Obi3 is a 3rd generation, Class I durable medical equipment (DME) robot intended to compensate for the movement of a human arm to restore self-feeding performance. The device is designed to enable patients to independently select and consume food and liquid using accessible switches or interfaces while maintaining culturally normative dining practices. Although earlier Obi generations showed promise, comprehensive usability data across multiple stakeholder groups remains limited. Objective: This study evaluated the usability, safety, and clinical relevance of Obi3 from the perspectives of patients, caregivers, and rehabilitation providers in real-world use. The findings were intended to generate evidence that informs clinical decision-making and determinations of medical necessity for DME consistent with the device’s FDA-cleared Indications for Use and clinician-supervised implementation. Methods: A mixed-methods usability study enrolled 50 participants, of whom 42 completed follow-up surveys after a one-week home trial of Obi3. Participants included 15 patients (pediatric and adult), 14 caregivers, and 13 providers. Quantitative measures included the System Usability Scale (SUS), survey items adapted from the Matching Person and Technology (MPT) framework, and self-feeding impairment ratings based on the International Classification of Functioning, Disability and Health (ICF). Paired-sample t tests, Wilcoxon signed-rank tests, and effect sizes (Cohen d) assessed changes in self-feeding scores. Qualitative data from open-ended survey responses and follow-up semi-structured interviews underwent thematic content analysis to complement quantitative findings. Results: Patients’ mean self-feeding impairment scores decreased significantly from 3.80 (SD 0.41) at baseline to 0.60 (SD 0.74) posttrial (n = 15; t₍₁₄₎ = 10.75, P < .001; Cohen d = 3.40). All patient participants demonstrated improvement in functional self-feeding ability. Mean SUS scores exceeded the benchmark for acceptable usability (≥68) across stakeholder groups: patients, 82.8 (SD 17.2); caregivers, 85.2 (SD 12.6); and providers, 85.0 (SD 10.7). Responses to Matching Person and Technology (MPT) items indicated strong alignment between user goals and device capabilities, perceived safety, and low complexity. Caregivers reported reduced feeding-related workload and stress, and providers endorsed ease of clinical integration. No adverse events or device malfunctions occurred. Conclusions: Obi3 demonstrated high usability, safety, and clinical utility in restoring self-feeding independence among individuals with severe UEMI. Findings across patients, caregivers, and providers support Obi3 as an effective piece of DME that enhances user autonomy and reduces caregiver burden. Future multisite and longitudinal research is warranted to confirm long-term outcomes, maintenance, and integration into rehabilitation practice. Clinical Trial: The study was approved by WCG IRB (protocol #20251472), and all participants provided informed consent.
Background: Acute ischemic stroke (AIS) management in rural regions is challenged by interhospital transfer delays, impacting outcomes. Objective: This study evaluates the efficacy of video-conferenci...
Background: Acute ischemic stroke (AIS) management in rural regions is challenged by interhospital transfer delays, impacting outcomes. Objective: This study evaluates the efficacy of video-conferencing teleconsultation on improving transfer efficiency and clinical outcomes in a hub-and-spoke model. Methods: This retrospective cohort study (January 2022–December 2024) included AIS patients identified as potential EVT candidates, transferred from a primary stroke center (PSC) to a comprehensive stroke center (CSC). Patients were categorized into teleconsultation and standard referral process (SRP) groups. The primary outcome was door-in-door-out (DIDO) time, with additional analyses on its components. Secondary outcomes included stroke-related decision-making and 90-day functional outcome using modified Rankin Scale (mRS). Safety outcomes included all-cause mortality within 90 days and symptomatic intracranial hemorrhage after intravenous thrombolysis and/or EVT. Results: A total of 83 patients were included, with 41 in the teleconsultation group and 42 in the SRP group (mean age: 73.3 years), and baseline characteristics were comparable. Teleconsultation significantly reduced DIDO time (95.2±22.9 vs. 132.3±41.5 minutes, p<0.001) by shortening CTA-to-ambulance notification time (44.6±17.4 vs. 79.5±37.6 minutes, p<0.001). Teleconsultation group had higher intravenous thrombolysis rates at the PSC (63.4% vs. 40.5%, p=0.04), higher EVT rates (34.2% vs. 14.3%, p=0.035) and shorter door-to-puncture time (83.0±35.5 vs. 118.5±25.9 minutes, p=0.04) at the CSC, with a significant shift toward better mRS at 90th day (OR: 4.55, p<0.001 vs. OR: 1.35, p=0.07). Safety outcomes were comparable between groups. Conclusions: Video-conferencing teleconsultation improves interhospital transfer efficiency, stroke-related decision-making, and functional outcomes. This study highlights its potential in optimizing rural stroke care.
Background: Machine learning, as a subfield of artificial intelligence, can have extensive nursing applications. Accurate understanding of the concept of machine learning, ethical considerations, acce...
Background: Machine learning, as a subfield of artificial intelligence, can have extensive nursing applications. Accurate understanding of the concept of machine learning, ethical considerations, acceptance and efficiency of this technology in nursing are among the important issues that are examined. Objective: To analyze the various dimensions of the concept of Machine Learning in nursing and to delineate its boundaries from other related concepts in the field of artificial intelligence. Methods: This study employs a conceptual analysis of machine learning in nursing, using the eight-step approach proposed by Walker and Avant. To fulfill key stages of this process, a search was conducted in several databases, including CINAHL, Embase, Scopus, PubMed, and Web of Science, using MeSH terms that focus on the keywords "machine learning" and "nursing" in articles published in English between 2018 and 2025. Results: The defining characteristics of machine learning include data-driven approaches, automation of the learning process, pattern extraction and relationship detection, algorithmic diversity, and adaptability. By leveraging these features, machine learning can optimize care processes, leading to an enhancement in the quality of nursing services. Machine learning models have the capability to identify disease trends, risk factors, and vital changes in patients' conditions, thereby facilitating the provision of preventive care. However, despite its significant potential to improve care quality, machine learning faces profound challenges in implementation and acceptance within clinical settings. Conclusions: Machine learning has the potential to enhance the quality of nursing care. However, challenges such as the limitations of models in generalizing to diverse populations, ethical concerns regarding privacy, and resistance to technology adoption necessitate integrated solutions.
Background: Cardiorespiratory fitness (VO2max) is a key predictor of cardiovascular and other health-related diseases and is often impaired in individuals with obesity due to functional and structural...
Background: Cardiorespiratory fitness (VO2max) is a key predictor of cardiovascular and other health-related diseases and is often impaired in individuals with obesity due to functional and structural limitations. Improving cardiorespiratory fitness enhances overall health and reduces mortality, making it an important indicator for preventing and treating obesity. Objective: The primary aim of this study is to develop an obesity-specific machine learning (ML) model that can accurately estimate VO2max, a key indicator of cardiovascular fitness, and make it accessible through a web-based application. Methods: A ML model will be trained to estimate VO2max in individuals with obesity using retrospective data combining assessments of VO2max tests and clinical parameters from adult patients with severe obesity body mass index (BMI ≥40.0 kg/m2, or 35.0-39.9 kg/m2 with at least one obesity-related comorbidity) from Vestfold Hospital Trust, Muritunet Rehabilitation Institution and Norwegian School of Sport Sciences. The ML-based VO2max estimation model will be presented as a web application, allowing easy access and interaction. The model’s estimations will be compared against direct VO2max measurements obtained from medical equipment across institutions as part of a prospective validation. Ethical approval has been obtained for the use of two databases in the initial model development; approval for the remaining data and prospective phase is pending. Results: Vestfold Hospital Trust, the Norwegian School of Sport Medicine, and Muritunet Rehabilitation have from 2013 to 2025 conducted > 2623 VO2max test and clinical parameters from 1,279 adults with severe obesity, both before, during and after lifestyle interventions. This comprehensive data set serves as the foundation for developing the ML model, which is presented through a user-friendly web application. A web application has been developed and will be tested with patients and healthcare personnel. The first scientific publication of the ML model is expected to be published in 2026. The results of the overall project are expected to be completed in 2028. Conclusions: This project aims to develop a machine learning model, which serves as a cost-effective tool for VO2max estimation in individuals with obesity, improving accessibility to this important health marker. This is the first known attempt in Norway to estimate VO2max in an obese population using machine learning, based on a unique clinical database. The project holds significant societal value with potential national and international relevance for healthcare and patient outcomes. Clinical Trial: ClinicalTrials.gov (Identifier: NCT07011108)
Background: The COVID-19 pandemic presented an unparalleled opportunity for telemedicine implementation, shortening adoption timelines and creating significant opportunities for observational research...
Background: The COVID-19 pandemic presented an unparalleled opportunity for telemedicine implementation, shortening adoption timelines and creating significant opportunities for observational research. Prior evidence is predominantly derived from small feasibility studies with limited comparative efficacy data and inadequate attention to implementation challenges and equity considerations. Objective: To synthesize methodologies, findings, and innovations from observational telemedicine studies conducted during the pandemic and identify critical research gaps. Methods: Narrative synthesis of 25 peer-reviewed observational studies (2020–2021) examining telemedicine across 11 clinical specialties, encompassing 119,016 patient contacts across multiple international settings. Studies employed prospective cohort designs, retrospective analyses, cross-sectional surveys, and mixed-methods approaches. Results: Telemedicine demonstrated clinical efficacy for chronic disease management with objective monitoring data, particularly in pediatric diabetes and cardiac device follow-up. However, substantial technology-acceptance discrepancies emerged—user satisfaction exceeded actual data capture reliability. Cross-sectional analyses unveiled systemic racial bias in satisfaction ratings and socioeconomic disparities in access. Innovations, including real-time locating systems, large-scale observational platforms, ambispective designs, and mixed-methods integration, have advanced methodological rigor. Persistent obstacles encompass selection bias, unmeasured confounding, outcome heterogeneity precluding meta-analysis, and temporal confounding. Conclusions: Observational pandemic-era telemedicine research substantiates selective clinical applications while exposing technology reliability limitations, persistent inequities, and methodological constraints on causal inference. Critical gaps include the absence of long-term outcome evaluation, economic analyses, diagnostic accuracy assessment, and equity-focused intervention research. Future advancement requires quasi-experimental designs, standardized outcome measures, explicit equity integration, and implementation science evidence for sustainable post-pandemic integration.
Background: Youth who identify as lesbian, gay, bisexual, transgender, queer, or as other sexual and gender minorities (LGBTQ+) encounter everyday expressions of prejudice and discrimination via infor...
Background: Youth who identify as lesbian, gay, bisexual, transgender, queer, or as other sexual and gender minorities (LGBTQ+) encounter everyday expressions of prejudice and discrimination via information and communication technologies. This includes sentiments and interactions that may be conceptualized as digital microaggressions. Objective: A preliminary measure of anti-LGBTQ+ digital microaggressions was compiled from emerging research and existing microaggressions scales, then tested on an internet-based sample of LGBTQ+ youth (aged 14–24) across three countries (n = 1,804). Methods: An exploratory factor analysis was conducted to understand emergent factor structures and vetted using a confirmatory factor analysis. Results: Results: Findings support further appraisal of the 45-item Anti-LGBTQ+ Digital Microaggressions Scale (ADMS), consisting of two three-factor subscales that measure (1) the experience of digital microaggressions directed at oneself and (2) witnessing digital microaggressions directed at others. The direct subscale (23 items) examines discrimination towards LGBTQ+ youth as individuals, including minimization and dismissal of their identity-based experiences. The indirect subscale (22 items) assesses discriminatory content directed at others or ambiently present in internet-based contexts, including negative portrayals of LGBTQ+ individuals and communities. Conclusions: Findings raise serious concerns about the prevalence of digital microaggressions in the lives of LGBTQ+ youth and offer a mechanism to support future investigations into this emerging area of research.
Background: Dehydration—specifically hyperosmolar dehydration (HD)—in adults is a common clinical condition associated with increased morbidity, mortality, and hospital admissions. Despite these a...
Background: Dehydration—specifically hyperosmolar dehydration (HD)—in adults is a common clinical condition associated with increased morbidity, mortality, and hospital admissions. Despite these alarming statistics, current treatment guidelines often fail to distinguish HD from other types of low body fluid status (e.g. hypovolaemia). This review aims to explore the existing evidence on treatment and to identify gaps in the evidence to guide future research Objective: The objective is to identify and summarize existing studies on treatment of dehydration in adults and to map the current evidence, highlight gaps in the literature and guide future research. Methods: The planned review will be conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. A systematic search will be performed across major peer-reviewed databases, with additional examination of reference lists and citations. Original studies of any design concerning treatment for HD in adults, specifically involving treatment with oral, subcutaneous, or intravenous fluids for dehydration, will be included. Data charting will contain study characteristics, participant demographics, details of HD diagnosis, treatment approaches, and reported outcomes. Results: The findings from the included studies will be reported through a narrative summary, supported by descriptive analysis of quantitative data if suitable. Conclusions: This scoping review will provide an overview of the current evidence on the treatment of HD in patients referred to hospital, identifying key insights and evidence gaps to inspire future research areas. Clinical Trial: The protocol will be registered at Open Science Framework? https://osf.io/ym65x
Background: Background:
Artificial intelligence (AI)-enabled health screening offers new opportunities to detect noncommunicable disease (NCD) risks in resource-limited settings. However, evidence on...
Background: Background:
Artificial intelligence (AI)-enabled health screening offers new opportunities to detect noncommunicable disease (NCD) risks in resource-limited settings. However, evidence on real-world feasibility, user acceptance, and behavioral outcomes of such tools in low- and middle-income countries (LMICs) remains limited. Objective: Objective:
This study evaluated the feasibility, acceptability, and short-term behavioral impact of DigiHealth, an AI-enabled health screening machine deployed among public school teachers in the Southern Philippines. Methods: Methods:
A cross-sectional implementation study was conducted among 384 teachers who underwent biometric and biochemical screening (BMI, blood pressure, fasting blood sugar, HbA1c, and lipid profile) using DigiHealth. Post-screening surveys measured perceived ease of use, reliability, privacy, and follow-up health behaviors. Quantitative data were analyzed using Welch’s t-test, χ², and logistic regression. The study was guided by the Technology Acceptance Model (TAM) and Health Belief Model (HBM). Results: Results:
Most participants were female (81.2%; median age 44 years). Males showed higher systolic blood pressure (130.7 vs 125.2 mmHg, P=.04) and triglycerides (171 vs 144 mg/dL). Overall, 85% rated DigiHealth as “good” or “excellent,” and 93% found it easy to use. Seventy percent consulted a health professional, and 67% reported lifestyle modification after screening. Age was inversely associated with clustering of ≥3 metabolic risk factors (P=.01). Conclusions: Conclusions:
AI-assisted workplace screening is feasible, acceptable, and behaviorally activating in low-resource contexts. DigiHealth demonstrates how pragmatic, fit-for-purpose AI innovations can complement national NCD programs and promote early detection in institutional settings within LMICs. Clinical Trial: NA
Background: Rheumatic heart disease (RHD) is a sequela of recurrent, untreated Group A Streptococcus (GAS) infections. RHD disproportionately affects children and young adults in the Global south. Int...
Background: Rheumatic heart disease (RHD) is a sequela of recurrent, untreated Group A Streptococcus (GAS) infections. RHD disproportionately affects children and young adults in the Global south. Intermittent mass screening of early RHD using affordable tools in these disease endemic regions is essential for effective prevention. Objective: This study examined multimodal physiologic data for assessing the prevalence of early RHD in a cohort of asymptomatic, at-risk schoolchildren in a rural Ethiopia. Methods: A total of 584 asymptomatic children, aged 10 to 20 years, were randomly selected for screening, and stratified into two groups (≤14 and >14 years). Electrocardiogram (ECG), Phonocardiogram (PCG), and echocardiography were performed, with diagnoses based on the 2012 World Heart Federation criteria. Results: After excluding 8 (1.4%) children who had non-rheumatic findings, 576 children comprised of 334 (58%) females and 242 (42%) males were analyzed. The mean age of the cohort was 16.1±2.5 years. Echocardiographic evaluation identified 19 RHD cases (10 borderline, 9 definite), with a higher prevalence among females (68%). The prevalence estimate derived from this analysis was 32.5 per 1000 population (95% CI: [18.1, 46.9]). Mitral valve was most affected (47%), followed by combined mitral and aortic involvement (42%). Mitral regurgitation (MR) was the most common (84%), then mitral stenosis (10%) and aortic regurgitation (6%). PCG showed MR (52.6%), MS (10.5%), and silent/unknown in the rest. Prolonged PR intervals was observed in 11% of RHD cases. Conclusions: The study confirms persistent high prevalence of asymptomatic RHD among schoolchildren in rural regions with female predominance. Clinical Trial: B3222022001075
Background: Clinical guidelines (CGs) standardize care through evidence-based recommendations, while Clinical Decision Support Systems (CDSS) can assist in applying these guidelines to individual pati...
Background: Clinical guidelines (CGs) standardize care through evidence-based recommendations, while Clinical Decision Support Systems (CDSS) can assist in applying these guidelines to individual patients. The scientific basis for the decisions offered by decision-support systems is often not explicitly stated or not clearly specified in the literature on CDSS. To our knowledge, no rigorous, systematic review has been conducted on the effectiveness of guideline-based decision support systems in which the technical integration and algorithmic embedding of clinical guidelines have been described or can be inferred from secondary literature. Objective: To systematically collect, describe, and synthesize evidence of randomized controlled studies of interventions using clinical decision support systems with a well-defined integration of evidence-based clinical guidelines on a direct medical outcome. Methods: This systematic review adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-SR) and its extension for Scoping Reviews (PRISMA-ScR) checklists. The eligibility criteria for this review are defined using the PICOS framework, including studies involving patients with any medical condition or disease. Study interventions need to include guideline-based clinical decision support systems (CDSS), encompassing all types of interventions used for treatment. Each intervention must provide a sufficiently accessible technical description detailing the types of data and algorithms used for decision-support procedures. The guidelines employed within these CDSS interventions must be derived from a clearly defined, evidence-based guideline development process. Studies must utilize a randomized controlled study design. Only studies on the effectiveness of the interventions on direct medical outcomes are included. Web of Science, including MEDLINE, and Scopus, are searched with search expressions aligned with the eligibility criteria. An update of the review is planned for autumn 2025. Results: On 11 August 2022, the initial search was conducted on PubMed, WoS, and Scopus. From a total of 6,282 records, 1,456 were removed prior to screening due to being duplicates, 2,506 records were excluded during the first screening step, and 2,350 were excluded during the second step. Fifty-nine papers were excluded based on their full texts, and 18 papers were finally included in the review following this initial search. This review is expected to demonstrate that CDSS based on CGs can improve clinical outcomes, although their effectiveness may vary depending on various factors. Potential limitations, such as high study heterogeneity, have already been identified. Conclusions: To our knowledge, this is the first rigorous systematic review on the effectiveness of guideline-based decision support systems in which the technical integration and algorithmic embedding of clinical guidelines have been described or can be inferred from secondary literature. With this review, we aim to address this gap by providing a detailed analysis of existing research and identifying best practices, challenges, and areas for future investigation. Clinical Trial: This systematic review has been registered with PROSPERO under the identifier CRD42024605679.
Background: Decentralized clinical trials (DCTs) are transforming traditional research by allowing participants to remotely take part through digital technologies such as telemedicine, mobile applicat...
Background: Decentralized clinical trials (DCTs) are transforming traditional research by allowing participants to remotely take part through digital technologies such as telemedicine, mobile applications, and digital platforms, overall enhancing participation, safety, accessibility, and overall trial outcomes. The COVID-19 pandemic further accelerated adoption, as there was a pressing need to minimize infection risks, delays, and disruptions. Despite growing innovation and initiatives like Trials@Home, there is limited understanding of how commercial technologies align with and support trial operations in the DCT lifecycle. Objective: This study aimed to map the landscape of commercial technologies used in DCTs and assess their availability, suitability, and alignment with clinical trial operations across the DCT lifecycle. Methods: A market scan of commercial technologies was conducted in 2024-2025 to update and add on previous work in 2020 using a structured approach. Seven peer groups were formed, each assigned to one of seven Basic Building Blocks (BBBs) representing key phases of the clinical trial lifecycle. These groups independently reviewed and categorized relevant solutions. The process included reassessment of previously identified solutions and identification of new technologies through keyword-based web searches, and categorization by the number of BBBs covered. Solutions also were categorized as Single- or Multiple-BBB based on their coverage, and a co-occurrence analysis identified strong and underrepresented pairings in BBB coverage. Results: The scan identified 312 technological solutions supporting DCTs. A similar distribution of solutions across BBBs was observed, with Set-up and Design and Patient Engagement being the most represented, while Operation and Coordination was the least covered. Most tools were specialized, with 226 single-BBB solutions, 48 covering two BBBs, and fewer than 10 addressing five or more. Only 2 solutions covered all seven BBBs. Co-occurrence analysis revealed strong overlaps between Patient Engagement, Intervention and Follow-up, and Operation and Coordination, while Set-up and Design showed minimal overlap with other BBBs. Conclusions: The rapid evolution of DCT technologies highlights the importance of structured assessments to guide technology selection. The balanced distribution of solutions per BBB suggests a broad coverage of trial operations. The stronger coverage in Set-up and Design and Patient Engagement compared with Operation and Coordination indicates areas for further development. The majority of tools were highly specialized with only a few covering multiple trial operations in an integrated manner. This reflects the maturity of specialized solutions and the potential for comprehensive systems spanning the full trial lifecycle. The strong pairs between Patient Engagement with Operation and Coordination and Intervention and Follow-up, together with the minimal overlap of Set-up and Design reveal a gap between planning and execution phases. This study provides a comprehensive catalogue of technologies, and offers practical insights to inform strategic technology selection for more efficient, inclusive, and connected clinical trial operations.
Social media represents an important tool for health promotion and disease prevention, particularly for populations at risk such as minorities. However, it is essential to define what research has be...
Social media represents an important tool for health promotion and disease prevention, particularly for populations at risk such as minorities. However, it is essential to define what research has been completed with the purpose of defining general trends in scientific findings, identifying knowledge gaps, and specifying research resource allocation priorities. For this study, we completed a literature search to identify, quantify and classify studies related to the use of social media in health promotion. We reviewed studies published in English between 2011 and 2023, and listed in ere PubMed, Cochrane Library, CINAHL, Nursing & Allied Health, JBI, PsycInfo, Sage Premier Journal, and Scopus. The search subject headings were ‘COVID-19’, social media’, minority’, and ‘Hispanics’. The analysis of data included frequency comparisons, classifying articles by intervention type, target population, methodology, and by publication year. The results show that most publications were based on US populations, involving interventions on infectious diseases and behavioral health. Most articles focused on the general population, with a small proportion studying minorities as defined by gender, gender identity, race, ethnicity, and age. The number of studies increased considerably after 2019, most likely reflecting the increased use of social media coinciding with the COVID-19 pandemic. The potential to promote health via social media is considerable, and there is a great need to expand research in this area focusing on minority populations.
Background: General Practitioners (GPs) play a pivotal role in a patient’s health care journey. However, demands on general practice, including an aging population and complex patient management, wo...
Background: General Practitioners (GPs) play a pivotal role in a patient’s health care journey. However, demands on general practice, including an aging population and complex patient management, workforce shortages and health system fragmentation, have been shown to adversely impact delivery of high-quality care and health outcomes. Integrated care models, particularly those that offer virtual care options, are one way to support improved access to quality care and efficiency of health care delivery across metropolitan and rural areas. The SUSTAIN model of care was created to provide an accessible option for integrated care. It consists of centralised paediatricians supporting general practitioners in their practice through virtual co-consultations, virtual case discussions and phone/email support. There is limited evaluation literature on integrated models of care being implemented in a primary care setting where the GP and family are face-to-face and the non-GP specialist is virtual. To address this gap, a comprehensive implementation evaluation of the SUSTAIN model of care was conducted. Objective: To examine what, why and how different factors impact the uptake of the SUSTAIN model of care from the perspectives of the SUSTAIN paediatricians and metropolitan and rural GPs in New South Wales (NSW), Australia. Methods: Qualitative study as part of the mixed-methods implementation evaluation of the SUSTAIN model of care. Data were collected via recorded online focus groups and interviews with general practitioners, general practice managers and paediatricians at 6- and 12-months post implementation of SUSTAIN. Data were analysed thematically using iterative thematic analysis informed by the Consolidated Framework of Implementation Research. Results: Eighteen focus groups and 13 interviews were conducted. GPs, practice managers and paediatricians found the SUSTAIN model acceptable, with the flexibility and practicality of the model highlighted. GPs valued the learning opportunities, collaboration and support they gained working alongside the paediatricians. Virtual delivery through telehealth was viewed as a positive means of receiving specialist support that would otherwise be inaccessible to many practices. Increased efficiency in workflow and working at the top of scope in paediatric care as well as opportunities for meaningful professional relationships and increased family trust in GP-delivered care were recognised as key benefits that enhanced uptake. The current landscape of Australian general practice, with fee-for-service billing, limited time and workflow pressures, were all recognised as barriers to engagement with the SUSTAIN model of care. GPs and paediatricians recognised the need for more appropriate remuneration to support co-consultation as vital to the sustainability and scalability of the SUSTAIN model. Conclusions: The SUSTAIN model of care expands on our understanding of the benefits of integrated GP-paediatrician models of care in general practice by demonstrating the utility of a paediatrician supporting a GP in their practice via telehealth across metropolitan and rural environments in NSW, Australia. Clinical Trial: Australian New Zealand Clinical Trials Registry ACTRN12623000543684
Background: Psychotic disorders are severe psychiatric conditions that affect approximately 24 million people worldwide. While research has traditionally focused on schizophrenia, other psychotic diso...
Background: Psychotic disorders are severe psychiatric conditions that affect approximately 24 million people worldwide. While research has traditionally focused on schizophrenia, other psychotic disorders are sometimes overshadowed by schizophrenia in the research field. Digital psychiatry offers innovative solutions to improve access to care, reduce stigma, and personalize interventions for patients who face barriers to traditional services. Objective: This scoping review aimed to explore the most recent studies targeting patients with non-schizophrenic psychosis. Methods: This review of literature examined articles published between the 1st January 2015 and 14th May 2025 on digital interventions targeting non-schizophrenic psychoses, identified through MEDLINE/PubMed. Results: Of 368 initial results, 19 studies met eligibility criteria. Interventions were grouped into four categories: internet-based therapies, smartphone applications, virtual reality (VR)-based treatments, and avatar therapy. The studies identified show that digital interventions for psychotic disorders, although mainly focused on schizophrenia and psychotic onset, also offer good prospects for other psychoses. In terms of acceptability, most studies show a good level of patient satisfaction, especially among young people, thanks to the flexibility and possibility of integrating treatment into daily life. However, significant barriers persist: psychotic symptoms themselves (suspiciousness, social withdrawal), technical difficulties, privacy concerns and poor training of clinicians. Finally, there is considerable methodological heterogeneity and limited representation of non-schizophrenic disorders, leading to difficulties in generalizing the results. Conclusions: Overall, digital technologies represent a promising opportunity to personalize interventions, improve access and support treatment continuity, but larger, more inclusive studies conducted in real-world clinical settings are needed.
Background: Large language models are increasingly used by employees at university hospitals for information retrieval or decision support. Self-hosted on-premise systems provide a secure environment,...
Background: Large language models are increasingly used by employees at university hospitals for information retrieval or decision support. Self-hosted on-premise systems provide a secure environment, conform with data privacy and security regulations for handling sensitive personal data. By automation of standard procedures through LLM application, time-consuming administrative tasks can be drastically reduced and analysis of large data sets facilitated. Objective: The objective of our study was to gather feedback from registered AI users on the usability and common use cases of the on-premise LLM infrastructure we established at the University Medicine Magdeburg, in order to optimize the models to the needs at our facility. Methods: We developed an online questionnaire to which registered AI users were given access and were informed via email. Results: Of 322 registered AI users, 98 participated in the user survey. Filtering incomplete responses, results from 91 participants remained for further analysis. Speed and quality received overall high approval rates. A majority of users utilized the platform at least once per week. Forty-four percent reported to save at least 30 minutes of work per week by using our AI platform. A diverse set of use cases could be observed, dependent on the users’ professions, e.g. healthcare and research professionals using the AI platform much more often for tasks of creation or analysis compared to administrative staff. Conclusions: Our data indicates that implementation of a self-hosted on-premise LLM has positive influence on the diverse group of professionals working at a university hospital, saving time and meeting their individual needs.
Background: An adequate amount of theoretical knowledge is a prerequisite for developing hands-on competency in contrast-enhanced ultrasound (CEUS), particularly for novices. Despite the increasing ad...
Background: An adequate amount of theoretical knowledge is a prerequisite for developing hands-on competency in contrast-enhanced ultrasound (CEUS), particularly for novices. Despite the increasing adoption CEUS for liver examinations, there is currently no standardized tool to assess the competency of trainees in terms of both theoretical knowledge and practical cognitive skills, which hinders the objective evaluation of training effectiveness.The purpose of this study is to develop and validate a CEUS competency assessment for the liver (CCAL) and address the critical gap in current training paradigms. Objective: To develop and validate a CEUS competency assessment for the liver (CCAL) and address the critical gap in current training paradigms. Methods: A four-stage process was conducted as follows:
① Item Generation: The initial items were derived from a literature review and clinical guidelines.
② Qualitative Refinement: The items underwent three rounds of Delphi expert consultation (n=21 experts) and cognitive testing (n=10 trainees) for content validity and clarity.
③ Internal Validation: Psychometric properties (reliability: Cronbach’s αand Guttman split-half; validity: exploratory factor analysis and item difficulty/discrimination) were analyzed using responses from trainees (n=100).
④ External Validation: Generalizability was assessed using data from trainees (n=579) across 25 multicenter sites. Results: The final CCAL was comprised of 66 items across three domains (demographics, self-evaluations, and objective questions), demonstrating high reliability (Cronbach’s α=0.916) and discriminant validity and revealing significant competency gaps in scanning procedures (65.6% pass rate) and image-guided intervention (38.3% pass rate), with objective questions showing balanced difficulty (63.2% easy and 3.5% difficult) and strong discrimination (61.4% good). Conclusions: The CCAL represents the first validated instrument designed for the objective assessment of operator competency in liver CEUS and thereby addresses an essential unmet need in current training paradigms. Furthermore, its implementation holds significant potential to standardize competency-based assessments and improve quality assurance protocols within hepatic imaging programs. Clinical Trial: Chinese Clinical Trial Registry; ChiCTR2000035750.
Background: Real-world psychiatric care is marked by wide heterogeneity in clinical presentations and outcomes, underscoring the need for systematic approaches to outcome measurement. The Clinical Glo...
Background: Real-world psychiatric care is marked by wide heterogeneity in clinical presentations and outcomes, underscoring the need for systematic approaches to outcome measurement. The Clinical Global Impression–Severity (CGI-S) scale is a brief, clinician-rated measure of overall illness severity widely used in psychiatric research but rarely documented in routine care. Large language models (LLMs) may enable automated extraction of CGI-S scores from narrative clinical notes providing scalable outcome measures for real-world clinical care and research. Objective: This study aimed to evaluate whether LLMs can estimate CGI-S scores from psychiatric clinical notes in patients with major depressive disorder (MDD) by first generating a clinician consensus gold standard dataset, and then comparing model-generated scores for validation. Methods: We used data from the Johns Hopkins electronic health record. Three psychiatrists independently rated 77 clinical notes using a validated depression-specific CGI rubric. Weighted Cohen’s kappa (κ) coefficients were calculated to assess interrater reliability and model–human agreement. Two prompting strategies, zero-shot and few-shot, were tested using GPT-4o, and agreement was compared against average human ratings. Exploratory analyses evaluated whether agreement varied by patient demographics, care setting, or note length. Results: Interrater reliability among psychiatrists was high (κ = 0.77–0.78). Agreement between model-generated and average human ratings was similarly strong (κ = 0.85) and was even higher for notes on which all three raters were in complete agreement (κ = 0.88). Weighted κ values remained consistently high across all subgroups (0.82–0.89), with no significant differences by age, sex, race, treatment location, or note length. Conclusions: LLMs can accurately estimate clinician-rated CGI-S scores from psychiatric clinical notes, achieving reliability comparable to expert raters. This approach may enable scalable outcome measurement and support the implementation of measurement-based care in real-world psychiatric practice.
Background: Emergency radiology necessitates highly accurate reporting under time constraints, yet increasing workloads raise the risk of errors. While large language models (LLMs) show potential for...
Background: Emergency radiology necessitates highly accurate reporting under time constraints, yet increasing workloads raise the risk of errors. While large language models (LLMs) show potential for proofreading in general radiology, their performance in emergency settings and non-English contexts remains unclear. Objective: To evaluate the performance of a domain-optimized LLM, DeepSeek-R1, for identifying errors in Chinese emergency radiology reports, with comparison against assessments by board-certified radiologists. Methods: We compiled 7435 emergency reports (radiography, CT, MRI) collected from November 2024 to April 2025. In Stage 1, five LLMs were evaluated using 200 reports. The best model, DeepSeek-R1, proceeded to Stages 2 and 3, where zero-shot and few-shot learning were tested on a separate set (n = 100). Model performance was compared against 12 radiologists. Stage 4 validated real-world utility on 800 verified reports. Results: DeepSeek-R1 achieved higher error detection rate using few-shot compared to zero-shot settings (84.4% vs. 60.9%, P = 0.003), outperforming residents (84.4% vs. 51.6% and 53.1%, respectively, both P < 0.05) and matching senior radiologists and attendings (84.4% vs. 68.8-93.8%, P = 0.26-1.00). Compared to residents, it detected 100% of critical omissions and 92% of other errors (all P < 0.05). Reading time was faster than humans (92 vs. 109 seconds). In real-world validation, DeepSeek-R1 identified 117 true errors (PPV 56.5%). Conclusions: DeepSeek-R1 holds promise for improving quality control in emergency radiology reports. Its efficiency and accuracy support its use as an assistive tool in real-world settings.
Background: Vision-enabled large language models (VE-LLMs) have the potential to provide flexible and explainable medical image interpretation. However, their real-world performance on clinical data s...
Background: Vision-enabled large language models (VE-LLMs) have the potential to provide flexible and explainable medical image interpretation. However, their real-world performance on clinical data such as 12-lead electrocardiograms (ECGs) has not been systematically assessed. Objective: This study aimed to evaluate the diagnostic accuracy and reliability of state-of-the-art VE-LLMs in interpreting real-world ECG images. Methods: We tested eight VE-LLMs (ChatGPT-5, ChatGPT-4, Gemini 2.5 Pro, Copilot, Grok-4, Perplexity, Claude Sonnet-4, and Claude Opus-4.1) using 70 de-identified ECG images. A standardized prompt requested nine determinations: rhythm, first-degree atrioventricular (AV) block, intraventricular conduction block and pattern, corrected QT (QTc) prolongation, premature atrial and ventricular contractions, ischemic ST-segment deviation, and axis deviation. An expert consensus served as the reference standard. Model outputs were evaluated using overall and per-class diagnostic metrics. Results: Overall accuracy across models varied significantly from 68.1% to 78.3% (429/630 to 493/630, Cochran’s Q, P<.001). ChatGPT-5 achieved the highest accuracy (78.3%) but had the slowest response time (median 276 seconds), whereas Perplexity and Copilot responded within a median of 2 and 3 seconds, respectively. Rhythm classification reached 72.9%–82.9% accuracy (51/70 to 58/70), but sensitivity for atrial fibrillation was ≤22% (≤2/9). Detection of first-degree AV block was poor (sensitivity 0%–33%; 0/9 to 3/9), and QTc prolongation was also poor (sensitivity 0%–45.5%; 0/22 to 10/22). Intraventricular block was identified with up to 70% accuracy (49/70), but correct subtype assignment was ≤44% (≤11/25). ST-segment deviation sensitivity was <25% for all models (highest 3/14). Agreement with expert interpretation was low, with Cohen’s kappa (κ) indicating poor-to-fair concordance (κ≤.37). Conclusions: VE-LLMs showed moderate overall accuracy but low sensitivity and limited agreement with expert ECG interpretation. Current performance is inconsistent and insufficient for clinical deployment. Future development should focus on domain-specific training and hybrid approaches combining LLM reasoning with established ECG algorithms before use in patient care.
Background: Health apps, which comprise both medical and wellness apps, hold potential to improve prevention, diagnosis, treatment, and management of disease. Yet, adoption by health care professional...
Background: Health apps, which comprise both medical and wellness apps, hold potential to improve prevention, diagnosis, treatment, and management of disease. Yet, adoption by health care professionals (HCP) including recommendation and prescription rates are low, even in countries where these apps are reimbursed. Professional guidelines from medical societies and trusted standardized health app quality assessment reports providing the information HCPs need to recommend or prescribe a specific app for an individual patient are crucial to enable this digital transformation of medicine. The CEN-ISO/TS 82304-2 (hereinafter “82304-2”) Technical Specification, an initiative of the European Commission, includes a research-based health app quality assessment framework comprising 81 quality requirements. Results of 82304-2 app assessments are summarized in a “health app quality label”. The 82304-2 label’s potential to increase willingness to recommend health apps was recently confirmed. However, to adequately inform HCPs for recommending and prescribing high-quality apps a more detailed “health app quality report” is required in addition to the 82304-2 label. Objective: To codesign the 82304-2 health app quality report by including the information detail that satisfies the information needs of individual HCPs in decision-making on a health app. Methods: A Participatory Design approach was applied to generate the report. In an 18-month process of participatory prototyping with 9 HCPs with digital health expertise the 82304-2 health app quality report was iteratively developed, designed, and validated. A convenience sample of 31 HCPs indicated the priority 82304-2 health app quality requirements that would inform their decision-making on recommending an app and as such need detailed quality information. Final feedback meetings with the 9 HCPs with digital health expertise and 8 medical societies were used to finalize the 82304-2 report design. Web-based questions in these meetings, as well as a comparative content analysis and the Health Education Materials Assessment Tool (HEMAT) were used to indicatively evaluate the 82304-2 report design. Results: In total 30/81 (37%) of the 82304-2 quality requirements were prioritized by >50% of the HCPs. The final 82304-2 report design provides detailed information for 27/30 (90%) of the prioritized 82304-2 quality requirements. The reporting detail for two 82304-2 quality requirements requires more research. The final feedback meetings, comparative content analysis and HEMAT provide indicative proof of the usefulness and usability of the 82304-2 report design. Conclusions: We succeeded in our aim to design the 82304-2 health app quality report and found promising potential for its distinctive usefulness for HCPs and medical societies. Further efforts are needed to test and fine-tune its multi-stakeholder and intercontinental usefulness and usability, to support medical societies in providing guidance and potentially training on recommending health apps, and to advance from the current design to a scalable fully-functional version of the 82304-2 report and associated open access database.
Background: Safe and reliable access to clean water remains a fundamental determinant of public health and sustainable development. In many rapidly urbanizing Nigerian communities, dependence on self-...
Background: Safe and reliable access to clean water remains a fundamental determinant of public health and sustainable development. In many rapidly urbanizing Nigerian communities, dependence on self-sourced groundwater and inadequate waste management systems continues to compromise water quality and expose residents to preventable diseases. This study investigated the status of water supply, quality, and associated health outcomes in Uselu Community, Benin City, to provide evidence-based insights for policy and intervention. Objective: The study aimed to (1) assess the primary sources of water available to residents, (2) evaluate household water-storage and treatment practices, and (3) examine the public-health implications of inadequate water access and sanitation behaviour in the community. Methods: A descriptive cross-sectional survey was conducted among 100 adult residents of Uselu Community selected through random sampling. Data were collected using structured questionnaires covering socio-demographics, water sources, treatment habits, sanitation practices, and self-reported waterborne diseases. Field observations complemented survey data, and results were presented as frequencies and percentages. Descriptive and inferential statistics were used to analyze trends, and findings were compared against national and international WASH benchmarks. Results: Findings revealed that 56% of respondents relied on boreholes as their main water source, while only 31% had access to public pipe-borne supply. Although 89% regularly washed their storage containers, fewer than half (43%) treated water by boiling or filtration, and only 17% practiced chlorination. About 32% reported disposing of waste near water sources, increasing contamination risks. The most common illnesses were typhoid fever (47%) and cholera (30%), with over half (55%) of respondents experiencing recurrent water shortages. These results indicate persistent infrastructural inadequacies, limited treatment adoption, and significant exposure to waterborne diseases. Conclusions: The study highlights critical water-supply and quality challenges in Uselu Community, driven by poor infrastructure, weak waste management, and inconsistent household treatment practices. Ensuring safe water access requires coordinated interventions combining infrastructural expansion, community hygiene education, and sustainable groundwater management. Strengthen municipal water systems, establish periodic water-quality monitoring, enforce sanitation regulations, and promote affordable household treatment technologies through continuous public-health education and community engagement. This study demonstrates that unsafe water and poor sanitation behaviours are central drivers of disease in Uselu Community. By translating evidence into actionable interventions, the research provides a model for improving public health, environmental sustainability, and water security in similar peri-urban settings.
Background: Digital platforms disseminating health information and providing support for the experience of non-memory-led dementias (NMLDs) are invaluable. However, the factors influencing engagement...
Background: Digital platforms disseminating health information and providing support for the experience of non-memory-led dementias (NMLDs) are invaluable. However, the factors influencing engagement with these resources in people affected by NMLDs are poorly understood. We conducted the world’s largest survey exploring the experience of digital access in non-memory-led dementias to learn directly from people with NMLD, their care partners and NMLD healthcare professionals (HCPs). Objective: To: a). Determine factors associated with web-based health and wellbeing resource use in people with NMLD and their care partners, and b). Investigate differences in web-based health and wellbeing resource use according to NMLD subtype. Methods: 450 individuals [individuals diagnosed with NMLD, e.g., frontotemporal lobar degeneration, posterior cortical atrophy (PCA), and primary progressive aphasia (PPA), their care partners, and NMLD healthcare professionals] responded to the survey. A subset of care partners provided two responses (carer-related and proxy), generating four survey groups with N(responses)=538. The survey included demographics and basic clinical information, the outcome measure of technology use (Venkatesh, 2012), and factors including: constructs from the Senior Technology Acceptance Model (Chen & Lou, 2020), depression (PHQ-4), web-related privacy/security concerns (Hong & Thong, 2013), and digital health literacy (Nelson, 2022). Separate multiple linear regressions were run for each survey group to elucidate which variables predicted higher use of web-based health and resources. The use of web-based resources for health and wellbeing was also explored across three non-memory-led dementia subtypes: FTD, PPA, and PCA. Results: Attitudinal belief was consistently the strongest predictor of health and wellbeing web-based resource use in NMLD populations. Control belief was significantly associated with higher web-based health and wellbeing resource use in the NMLD and proxy group; a trend was observed in the carer group. 62.8-70% of the variance in web-based health and wellbeing resource use was accounted for in the three models. Lower digital health and wellbeing use was associated with FTD diagnosis and caregiver groups relative to PPA and PCA. Conclusions: Collectively, these findings indicate several factors are critical to consider when designing digital offers for people with NMLD and their caregivers, in particular targeting practical and emotional perceptions of web-based resource use for health and wellbeing. This should be undertaken in combination with design considerations which address condition-specific cognitive profiles encountered by those living with the diagnosis, and those who care for them.
Background: Cervical cancer (CC) is one of the leading causes of female mortality after breast cancer. CC accounts for more than 7.5% of female cancer deaths worldwide. Human papillomavirus (HPV) is t...
Background: Cervical cancer (CC) is one of the leading causes of female mortality after breast cancer. CC accounts for more than 7.5% of female cancer deaths worldwide. Human papillomavirus (HPV) is the most common sexually transmitted infection (STI) in women and the leading cause of cervical cancer in women for almost 99% of all CC cases. HPV vaccination could prevent up to 70% of HPV-related cervical cancer and 90% of genital warts. HPV vaccination is the bedrock of primary prevention and helps reduce the incidence and death rates of HPV-associated cervical cancer. This analysis examines each theme based on responses to questions about HPV and HPV vaccine knowledge and health beliefs among Kuwaiti parents. Objective: The study aims to understand the knowledge and health beliefs of 20 Kuwaiti parents regarding HPV vaccination, with the goal of developing a health promotion policy and introducing a national immunization program in Kuwait. Methods: The remaining 37 participants were then evaluated using purposive sampling to select 20 participants for the one-on-one semi-structured interviews. The researcher wanted to include both participants (male and female parents) with primary education (diploma and below) and those with secondary and above education (Bachelor's and above). the researcher had four categories with sufficient numbers (at least five in each category), which gave us at least 20. Semi-structured interviews were held with individual parents based on the Health Belief Model (HBM). The data were thematically analyzed using an inductive approach, generating themes through the theoretical framework of the HBM, and theme extraction analyses were managed on a semantic level. Results: There are seven main themes containing 20 sub-themes. Seven themes are: (1) Knowledge and awareness about HPV infection and vaccine. (2) Perceived susceptibility, which is explained by the HPV infection effect based on gender. (3) Perceived barriers to HPV vaccination with several sub-themes: stigma, social customs, negative vaccination uptake, and religious influences. (4) Perceived benefits: Parents emphasise the benefits of getting an HPV vaccine, such as protection against the virus and related cancer diseases. (5) Perceived severity, a fear of getting a severe disease. (6) Self-efficacy, with sub-themes of parent experiences decisions regarding HPV vaccination (7) Cues-to-action, the role of the Ministry of Health, and (HCPs). Conclusions: The HBM framework is beneficial for Kuwait's HPV vaccination campaign. The correlation between sexual intercourse and the HPV vaccine frequently adds complexity to the decision-making process about immunisation. This study demonstrates that positive cues to action from HCPs and educational vaccination benefits can overcome perceived barriers among parents related to stigma and religion. It is essential to conduct such research to guide the development of interventions aimed at promoting the adoption of the HPV vaccine uptake.
Background: With the growing ageing population, technology that supports independent living is increasingly important. Web search systems are well-established, whereas Generative AI (e.g., ChatGPT) re...
Background: With the growing ageing population, technology that supports independent living is increasingly important. Web search systems are well-established, whereas Generative AI (e.g., ChatGPT) represents a newer, adaptive tool that could offer personalised information access. However, little is known about how older adults, particularly those with Mild Cognitive Impairment (MCI) or mild dementia, perceive and engage with these systems. Objective: This study explored the use and perspectives of web search and Gen-AI in older adults with and without MCI. Methods: A UK-wide mixed-methods study was conducted with older adults, including those with MCI or mild dementia. An online survey captured technology use, Likert-scale ratings of web search and Generative AI, and reasons for non-use. Follow-up focus groups provided in-depth qualitative perspectives. Quantitative data were analysed using descriptive and comparative statistics, while qualitative data were thematically analysed. Results: Survey findings showed higher use of web search (98%) compared to Generative AI (14%) within these groups. Web search was rated positively across participants, although challenges were raised regarding the phrasing of queries and commercialisation. Gen-AI use was less common, but more than half of non-users expressed willingness to adopt it in future. Combined with focus group responses, themes exploring keyword searching, mistrust, lack of knowledge, and willingness to learn were established. Participants also suggested potential applications of Generative AI, such as supporting independent living through monitoring and simplifying complex searches. Conclusions: Web search remains the primary method, and participants highlighted both advantages and frustrations with current systems. Generative AI was underused but seen as promising, with its adoption mainly limited by mistrust and knowledge gaps. Our findings indicate that structured training, early introduction, and user-centred design could encourage adoption, enhance accessibility, and support independent living among older adults with and without MCI.
Background: Women with breast cancer face many barriers to return to work (RTW) after their treatment. The FAcilitating and SusTain the Return to work After breast Cancer (FASTRACS) intervention aims...
Background: Women with breast cancer face many barriers to return to work (RTW) after their treatment. The FAcilitating and SusTain the Return to work After breast Cancer (FASTRACS) intervention aims to facilitate and sustain functional RTW. The main objective of the RECOVA-FASTRACS study is to evaluate the processes of the using a realist approach that analyses what works, how, for whom and under what circumstances.
Methods: The RECOVA-FASTRACS study uses a mixed-methods design to assess the implementation, context, and impact mechanisms of the FASTRACS intervention. The qualitative analysis will include two main components: a trajectory analysis and a focus group assessment. The trajectory analysis will examine the experience of women who participated in the intervention and key individuals involved in their RTW process. We will use semi-structured interviews according to the multiple-case study method. Additionally, to explore organisational and professional practices, focus groups will be conducted with professionals who deliver the intervention. To analyse the trajectories, embedded and iterative integration will combine the qualitative findings, with relevant quantitative data from the FASTRACS randomised controlled trial for five domains (i.e. personal situation, professional situation, return to work, care pathway, intervention tool use and perceived usefulness).
Discussion: Our mixed-methods realist evaluation will provide a detailed analysis of the intervention processes, helping to identify impact mechanisms within specific contexts. This approach is meant to ensure a more informed and realist deployment of the intervention by professionals following the study.
Background: Young adults face rising wellness challenges including prediabetes risk, requiring sustained engagement with preventive health interventions. Digital wellness applications offer promise fo...
Background: Young adults face rising wellness challenges including prediabetes risk, requiring sustained engagement with preventive health interventions. Digital wellness applications offer promise for promoting healthy lifestyle behaviours, yet high dropout rates and inadequate personalization limit their effectiveness. This paper outlines the technical implementation and usability evaluation of MiCARE, a theory-driven progressive web application (PWA) designed to support sustained wellness engagement among young adults through user-centered design. Objective: Our aim is to systematically implement theory-driven design specifications into a functional web application, the MiCARE platform, and to conduct a rigorous usability evaluation with young adults aged 18-34 in Victoria, Australia, in both rural and urban areas using the Task-Technology Fit (TTF) and Unified Theory of Acceptance and Use of Technology (UTAUT) frameworks to assess usability, usefulness, and satisfaction. Methods: This is an embedded mixed-methods study across two phases: Phase 3 and Phase 4. Phase 3 involves the technical implementation of six theory-driven features (empathetic chatbot, learning hub, dynamic goal setting, gamification, personalized reminders, progress dashboard) using HTML5/CSS3/JavaScript, Google Dialogflow ES, and Firebase services, following the Agile methodology over six months with biweekly self-managed sprints and clinical verification. Phase 4 is a three-month usability evaluation with 20 young adults aged 18-34 in Victoria, Australia. Participants will complete screening, initial, mid-point, and final surveys assessing usability, usefulness, and satisfaction, while real-time usage analytics captures engagement patterns. Data analysis will employ the TTF and UTAUT frameworks, with quantitative data analysed using descriptive statistics (R Studio), qualitative feedback analysed through thematic analysis (NVivo), and engagement patterns analysed via machine learning models. The study has received ethics approval from La Trobe University Human Research Ethics Committee (HEC24507). Results: The study is taking place between 2025 and 2026 and is currently in preparation for Phase 3 implementation. Evaluation results will be disseminated in academic forums, peer-reviewed publications in early-2027. The findings will enable us to evaluate the feasibility, acceptability, and usability of a theory-driven PWA for young adult wellness engagement. Conclusions: This study will be the first to explore the technical implementation and usability of a multi-theoretical, user-centered PWA for wellness engagement in preventive health, bridging the gap between conceptual frameworks and deployed interventions.
Japan has universal health coverage and designated childhood cancer centers, but the national information environment still functions as a “black box”: incidence can be tracked, whereas treatment...
Japan has universal health coverage and designated childhood cancer centers, but the national information environment still functions as a “black box”: incidence can be tracked, whereas treatment exposure and long term follow up are not reliably linked across hospitals, registries, and survivorship services. In this viewpoint, we synthesize international guidance and Japanese policy to propose a formative design for digital health governance that connects clinical systems, registries, and survivorship. We specify a minimal pediatric dataset and an interoperability architecture based on the Health Level Seven Fast Healthcare Interoperability Resources (HL7 FHIR) standard. A national Pediatric Data Steward would govern standards and APIs, terminology and coding (eg, International Classification of Diseases for Oncology and International Classification of Childhood Cancer, with mappings to SNOMED CT and LOINC), privacy and consent aligned with the Act on the Protection of Personal Information and the Next Generation Medical Infrastructure Act, data use agreements, data quality, and audit. Validated data from electronic health records, laboratories, radiology, pathology, and cooperative group databases would flow through a FHIR gateway to the National and Hospital based Cancer Registries and to a patient facing digital survivorship passport, with bidirectional updates and linkage to resident registries and vital statistics. We also propose pediatric indicators and a staged roadmap to implementation. Transforming pediatric oncology information in Japan into a learning system is primarily a governance task; a Pediatric Data Steward, a harmonized pediatric data dictionary, and a portable, consent aware survivorship passport could improve timeliness, completeness, follow up, equity, and transparency.
This paper explores the role of open-source Large Language Models (LLMs) in promoting AI health equity from the perspective of the health service triangle model. First, it analyzes the development his...
This paper explores the role of open-source Large Language Models (LLMs) in promoting AI health equity from the perspective of the health service triangle model. First, it analyzes the development history of AI health and the current status of global application inequalities, pointing out that closed-source models exacerbate gaps in health services due to technological monopolies, high costs, and data privacy issues. Second, by comparing open-source models with closed-source models in terms of parameter scale, deployment methods, and application scenarios, it reveals the advantages of open-source models in local deployment, secondary development, and cost control. Finally, based on the health service triangle model, the paper demonstrates how open-source LLMs drive the democratization of medical resources—particularly benefiting low-resource regions—by expanding service types, improving accessibility, enhancing quality, and reducing costs. The study concludes that while open-source technology must address challenges such as hallucination risks and ethical responsibilities, it ultimately enables global health equity through technological sharing.
Background: The detection of pulmonary nodules (PNs) has increased with the use of low-dose computed tomography (LDCT) screening. Effective management requires the ability to track and compare images...
Background: The detection of pulmonary nodules (PNs) has increased with the use of low-dose computed tomography (LDCT) screening. Effective management requires the ability to track and compare images over time, yet challenges remain in accessing prior imaging data across institutions. Cloud-based medical imaging (CMI) solutions offer a potential means of improving access and facilitating cross-institutional data exchange. However, the adoption and utility of CMI in PN care, especially in China, remain underexplored. Objective: This study aims to evaluate the possession, use, and impact of CMI on healthcare utilization, patient knowledge, and financial burden, as well as to identify usability and interoperability barriers through qualitative investigation. Methods: A mixed-methods cross-sectional study was conducted from October 2022 to May 2024. The study involved 701 patients with PNs who completed structured surveys, and 20 participants (10 patients and 10 physicians) were interviewed. Data were analyzed to examine associations between CMI use and healthcare utilization, costs, and patient perceptions, and qualitative interviews were analyzed for usability themes. Results: The study found that 87.2% of patients had obtained CMI, with 57.6% actively using it. CMI users accessed more internet hospitals, consulted more physicians, and reported lower healthcare costs compared to non-users. Users also demonstrated higher disease knowledge. Qualitative data identified key barriers including poor system usability, limited retention time for images, and weak interoperability. CMI was perceived as beneficial for patient convenience and clinical efficiency, though concerns over image quality and system fragmentation were prevalent. Conclusions: While CMI is widely available, its usage remains suboptimal. Increased use is associated with enhanced healthcare engagement and reduced costs, suggesting that improving system usability and ensuring consistent access to imaging could enhance the benefits of CMI. Future improvements should focus on ensuring long-term access, better retention protocols, and overcoming interoperability issues. Clinical Trial: All participants provided written informed consent under institutional ethics approval [approval number: 2025-KY-122-01].
Background: There are still insufficient studies exploring its relationship with the Insulin Resistance (IR) surrogates from the perspective of sleep structure. Objective: The aim of this study is to...
Background: There are still insufficient studies exploring its relationship with the Insulin Resistance (IR) surrogates from the perspective of sleep structure. Objective: The aim of this study is to apply smart bracelets to monitor the sleep structure parameters of middle-aged and elderly people during natural sleep and investigate their association with the IR surrogates. Methods: A total of 723 individuals aged between 40 and 65 participated in the questionnaire surveys, sleep assessments, and regular hospital physical examinations. Sleep assessment involves the respondents wearing a smart bracelet (Honor Band5i) on their non-dominant hand and continuously measuring the sleep of natural people in the real world for three days. Generalised estimating equation regression analysis and robust poisson regression were used to analyse the association between sleep structural parameters and the three IR surrogates, and restricted cubic spline (RCS)regression analysis was used to explore the threshold and dose-response relationship. Results: The proportion of REM sleep among the 723 respondents was 17.31% ± 4.76, the proportion of slow-wave sleep was 25.33% (21.83, 28.00), and the proportion of light sleep was 57.67% (53.33,62.00). Multifactorial regression analyses showed that an increase in the duration and proportion of REM sleep was associated with a reduced risk of IR (ORREM%-TyGWHtR =0.993, 95%CI: 0.987-0.999, p=0.029, ORREMmin-TyG =0.997, 95%CI: 0.994-0.999, p=0.038, ORREMmin-METSIR =0.994, 95%CI: 0.990-0.998, p=0.006); No significant associations were found between the length and proportion of slow wave sleep, the length and proportion of light sleep, and the three IR indices (p> 0.05). After the proportion and duration of REM sleep were later dichotomised by the nodes obtained from the RCS analysis, and this association was only observed in the male group in the gender stratification (ORREM%-TyG =0.853, 95%CI: 0.741-0.982, p=0.026, ORREMmin-TyG =0.855,95%CI: 0.742-0.985, p=0.030). Furthermore, even after excluding the REM (%) ≥30% (n=6) or patients with diabetes (n=50), the trend between REM sleep and IR remained consistent. Conclusions: This study found that the overall proportion and duration of REM sleep in the middle-aged and elderly population were relatively low. Additionally, the study also discovered that the increase in the proportion of REM sleep is associated with a reduced risk of IR surrogates. This research indicates that monitoring and optimizing the duration and proportion of REM sleep may be a new target for preventing metabolic diseases. Moreover, the widespread use of commercial watches in the home environment will facilitate the assessment of future sleep patterns. This will also provide a basis for people to manage their daily sleep health autonomously.
Background: The growing need for remote patient monitoring, accelerated by the global pandemic and an aging population, necessitates the development of advanced non-contact technologies for measuring...
Background: The growing need for remote patient monitoring, accelerated by the global pandemic and an aging population, necessitates the development of advanced non-contact technologies for measuring vital signs. Conventional contact-based sensors pose risks of infection and cause discomfort during long-term use, while existing non-contact methods suffer from inaccuracies due to environmental factors and user motion. Heart rate (HR) and body temperature (Temp) are fundamental indicators of health, yet their reliable and convenient remote measurement remains a significant challenge. Objective: This study aims to develop and validate an integrated, non-contact system for accurately measuring HR and Temp. The proposed system leverages 60GHz RADAR and a high-performance infrared (IR) sensor, enhanced with advanced signal processing and an AI-based computer vision algorithm, to overcome the limitations of conventional methods. Methods: A novel system was designed, combining a 60GHz RADAR sensor for HR measurement and an IR sensor for Temp measurement. To enhance HR accuracy, a Window Filter and a Peak Uniformity algorithm were applied to the raw RADAR signal to mitigate noise and motion artifacts. For Temp measurement, an IR sensor with a narrow 5° Field of View (FOV) was integrated with a YOLO Pose-based tracking system, which uses a camera and servo motors to automatically orient the sensor towards the user's face. The system's performance was validated in a controlled laboratory setting with 30 healthy adult participants (mean age 40.8). The results were benchmarked against gold-standard devices: a MAX30102 PPG sensor for HR and a Braun ThermoScan 7 for Temp. Results: The advanced signal processing for the RADAR sensor significantly improved HR measurement accuracy, reducing the Mean Absolute Error (MAE) from 13.73 BPM to 5.28 BPM (p=0.002) and decreasing error variability. For temperature, the AI-guided IR sensor demonstrated superior performance, lowering the MAE from 4.10°C to 1.64°C (p < 0.001) compared to a fixed-angle sensor. Notably, the maximum error of the AI-guided system (2.2°C) was lower than the minimum error of the conventional method (2.6°C), indicating enhanced stability and reliability. Conclusions: The findings demonstrate that integrating 60GHz RADAR with advanced signal processing and an AI-driven tracking system provides a robust and accurate solution for non-contact vital sign monitoring. Clinical Trial: KWNUIRB-2025-07-007-001
Background: Austria has only recently established a legal framework for assisted dying. Individuals seeking assistance in suicide must navigate a multi-stage process that has been criticised for its c...
Background: Austria has only recently established a legal framework for assisted dying. Individuals seeking assistance in suicide must navigate a multi-stage process that has been criticised for its complexity, both for the individuals seeking assistance as well as the healthcare and legal professionals involved in the procedure. Objective: In order to address the critical gap in empirical research that sheds light onto the law’s implementation, we have designed a multi-perspective evaluation that examines the various perspectives of individuals seeking assisted suicide, their family members and other relatives, as well as of all professions specified in the legal framework – notably physicians, notaries and other relevant legal professionals, pharmacists, and psychologists. Methods: Our study employs an interdisciplinary approach that integrates theories, concepts, and methodologies from legal science, ethics and social science. Within the latter, we aim to provide a comprehensive account of stakeholder experiences through a series of semi-structured interviews and two online questionnaire surveys. Results: The initial research proposal received approval from the University of Vienna Ethics Committee in November 2023. The legal and ethical analyses are ongoing, with several key legal and ethical barriers already identified. Recruitment for interview participants began in January 2024. As of October 2025, the majority of interviews across all stakeholder groups have been conducted and transcribed. Given the novelty of the legislation and the limited practical experience to date, further interviews are scheduled until the end of 2025. Data collection for both questionnaire surveys took place from June until September 2024 with data analysis completed in May 2025. Conclusions: Our multi-perspective evaluation aims to assess the framework on assisted suicide in Austria. By evaluating the perspectives of relevant key stakeholders, we aim to provide a nuanced understanding of the law’s societal, legal, and ethical implications.
Background: While growing evidence suggests that music training supports child development, few long-term randomized controlled trials (RCTs) have rigorously tested these claims. Moreover, it remains...
Background: While growing evidence suggests that music training supports child development, few long-term randomized controlled trials (RCTs) have rigorously tested these claims. Moreover, it remains unclear whether the benefits are confined to music-specific domains or extend to higher-order cognitive functions such as inhibitory control (IC), a core executive function associated with long-term outcomes in academic achievement, career success, socio-emotional health, and physical well-being. Objective: This paper presents the protocol for the Extracurricular Activity and Child Early Learning and Development (EXCEL) trial, an RCT designed to assess the feasibility of a long-term music training program focusing on the brain and behavioral correlates of IC. Methods: A total of 126 children, aged 6 to 8 years and residing in neighborhoods with limited resources in Los Angeles, were individually randomized to either a music (intervention) or theatre (active control) after-school program. Both programs were delivered over 24 months by established community arts organizations. Eligibility criteria included: average intellectual functioning, no major medical or psychiatric conditions, and MRI eligibility. Children with prior formal music training exceeding six months or severe hearing impairment were excluded. Before the intervention began, all participants completed baseline behavioral and neuroimaging assessments. The primary trial aim was to assess the effects of extended music training, relative to theatre training, on changes in measures of IC (i.e., Go/No-Go task and delayed gratification) and related neural functional activation. A secondary interim aim of the trial was to evaluate the feasibility of conducting a long-term RCT of music education in a first cohort, measured by participant retention, adherence to the program, willingness to continue at the 12-month mark, and fidelity. Results: Recruitment, screening, baseline testing, randomization, and program enrollment began in August 2022, and after-school programming began in October 2022. The randomized interventions and all data for the first cohort (N = 42) have been collected. Intervention and active control programs for a second cohort are ongoing and will end in Fall 2026. Conclusions: This paper reports the EXCEL trial protocol and provides estimates of the feasibility of implementing a long-term randomized controlled trial of music training in real-world, community-based settings with children. While similar neuroimaging RCTs are currently underway in Europe, the EXCEL trial is among the first in the United States to integrate longitudinal neuroimaging with arts intervention. Findings will inform the viability of scaling such programs and contribute to our understanding of how sustained music engagement may influence the development of inhibitory control circuitry in childhood. Clinical Trial: The EXCEL Trial Registration: ClinicalTrials.gov NCT05502939
Background: Software-based interventions have emerged as effective tools for managing chronic diseases. Lifestyle intervention (LI) apps can promote weight loss, but many depend on human coaches or he...
Background: Software-based interventions have emerged as effective tools for managing chronic diseases. Lifestyle intervention (LI) apps can promote weight loss, but many depend on human coaches or healthcare providers, thus introducing higher costs and variability in feedback. Most existing apps rely on calorie-counting approaches and lack structured, individualized guidance, leaving users to determine how to translate general recommendations into daily nutrition and exercise practices. Moreover, many do not provide rapid, adaptive feedback to adjust meal or activity plans in real time. Objective: To compare the RightBMI App, an autonomous, protein-focused digital lifestyle intervention, with provider-delivered lifestyle intervention (LI) for weight loss and body composition changes in bariatric surgery candidates. Methods: A prospective randomized trial (April 2024 - April 2025, Holyoke Medical Center) enrolled 160 patients (App: n=80; no-App: n=80). RightBMI provided personalized nutrition and exercise plans. Outcomes (% total body weight loss [%TBWL], % fat mass loss [%FML], % visceral fat loss [%VFL], % muscle mass loss [%MML]) were assessed over 24 weeks using Generalized Estimating Equations (GEE) with multiple imputation, adjusting for age, BMI, and sex (no-App as reference). Results: GEE models showed significant time effects for %TBWL (week 8: coefficient 2.91, p<0.001; week 24: 18.12, p<0.001) and %FML (week 8: 5.30, p<0.001; week 24: 33.65, p<0.001) in the no-App group. The App group had greater %TBWL at weeks 12 (2.64%, p<0.001) and 16 (2.47%, p=0.027), and %FML at weeks 12 (2.94%, p=0.028) and 16 (4.20%, p=0.003). At week 24, outcomes were comparable: App group (%TBWL: 20.01%, %FML: 36.81%, %VFL: 31.99%, %MML: -0.09%) vs. no-App (%TBWL: 19.97%, %FML: 35.74%, %VFL: 32.97%, %MML: 0.70%; all p>0.89). Both groups maintained stable %MML with %TBWL ~20% and %FML >32%. User satisfaction was high (8.76/10). Conclusions: The RightBMI App outperformed provider-led LI at mid-study, achieving comparable 24-week weight loss (~20%) and muscle preservation. With 90% bariatric surgery clearance (vs. 71.25% no-App) and low dropout (3.75% App, 1.25% no-App), RightBMI is a scalable, effective tool for obesity management.
Background: Acute respiratory distress syndrome (ARDS) is caused by an acute pulmonary inflammation, resulting in significant hypoxia. Current treatment is symptomatic, using mechanical ventilation, a...
Background: Acute respiratory distress syndrome (ARDS) is caused by an acute pulmonary inflammation, resulting in significant hypoxia. Current treatment is symptomatic, using mechanical ventilation, and in extreme cases the initiation of extracorporeal membrane oxygenation (ECMO). Objective: Uncertainty exists regarding the optimal timing of initiation of veno-venous ECMO therapy. In the “Early versus Late Initiation of vvECMO” (ELIEO) trial, we aimed to investigate the impact of early ECMO initiation on outcome in ARDS patients. Methods: ELIEO is a prospective randomized multicenter trial assessing whether early initiation of vvECMO could result in improved outcomes in ARDS. Five hundred and eight patients suffering from severe ARDS will be divided into two groups: patients in Group A will begin ECMO therapy within 24 h after admission to the ICU of an ECMO center, while patients in Group B will receive standard treatment according to ARDS Network guidelines and ECMO therapy as a rescue therapy only. During follow-up visits (days 28 and 90), the functional status of patients will be evaluated. The primary endpoint is survival during the 90-d follow-up period. Secondary endpoints include SOFA scores, bleeding complications and ICU-related complications. Results: The results of the ELIEO trial will highlight the importance of the time point at which vvECMO therapy is initiated in patients with severe ARDS. Conclusions: Given the enormous challenge patients with ARDS pose to the health care system, the findings of this trial might have a significant impact on the structuring of intensive care units and on ARDS therapies. Clinical Trial: The ELIEO trial was first approved by the local ethics committee (University Tübingen, Germany) on December 18, 2020. The trial is registered at clinicaltrials.gov (NCT04208126).
Background: Introduction: Advances in cancer treatment have improved survival rates, however, patients continue to experience significant treatment-related side effects, leading to reduced quality-of-...
Background: Introduction: Advances in cancer treatment have improved survival rates, however, patients continue to experience significant treatment-related side effects, leading to reduced quality-of-life. Prehabilitation is an intervention that occurs before treatment and can improve patients’ functional capacity, recovery, and wellbeing through exercise, dietary, and psychological support. Typical hospital-based prehabilitation is not accessible to all patients due to geographical, socioeconomic, and time-related barriers. Technology-based approaches, including eHealth and mHealth interventions, may overcome these barriers by enabling remote, patient-centred delivery. However, the current evidence base is heterogeneous and lacks synthesis regarding feasibility, acceptability, outcomes, and equity. Objective: Objective: This protocol for a scoping review aims to outline how we will systematically map and synthesise the evidence on technology-based prehabilitation interventions for people with cancer, to identify intervention designs, assess feasibility and accessibility, and highlight knowledge gaps to guide future research and practice. Methods: Inclusion criteria: In the proposed scoping review, eligible studies will include adults (≥18 years) with a cancer diagnosis who are scheduled for elective treatment (surgery, radiotherapy, chemotherapy, immunotherapy, or hormone therapy). Interventions must involve eHealth or mHealth approaches supporting unimodal or multimodal prehabilitation activities such as exercise, nutrition, psychological support, or lifestyle modification. Outcomes of interest include functional fitness, quality of life, psychological wellbeing, treatment preparedness, recovery, adherence, and feasibility.
Method: The review will follow JBI methodology and PRISMA-ScR guidelines. A three-step search strategy will be applied across multiple databases and grey literature sources. Data will be charted and presented in tables, figures, and narrative synthesis. Critical appraisal using JBI tools will contextualise methodological quality but not exclude studies. Results: N/A Conclusions: N/A Clinical Trial: https://doi.org/10.17605/OSF.IO/VNWA7
Background: Labor pain is among the most intense forms of pain, and neuraxial anesthesia including epidural, spinal, and combined spinal-epidural techniques is considered the gold standard for its man...
Background: Labor pain is among the most intense forms of pain, and neuraxial anesthesia including epidural, spinal, and combined spinal-epidural techniques is considered the gold standard for its management. Despite its effectiveness, persistent misconceptions, cultural barriers, and disparities in awareness contribute to underutilization among certain populations. Educational interventions have been developed to address these gaps, yet a comprehensive synthesis of such efforts within the United States is lacking. Objective: This scoping review aims to map the extent, range, and nature of educational interventions designed to improve knowledge, awareness, and acceptance of neuraxial anesthesia during labor among pregnant women. Methods: Following the PRISMA-ScR framework, peer-reviewed studies published in English were identified through PubMed, Embase, and Scopus up to August 2025. Eligible studies included pregnant women eligible for neuraxial anesthesia, with interventions delivered during prenatal or perinatal care. Extracted data included study design, intervention type, delivery method, timing, and outcomes related to knowledge acquisition, awareness, acceptance, satisfaction, and uptake. Data will be summarized descriptively, supported by tables, charts, and narrative synthesis. Results: Findings are expected to demonstrate that culturally sensitive, multimodal interventions particularly when delivered prenatally enhance knowledge retention, reduce anxiety, and increase epidural uptake, especially in historically underserved populations. Digital interventions such as mobile apps and videos are emerging, though accessibility remains a challenge. Gaps in long-term outcome data and limited attention to diverse racial and rural populations are anticipated. Conclusions: This review will inform the development of standardized, scalable, and culturally relevant educational strategies to promote informed decision-making, patient autonomy, and equitable access to neuraxial labor analgesia.
Background: Antidepressant use and withdrawal are often accompanied by side effects such as dizziness, weight gain, and sexual dysfunction. Antidepressants and associated side effects are stigmatized...
Background: Antidepressant use and withdrawal are often accompanied by side effects such as dizziness, weight gain, and sexual dysfunction. Antidepressants and associated side effects are stigmatized topics. Social media platforms like Reddit are considered "safe spaces" by users because they can freely share their experiences and receive support. Objective: This study aimed to examine how users talk about antidepressant side effects, withdrawal symptoms, and related experiences of depression on the subreddit r/depression. Methods: We scraped 10 high-engagement threads from the r/depression subreddit using the Python wrapper for the Reddit API and conducted a two-step analysis. First, a pilot test was performed using Sertraline/Zoloft threads, followed by analysis of all antidepressant threads. A subset of data was hand-coded to create and validate regular expressions, which were then used to automatically code the remaining dataset. The resulting coded data were analyzed using Epistemic Network Analysis (ENA) and complemented with qualitative analysis, elements of semantic networks, and hypergraphs. Results: We found that posts are more likely to discuss emotional flattening, sleep, and memory or brain issues. Additionally, references to dizziness tended to occur with discussions of withdrawal and offers of empathy, while reports of dream-related side effects and requests for personal experiences co-occurred frequently. With the additions of elements of semantic networks and hypergraphs, we deduced that offers of empathy occurred when users said they experienced dizziness caused by withdrawal, while mentions of brain zaps from withdrawals received teaching support. Conclusions: Study findings highlight how individuals experiencing antidepressant side effects and withdrawal symptoms use online forums like Reddit to seek validation, share coping strategies, and provide emotional support to others. The nuanced discussions observed, particularly around empathy, symptom management, and shared learning, underscore the role of peer-to-peer networks in normalizing stigmatized experiences and mitigating isolation associated with antidepressant use. Clinicians and digital health practitioners can leverage these insights to better understand patient language, emotional framing, and informational needs outside clinical settings.
Background: Despite rapid technological advancement, digital elderly care services have yet to achieve widespread acceptance among older adults, underscoring the imperative to identify the factors inf...
Background: Despite rapid technological advancement, digital elderly care services have yet to achieve widespread acceptance among older adults, underscoring the imperative to identify the factors influencing their adoption. Objective: This study employs digital meal assistance services as a representative case to analyze the determinants of low adoption rates through the theoretical lens of behavioral attitudes. Methods: Utilizing survey data from 1,019 individuals aged 60 and above, this research applies exploratory factor analysis (EFA) to delineate the structure of attitudes, complemented by Logit models to empirically verify their impact on service usage. Results: Behavioral attitudes were conceptualized across five dimensions: burden reduction, convenience facilitation, service acceptance, digital trust, and funding sources. Findings indicate that older adults prioritize the potential of these services to alleviate care burdens on their children. Notably, while low-income older adults recognize the value proposition, they demonstrate the lowest levels of trust. Conclusions: The study concludes that attitudinal variances are a significant contributor to the intention-behavior gap in digital service adoption. Consequently, digital meal assistance should be viewed as complementary to, rather than a replacement for, traditional support models. Policy interventions should prioritize trust-building and burden reduction strategies. Clinical Trial: there is no trial in the paper
Background: Cognitive function, inhibitory control (IC), cognitive flexibility (CF), working memory (WM), and attention are higher-level executive control functions with a complex relationship. There...
Background: Cognitive function, inhibitory control (IC), cognitive flexibility (CF), working memory (WM), and attention are higher-level executive control functions with a complex relationship. There is only limited evidence on the effectiveness of electroacupuncture at acupoints GV20 and GV24 to improve executive control function. Objective: This study aimed to evaluate the clinical effectiveness of electroacupuncture at acupoints GV20 and GV24 to alleviate deficits in executive control. Methods: A single-blind randomized controlled trial was conducted at the First Affiliated Hospital of Henan University of Chinese Medicine involving 76 patients with post-stroke cognitive impairment (PSCI) aged 18 to 74 years. The participants were randomly assigned to either the electroacupuncture group or the conventional treatment group at a 1:1 ratio, with 38 individuals in each group. In addition to receiving conventional treatment, the electroacupuncture group underwent electroacupuncture at acupoints GV20 and GV24 for 30 minutes, 5 times a week, for 4 weeks. Participants were assessed using the Montreal Cognitive Assessment (MoCA), Trail Making Test (TMT), Stroop Color Word Test (SCWT), and Stroke Specific Quality of Life Scale (SSQOL) both before and after intervention. Results: Using an intention-to-treat (ITT) analysis, both the electroacupuncture and control groups demonstrated significant improvements in executive control function, overall cognitive function, and activities of daily living compared to baseline. Specifically, the electroacupuncture group exhibited highly significant improvements in TMT-A (Z=−4.859, OR −23, 95% CI −29.50 to −17.50, P <.001), TMT-B (Z=−5.316, OR −34, 95% CI −42.50 to −28.00, P <.001), SCWT-W (Z=−5.375, OR −28, 95% CI −34.00 to −22.50, P <.001), and SCWT-CW scores (Z=−5.178, OR −44, 95% CI −59.00 to −34.50, P <.001). In the control group, significant improvements were observed in TMT-A (Z=−3.785, OR −8, 95% CI −11.00 to −4.50, P <.001) and SCWT-W scores (T=3.893, OR 8.158, 95% CI 3.912 to 12.404, P <.001), while TMT-B (Z=−2.882, OR −11.50, 95% CI −21.00 to −4.00, P =.004) and SCWT-CW scores (Z=−2.448, OR −12, 95% CI −21.00 to −2.00, P =.025) showed significant enhancements. Both groups experienced significant improvements in MoCA, and SS-QOL scores (P <.001) compared to baseline. Notably, when comparing the electroacupuncture group to the control group, the electroacupuncture group exhibited highly significant improvements in SCWT-W scores (Z=−3.414, OR 24, 95% CI 10 to 36, P <.001) and significant enhancements in MoCA (t=−2.908, OR −2.396, 95% CI −4.038 to −0.754, P =.005), SSQOL (T=−2.104, OR −13.921, 95% CI −27.103 to −0.739, P =.039), and SCWT-CW scores (Z=−2.244, OR 45, 95% CI 6 to 83, P =.025). Conclusions: Electroacupuncture at acupoints GV20 and GV24 demonstrated significant efficacy in ameliorating executive control deficits in PSCI patients. This intervention effectively restored key executive control functions, such as IC, CF, attention, and WM, while also enhancing overall cognitive function and the activities of daily living following a stroke. Clinical Trial: ChiCTR2300074400
Background: Obesity is associated with numerous health issues, and early identification and intervention in high-risk individuals can improve prognosis. Objective: This study evaluated the impact and...
Background: Obesity is associated with numerous health issues, and early identification and intervention in high-risk individuals can improve prognosis. Objective: This study evaluated the impact and effectiveness of an integrated health management program on the weight of individuals with obesity. Methods: We retrospectively collected case management data from 97 individuals with obesity (≥20 years) who received weight management care between September 1, 2023, and April 30, 2024. Exclusions included weight-loss medications, surgery, and other weight-loss programs. Data comprised patient demographics, medical history, health behaviors, and physical examination results. Follow-up data were obtained from a health management platform and hospital database. Statistical analyses used paired t-tests, Wilcoxon signed-rank tests, and generalized estimating equations (GEE). Results: The 2-month completers achieved a greater weight loss (−0.87 ± 1.35 kg) than 1-month completers (−0.03 ± 0.75 kg; p < 0.001). Health behavior scores improved at both time points (all p < 0.001), and step counts increased 8.9-fold overall and 10.5-fold among 2-month completers (p < 0.001). Among 2-month completers, those engaging in ≥3 program components had a lower adjusted weight (86.0 ± 1.6 kg) than those engaging in <3 program components (89.3 ± 1.7 kg; F = 6.09, p = 0.017). GEE models showed that ≥3-component engagement increased odds of weight loss by 16.6-fold at 1 month and 23.2-fold at 2 months. Conclusions: Weight loss improved in a dose-dependent manner, with ≥3-component engagement showing the strongest effects. Long-term studies with booster contacts are needed to validate the sustained benefits of our integrated health management program. Clinical Trial: none
Background: AD is a chronic and relapsing inflammatory dermatologic condition marked by erythematous, pruritic lesions. Multiple factors like psychological stress, lifestyle factors, and socioeconomic...
Background: AD is a chronic and relapsing inflammatory dermatologic condition marked by erythematous, pruritic lesions. Multiple factors like psychological stress, lifestyle factors, and socioeconomic determinants influence disease progression and treatment outcomes globally. Clinical trials evaluating AD interventions face challenges in recruitment and retention of underserved patient populations, potentially compromising the generalizability of findings to wider populations. This study aims to investigate recruitment and retention strategies in Atopic Dermatitis (AD) clinical trials. Objective: This study aims to investigate recruitment and retention strategies in Atopic Dermatitis (AD) clinical trials. Methods: We conducted a cross-sectional analysis following PRISMA guidelines to assess recruitment and retention strategies in AD clinical trials. The relevant clinical trials were acquired in a comprehensive search of MEDLINE (PubMed) and Embase (Elsevier) on May 28, 2024. Data were extracted from trials published between January 1, 2013 and December 31, 2023. For statistical analysis, Stata 18 SE (StataCorp LLC, College Station, TX) was used to determine the frequencies of recruitment and retention strategies. Results: Of the 32 trials analyzed, only 4/32 (12.5%) integrated recruitment strategies to include underrepresented populations and only 4/32 (12.5%) had planned diversity goals to improve recruitment. Three out of the 32 (9.4%) studies reported challenges with recruitment. Conclusions: : Our study highlights the need for inclusive recruitment and retention strategies in AD clinical trials. The lack of diverse representation in clinical trials can contribute to obstacles in medical research and can eventually prevent advancements in treatment outcomes. It is essential to address these gaps to ensure the external validity of research findings and to improve treatment outcomes.
Background: Hansen’s Disease, a chronic infectious disease, presents with a variety of cutaneous lesions. Being the “great mimicker” that it is, patients may often be misdiagnosed initially, hen...
Background: Hansen’s Disease, a chronic infectious disease, presents with a variety of cutaneous lesions. Being the “great mimicker” that it is, patients may often be misdiagnosed initially, hence the delay in the initiation of the multidrug therapy. Dermoscopy offers an effective, efficient, operator-friendly and non-invasive adjunctive tool in the diagnosis of Hansen’s Disease. Objective: The general objective of the study is to describe the common dermoscopic features according to clinical and histologic findings among all newly diagnosed Hansen’s Disease patients in a tertiary institution within the study period of 6 months. Methods: Purposive sampling was applied to include all newly diagnosed and biopsy-proven Hansen’s Disease patients aged 18 years to 65 years. Participants were clinically examined and dermoscopy was performed on a representative lesion. Other data were collected from chart review, acid fast smear and histopathology reports. Results: The main dermoscopic feature of Hansen’s Disease is yellowish orange areas observed in all 23 cases studied regardless of the spectrum. This feature can be attributed well to the presence of granuloma formation and inflammation. Another common feature is the presence of white globules and dots which correlates to the presence of the grenz zone, while vascular structures correlate with dilated blood vessels on histopathology. Conclusions: The major dermoscopic features seen in the study may add to the clinical clues to arrive at a diagnosis of Hansen’s Disease. Although dermoscopy alone is insufficient for the confirmation of Hansen’s Disease, combining it with physical findings would provide additional basis for its clinical diagnosis.
For decades, global guidance for sedentary behaviour and sleep has primarily been informed by studies that relied on self-report questionnaires to assess behaviours. However, it is widely recognised t...
For decades, global guidance for sedentary behaviour and sleep has primarily been informed by studies that relied on self-report questionnaires to assess behaviours. However, it is widely recognised that self-reported data suffer from numerous limitations, including recall and social desirability biases, as well as poor validity and precision. The Prospective Physical Activity, Sitting and Sleep consortium (ProPASS) is a large international collaboration of cohort studies with research-grade wearables data designed to address these challenges. The ProPASS consortium looks to advance our understanding of the associations of free-living physical activity, posture (sitting, standing), and sleep with major health and non-communicable disease outcomes. In this editorial, we provide an overview of the first ProPASS scientific outputs including its growth in recent years; key advancements towards unified wearables methodologies; the ProPASS data resources, and how these will be made available to the global research community. To assist future analogous initiatives, we also share the key challenges ProPASS has encountered and discuss mitigation strategies.
Background: Cerebral palsy (CP) is a non-progressive neurological disorder affecting approximately 1.6 per 1,000 children worldwide. Children with CP in Low- and Lower-Middle-Income Countries (LLMICs)...
Background: Cerebral palsy (CP) is a non-progressive neurological disorder affecting approximately 1.6 per 1,000 children worldwide. Children with CP in Low- and Lower-Middle-Income Countries (LLMICs) face significant barriers to accessing effective rehabilitation services, which can negatively impact their functional outcomes and quality of life. Emerging technology-based rehabilitation interventions, including 3D printing, virtual reality (VR), and telerehabilitation, offer innovative and potentially cost-effective approaches to address these challenges in resource-constrained settings. Objective: The objective of this scoping review was to explore the types of technology-based rehabilitation interventions used to support children with CP in LLMICs, to identify the countries where these technologies have been implemented, and to examine the associated implementation challenges and opportunities within these settings. Methods: A systematic search of PubMed, Web of Science, and Scopus was conducted to identify studies published from 2015-2025 that evaluated technology-based motor rehabilitation interventions for children with CP in LLMICs, as defined by the World Bank. The scoping review followed Arksey and O’Malley’s methodological framework. Two independent reviewers screened titles, abstracts, and full texts, with discrepancies resolved by consensus. Data were extracted on study characteristics, intervention types, outcomes, and contextual factors related to implementation in LLMICs. Results: From 1,788 titles and abstracts screened, 255 full-text articles were assessed for eligibility, resulting in the inclusion of 11 studies spanning Egypt, Jordan, Pakistan, and India. The identified interventions encompassed Kinect® sensor-based therapy, augmented reality applications, and exergaming platforms such as the Wii¬®. The predominant implementation challenge across LLMIC settings was the high cost and limited availability of virtual reality equipment. Nonetheless, the reviewed studies highlighted several opportunities including enhanced patient engagement, increased motivation, and the potential for delivering therapy in a safe environment. Conclusions: This scoping review highlights the growing implementation of technology-based rehabilitation interventions for children with CP in LLMICs. Technologies such as virtual reality, augmented reality, and exergames demonstrate promise in improving motor function and fostering patient motivation and engagement. Despite cost and accessibility barriers, these innovative tools including virtual and augmented reality and exergames represent viable, scalable solutions for augmenting rehabilitation services in low-resource settings.
Background: Mpox was declared a public health emergency of international concern in 2022. Instagram is widely used by age groups and communities disproportionately affected by mpox, yet platform-speci...
Background: Mpox was declared a public health emergency of international concern in 2022. Instagram is widely used by age groups and communities disproportionately affected by mpox, yet platform-specific evidence on mpox information characteristics and engagement is limited. Objective: To characterize sources, content, and engagement features of mpox-related Instagram posts, to describe prevention and treatment framing, and to compare the top 10% most-liked posts with the remaining corpus. Methods: We retrieved English-language public Instagram posts via CrowdTangle containing “mpox” or “monkeypox” dated May 5, 2022 to January 17, 2023 (initial N=18,616). Using a pretested, deductive codebook adapted from prior Instagram health studies, two coders completed two pilot rounds; variables with low agreement were excluded. Interrater reliability across retained variables showed mean κ=0.70 (median κ=0.83). A randomized analytic sample of N=1,000 posts was coded for source type, content features, and prevention/treatment framing. Descriptive statistics were computed. For engagement contrasts, we compared the top 10% most-liked posts with the bottom 90% using tests of differences in independent proportions (mean differences [MD] with p-values). Results: Most posts originated from organizations (76.0%) versus individuals (24.0%). Organizational sources most commonly included businesses (57.4%) and news/media outlets (52.8%); government (22.9%), nonprofits (17.3%), and health-care organizations (9.2%) were less frequent. About one-third of posts cited a source (34.4%), most often the WHO and CDC/other federal entity. Posts predominantly used illustrated images/infographics (82.7%); photos appeared in 47.3% and videos in 12.4% of posts. Prevention content appeared in 38.4% of posts, most commonly vaccination (68.5% of prevention posts), followed by avoiding close contact (14.5%), avoiding contact with objects (8.3%), abstaining from sexual activity (7.6%), and condom use (1.3%); 28.9% of prevention posts noted barriers. Treatment mentions were uncommon (2.5% traditional biomedical; 0.2% alternative). Compared with the bottom 90%, the top 10% most-liked posts: 1) were more likely to originate from public figures/celebrities among individuals (MD=-0.591; p<.001) and from businesses (MD=-0.299; p<.001) or news/media (MD=-0.350; p<.001) among organizations; 2) were less likely to be from government, nonprofit, or health-care organizations (all p<.01); and more often included non-moving images (MD=-0.119; p<.05), visible lesion depictions (MD=-0.081; p<.05), prevalence mentions (MD=-0.180; p<.001), and citations (MD=-0.162; p<.01). Conclusions: During the initial outbreak period, highly engaged mpox content on Instagram skewed toward posts by public figures and news/business accounts and toward static, citation-bearing visuals that included prevalence context and occasionally lesion imagery. Public-health communicators seeking reach on Instagram should prioritize clear static infographics with explicit source citation and epidemiologic context and consider co-publishing with trusted creators and news outlets, while addressing access barriers highlighted in prevention posts.
Background: Atypical fibroxanthoma (AFX) is a rare mesenchymal neoplasm that is most commonly identified on sun-exposed areas of the head, neck, and dorsal extremities of elderly patients. Objective:...
Background: Atypical fibroxanthoma (AFX) is a rare mesenchymal neoplasm that is most commonly identified on sun-exposed areas of the head, neck, and dorsal extremities of elderly patients. Objective: To present a rare case of AFX, its clinical presentation, histopathology, treatment, and to discuss the use of immunohistochemistry as a method in diagnosing AFX. Methods: We evaluated a 67-year-old woman with a history of basal and squamous cell carcinomas who presented with a rapidly enlarging, tender papule on the dorsal left hand. Prior topical fluorouracil therapy was ineffective. Histopathologic examination confirmed the diagnosis, and treatment was initiated. A literature review was performed to place this case in context with other reported instances of AFX. Results: Clinical examination revealed a 1.2 cm dome-shaped, red-pink papule; shave biopsy demonstrated histopathologic features consistent with atypical fibroxanthoma (AFX). The patient was referred to Mohs micrographic surgery with a high cure rate, where the tumor was cleared in a single stage, with histologically negative margins. Conclusions: This case highlights the importance of clinicopathologic correlation, appropriate use of immunohistochemistry, and evidence-based surgical management in AFX.
Background: In recent years, digital mental health interventions have become increasingly important due to the rising demand for psychotherapy and the shortage of resources. Digital inpatient-like psy...
Background: In recent years, digital mental health interventions have become increasingly important due to the rising demand for psychotherapy and the shortage of resources. Digital inpatient-like psychotherapy (DIPT) is a therapeutic concept that allows patients to receive inpatient-like psychotherapy in a digital environment. Objective: This qualitative interview study sheds light on patients' attitudes and expectations towards digital inpatient-like psychotherapy in terms of acceptance, perceived benefits and barriers, as well as suggestions for initial implementation steps Methods: Semi-structured interviews were conducted with 20 patients receiving day-patient or inpatient psychotherapy in a university hospital. Iterative thematic analysis and inductive coding were conducted by three independent researchers following Braun and Clarke’s approach to thematic analysis. Three main categories emerged with multiple subsidiary themes and subthemes. Results: Interviewees included individuals with various mental health disorders. The analysis of the interviews revealed three categories ((1) requirements for effective implementation of DIPT, (2) influence of familiar environment and digital communication on the interpersonal level, and (3) patients’ benefits from DIPT) with seven themes. The overall attitude and acceptance towards digital inpatient-like psychotherapy was predominantly positive, with interviewees recognizing numerous benefits including location independency, time flexibility, and increased openness towards personal mental health issues. However, potential barriers such as lack of personal prioritization, tendencies for social withdrawal or insufficient relationship building must be addressed and considered. Conclusions: Interviewees included individuals with various mental health disorders. The analysis of the interviews revealed three categories ((1) requirements for effective implementation of DIPT, (2) influence of familiar environment and digital communication on the interpersonal level, and (3) patients’ benefits from DIPT) with seven themes. The overall attitude and acceptance towards digital inpatient-like psychotherapy was predominantly positive, with interviewees recognizing numerous benefits including location independency, time flexibility, and increased openness towards personal mental health issues. However, potential barriers such as lack of personal prioritization, tendencies for social withdrawal or insufficient relationship building must be addressed and considered.
Background: While healthcare providers are the most trusted sources of health information, service establishments within communities represent important yet underutilized sources of health information...
Background: While healthcare providers are the most trusted sources of health information, service establishments within communities represent important yet underutilized sources of health information. Specifically, food and beauty establishments can act as alternative settings for health communication, facilitating broader engagement with the general population. Objective: This study examined factors associated with willingness to receive health information from these non-healthcare services among community-dwelling adults in Singapore. Methods: A cross-sectional survey was conducted among residents in two neighbourhoods in Central Singapore between November 2024 and April 2025. Data on socio-demographics, trust in information from healthcare and non-healthcare sources, and willingness to receive health information were collected anonymously. Multivariable logistic regression identified factors independently associated with willingness to receive health information from non-healthcare sources. Results: Most of the 403 respondents were aged ≥50 years (55.3%), female (54.3%), Chinese (82.6%), and higher educated (74.9%). Of the 339 respondents with no prior exposure to health information from non-healthcare services, nearly one-in-three (31.3%) reported that they were willing to receive health information from these sources. In adjusted analysis, those who trusted health information (AOR 3.71 [95% CI: 1.50, 9.19]) and those with high health information orientation (AOR1.89 [95% CI: 1.11, 3.21]) were more willing to receive health information from non-healthcare services in the future. Trust in health information increased willingness among those aged 21-34 years (AOR 4.98 [95% CI: 1.35, 18.30]), those aged 35-49 years (AOR 8.02 [95% CI: 2.62, 24.59]), and males (AOR 6.22 [95% CI: 2.79, 3.89]) to receive health information from these sources, but not among those aged ≥50 years (AOR 1.92 [95% CI: 0.92, 4.02]) or females (AOR 1.85 [95% CI: 0.87, 3.96]). Conclusions: Nearly a third of community-dwelling adults expressed willingness to receive health information from non-healthcare services, highlighting the potential for leveraging these channels in health communication. Higher level of willingness was positively associated with higher health information orientation and greater trust. Additionally, trust in non-healthcare services enhanced the willingness among those aged 21-49 years and males. Building age- and gender-sensitive trust strategies could strengthen engagement through non-healthcare channels.
Background: Stunting affects 21.6% of Indonesian children under five, with complications from high-risk pregnancies (HRP) identified as a potential determinant. The Developmental Origins of Health and...
Background: Stunting affects 21.6% of Indonesian children under five, with complications from high-risk pregnancies (HRP) identified as a potential determinant. The Developmental Origins of Health and Disease (DOHaD) framework suggests that prenatal exposures may permanently alter physiological development and disease susceptibility later in life. Objective: This study aimed to examine the cumulative effects of HRP complications on the risk of stunting in Indonesian children under five, while controlling for socioeconomic confounders. Methods: A retrospective study was conducted in Sleman Regency, Indonesia, analyzing 450 children (300 stunted and 150 non-stunted) aged 12-59 months. Data were collected from maternal medical records, MCH handbooks, and integrated health post reports. Multivariate logistic regression was used to adjust for socioeconomic confounders including maternal education, family income, and antenatal care visits. Results: Mothers of stunted children had significantly higher rates of any HRP complication (68.7% vs. 32.0%, p < 0.001). After adjustment, multiple HRP complications (≥2 conditions) showed the strongest association with stunting (adjusted odds ratio [aOR]=5.80; 95% confidence interval [CI]: 3.26–10.32), exceeding the risk associated with individual complications such as anaemia (aOR=3.21; 95% CI: 2.12–4.86) or pre-eclampsia (aOR=4.37; 95% CI: 2.18–8.76). Maternal education (aOR = 0.72), family income (aOR = 0.68) and antenatal care visits (aOR = 0.85) were identified as protective factors. Conclusions: The dose-response relationship between cumulative HRP complications and stunting supports the DOHaD hypothesis. Current antenatal care protocols focusing on single risk factors may be insufficient. Integrated prenatal care addressing cumulative risks is essential for stunting prevention in Indonesia. Clinical Trial: -
Background: Mental health problems among university students are a growing global concern, yet limited resources and inadequate understanding of counseling procedures often delay support. Informed con...
Background: Mental health problems among university students are a growing global concern, yet limited resources and inadequate understanding of counseling procedures often delay support. Informed consent forms (ICFs) are vital for protecting rights and autonomy, but many are incomplete, ambiguous, or overly technical, and few institutions can effectively optimize them. Large language models (LLMs) offer scalable, low-cost solutions to enhance clarity and accessibility. Objective: This study aimed to evaluate whether LLM-based optimization could improve the structure, readability, content quality, and comprehensibility of university counseling ICFs, and to compare the performance of two advanced models—ChatGPT-5 and Grok-4. Methods: Counseling ICFs from 33 Chinese universities were collected and optimized using two advanced LLMs, ChatGPT-5 and Grok-4. A multidimensional framework assessed textual structure and readability, content quality from counselors’ perspectives, and comprehension from clients’ perspectives. Evaluations were conducted by mental health professionals and student volunteers. Wilcoxon signed-rank tests and linear mixed-effects models were applied for comparison and validation. Results: Compared with the originals, LLM-optimized ICFs demonstrated significant gains across all dimensions. The Lee–Yang readability index decreased from 28.68(5.69) to 22.39(2.13) with ChatGPT-5 and 24.37(2.32) with Grok-4 (both P<.001), while tone friendliness increased from 2.57(0.29) to 2.67(0.12) and 2.67(0.13), respectively. Expert-rated content quality improved from 45.33(8.74) to 52.54(7.92) and 55.49(7.81) (P<.001), primarily through enhanced specificity and existence of key items. Client comprehension scores rose from 19.02(1.32) to 22.33(0.81) and 22.05(0.90) (P<.001), reflecting higher clarity, readability, and acceptability. Linear mixed-effects models confirmed these findings. Conclusions: LLM-based rewriting markedly improved the clarity, completeness, and readability of counseling consent forms. By enhancing linguistic accessibility and professional precision, these models can support clearer communication and stronger counselor–client understanding. For universities with limited counseling resources, integrating LLM-assisted optimization may represent a practical step toward standardized, comprehensible, and client-centered counseling documentation. Clinical Trial: Not applicable.
Background: Violent content is becoming increasingly prevalent on digital media platforms. Understanding the nature of this violence and public perception is important for public health initiatives. O...
Background: Violent content is becoming increasingly prevalent on digital media platforms. Understanding the nature of this violence and public perception is important for public health initiatives. Objective: The investigation focuses on identifying prevalent discourse patterns, emotional responses across demographic groups, and thematic clusters that emerge from organic public conversations about media violence. Methods: This study employs advanced computational methods to analyze a comprehensive dataset of Instagram comments related to media violence and public health. Results: The sentiment analysis of 87.493 Instagram comments revealed a predominantly negative discourse surrounding media violence. The dominant emotions in the analysis of public discourse were found to be fear and anger. It was determined that there was disappointment due to the failure of relevant stakeholders to take action against violence in the media, or due to inadequate responses. Health professionals stated in 67% of their comments that exposure to media violence could be associated with anxiety, depression, and behavioral disorders in individuals. Conclusions: There are significant gaps in the public's understanding regarding individual differences in responses to media violence. The findings indicate that while public discourse demonstrates sophisticated understanding of certain media violence dimensions, but also highlight the necessity of media literacy to increase public awareness of research-supported protective strategies and individual difference factors that mitigate the effects of media violence.
Purpose: We aim to create and compare two digital-health pipelines for voice recording and speech analyses based on smartphones and professional recording equipment. We benchmark the quality of the sm...
Purpose: We aim to create and compare two digital-health pipelines for voice recording and speech analyses based on smartphones and professional recording equipment. We benchmark the quality of the smartphone recordings on speech features previously shown to be predictive of neurological impairment.
Approach: A mobile phone app that records a user performing three speech tasks on the smartphone’s built-in microphone is developed. Simultaneously they are recorded using professional recording equipment. Speech features are extracted and compared across each recording pair. Speakers performed three speech tasks – reading a text, repeating syllables for 20 seconds, and sustaining a vowel. Bland-Altman visualization, Deming regression, correlation tests (Spearman, Intraclass) and Kolmogorov-Smirnov tests were utilized to assess concordance degree across devices. Dotplots and standard deviation across speaker and across time were used to assess longitudinal stability. Signal-to-Noise ratios were utilized to assess inter-and-within-rater reproducibility. The robustness of the features over time was assessed by the relative size of differences between speakers and measurement error and profiling the reproducibility of the measurements in a test-retest scenario.
Results: A corpus of 20 recording sessions was collected from 3 speakers, with one speaker recording 6 sessions spanning 5 months. Twenty-three speech features served as a basis for assessing concordance between recording pairs. 19/23 (80%) features were found to be significantly correlated across recording methods; 10/23 (43%) features have statistically-significant p-values. The smartphone’s noise-cancellation seems to be affecting some features. Most features (14/23, 63%) are longitudinally unstable.
Conclusions: A voice recording and speech analyses pipeline using a smartphone appears potentially capable of capturing the essential variability of the speech features used for establishing and validating speech biomarkers. Device-dependent noise-reduciton algorithms deployed in modern smartphones need to be handled with care. Much-larger-N Case-Control studies are needed to validate and extend these preliminary findings to clinical setting and across specific neurological disease states.
Background: Mental health Conversational Agents (MHCAs), or chatbots, are increasingly used to provide accessible, scalable support for individuals experiencing psychological distress. While these too...
Background: Mental health Conversational Agents (MHCAs), or chatbots, are increasingly used to provide accessible, scalable support for individuals experiencing psychological distress. While these tools, whether AI-driven or scripted, hold promise for expanding mental health care, concerns remain regarding their safety, responsiveness, and appropriateness, especially for trauma-exposed users. Trauma-informed care (TIC), a well-established framework in in-person therapy, emphasizes safety, trust, empowerment, collaboration, peer support, and cultural sensitivity. However, little is understood about how users interpret and prioritize TIC principles when engaging with chatbot-based mental health support. Objective: This study aimed to explore 1) how users conceptualize trauma-informed care in the context of mental health chatbots and 2) what factors can help us to predict whether users perceive their chatbot interaction as trauma-informed. Methods: A web-based, self-administered survey (REDCap) was completed by 606 participants recruited via ClickWorker, social media, and MyChart. The 59-item survey (multiple response questions, Likert Scale, open-ended) assessed demographics, technology use, adverse life experiences, chatbot use, and perceptions of TIC and satisfaction with MHCAs. To identify latent domains representing how participants structure their understanding of TIC in conversational agents' contexts, Exploratory and Confirmatory Factor Analyses were conducted. To identify factors to predict trauma-informed interaction, multivariable logistic regression models were used. Results: Participants reported high overall satisfaction (84.5%) and high trauma-informed perception (92.9%) of their chatbot experience. Factor analyses yielded a validated five-domain structure: Trust & Transparency, Data Safety, Empowerment, Peer Support, and Cultural Sensitivity, with excellent model fit (CFI = 0.978, RMSEA = 0.045). Regression analyses identified Trust (OR = 3.89, p = .001), Empowerment (OR = 1.97, p = .025), and Peer Support (OR = 1.73, p = .021) as significant positive predictors of TIC perception. In contrast, citing convenience as a primary use reason (OR = 0.33, p =.041) and higher smartphone proficiency (OR = 0.38, p = .033) were negatively associated with TIC perception. Conclusions: This study offers an empirical foundation for defining and measuring trauma-informed design in mental health conversational agents. Key TIC features such as trust-building, emotional validation, and peer connection significantly shape user perceptions. Results underscore the need for AI-based mental health tools to align with trauma-informed principles and adapt to diverse user expectations to enhance therapeutic safety, credibility, and inclusivity.
Background: Electronic health records are a vast and valuable source of information, useful for tasks such as estimating disease prevalence. However, much of this information, particularly doctors’...
Background: Electronic health records are a vast and valuable source of information, useful for tasks such as estimating disease prevalence. However, much of this information, particularly doctors’ notes, is in free-text format rather than in a structured form and is therefore not readily amenable to analysis. Manual coding of this textual data is both time-consuming and resource-intensive, making it impractical for large datasets. The advent of powerful open-source language models offers innovative solutions to this scalability challenge. Objective: By providing hands-on guidance for applied health researchers, this study aims to demonstrate the effective and accurate automatic classification of free-text notes using a language model fine-tuned for automated International Statistical Classification of Diseases and Related Health Problems – 10th version (ICD-10) coding. Methods: Building on the extensive ‘FIRE’ routine database from the Institute of Primary Care at the University Hospital Zurich and the University of Zurich, we trained a large language model–based multi-label classifier on a dataset of 38’728 free-text notes which had been manually categorized into 48 classes, using specific ICD-10 codes and code ranges or non-diagnostic/ad hoc labels (e.g., ‘unclear diagnosis’, ‘status post’). We stratified the labelled data into training (70%), validation (15%) and post-training test (15%) sets, ensuring similar label distributions across these sets. Using the Transformers Python library, we trained the model over 10 epochs and evaluated it on the post-training test dataset. Results: Across 48 classes, the FIRE classifier achieved strong performance on the held-out post-training set: F1 = 0.85 (micro, overall across all predictions), 0.86 (macro, mean of per-class scores treating classes equally), and 0.84 (weighted, per-class scores weighted by class frequency). Conclusions: This study demonstrates steps for training open-source models and highlights the potential of large-scale language models to streamline and scale the extraction of diagnostic information for practical applications. Our model can be robustly deployed, for example, for pre-screening and labelling of free-text information, thus potentially reducing the burden of repetitive and error-prone manual handling. Clinical Trial: N/A
This is a single center, cross-sectional, anonymous survey of medical students at the University of Colorado School of Medicine who had completed an anesthesia rotation. We sought to assess medical st...
This is a single center, cross-sectional, anonymous survey of medical students at the University of Colorado School of Medicine who had completed an anesthesia rotation. We sought to assess medical student perceptions of inclusivity for LGBTQIA+ identifying people within our specialty. We demonstrate the feasibility of querying medical student perception of anesthesiology via an online survey.
Background: The COVID-19 pandemic highlighted the importance of public health communication while exposing its shortcomings, particularly among African American communities disproportionately affected...
Background: The COVID-19 pandemic highlighted the importance of public health communication while exposing its shortcomings, particularly among African American communities disproportionately affected by the virus. Traditional expert-driven communication campaigns often failed to resonate with this population due to pandemic fatigue, misinformation, and longstanding mistrust. Culturally grounded and co-created communication strategies are increasingly recognized as critical to improving the effectiveness of public health messaging. However, limited experimental evidence exists to evaluate whether community such messages outperform traditional expert-developed messages in promoting engagement and behavioral intent. Objective: This study aimed to evaluate the effectiveness of community co-created messages, developed through participatory design methods and supported by generative artificial intelligence tools, in promoting COVID-19 preventive behaviors among African American adults in North Carolina. Specifically, we sought to determine whether participatory messages outperformed standard public health messages in enhancing message credibility, emotional engagement, and behavioral intent. Methods: We employed a multi-phase crowdsourcing approach, including two open calls and a designathon, to develop a culturally grounded, community-driven video promoting COVID-19 prevention. A key innovation was the integration of generative AI tools enabling designers to translate ideas into digital outputs without requiring technical expertise. The community-driven video was compared with an expert-designed video widely circulated during the pandemic. African American adults (N = 546) recruited online were randomly assigned to view one of the two videos and then completed a survey assessing narrator relatability, youth versus adult appeal, motivation, attention, and perceived behavioral impact. Results: Regression analyses controlling for demographics indicated that participants rated the community-driven video as significantly more relatable, motivating, attention-grabbing, and behaviorally impactful than the expert-designed video. The community-driven video was also perceived as more appealing to youth, while the expert-designed video was seen as more appealing to adults. No significant differences emerged for message agreement or likelihood to recommend. Conclusions: Findings provide empirical evidence that community-driven communication can increase message appeal among African American audiences. Incorporating participatory design and creative co-production processes into public health campaigns may increase their resonance, strengthen trust, and improve equity in health communication. These results provide experimental support for embedding community perspectives at the center of message development in future public health initiatives.
Background: Accurate small area estimates of vaccination rates and disease burden can inform public health interventions. Objective: To compare population denominators derived from census data and ele...
Background: Accurate small area estimates of vaccination rates and disease burden can inform public health interventions. Objective: To compare population denominators derived from census data and electronic health record (EHR) data from a statewide collaboration in Minnesota and examine concordance between CDC and EHR-based estimates of diabetes and hypertension prevalence at the census tract level. Methods: Retrospective study utilizing EHR data from 2018-2022 from the Minnesota EHR Consortium (MNEHRC), population estimates from 2020 census data, and disease prevalence estimates among adults from the Centers for Disease Control and Prevention (CDC) Population Level Analysis and Community Estimates (PLACES) project. Patients were included if they had a Minnesota address and a clinic visit in the last 3 years. Patients with hypertension and diabetes were identified based on the presence of at least one diagnosis code in the OMOP condition occurrence table in the last five years or an elevated outpatient blood pressure (systolic blood pressure ≥140 mmHg or diastolic blood pressure ≥90 mmHg) on two or more days in the last three years for hypertension or at least one A1c ≥6.5 in the last three years for diabetes. Results: There were 5,271,191 unique individuals who had a visit in the last three years (2018-2020) at one of the 11 MNEHRC healthcare systems. This represents 92% of the 2020 census estimate for Minnesota (5,707,254). The ratio of MNEHRC patients to the Minnesota statewide 2020 census estimate was higher for females (0.97) than males (0.88) and higher for older age groups (age 65 years and older: 1.05) than younger age groups (age 0-17 years: 0.83). The MNEHRC patient to census ratio also differed by race – the ratio was highest for Black Minnesotans (1.17) and lowest for American Indian/Alaska Native Minnesotans (0.68). According to MNEHRC data, the number of adults in Minnesota with diabetes was 415,914 (9.5%) and the number with hypertension was 1,365,413 (32%). Estimates from PLACES for diabetes was 435,481 (9.9%) and for hypertension was 1,311,459 (30%). The percent of census tracts where the MNEHRC estimate was within 10% of the PLACES estimate was 40% for diabetes and 42% for hypertension 78% and 80% were within 25% respectively. Conclusions: Our analysis suggests that there are both similarities, as well as important differences between small-area estimates derived from EHR and survey data. Such differences suggest further research is needed to determine the optimal collection method for local estimates of health conditions.
Background: Neighborhood disinvestment, characterized by built environment disrepair and deterioration, has been linked to health behaviors and outcomes, including cancer survival. While prior studies...
Background: Neighborhood disinvestment, characterized by built environment disrepair and deterioration, has been linked to health behaviors and outcomes, including cancer survival. While prior studies have assessed spatial variation, temporal dynamics of disinvestment remain underexplored, despite potential relevance for long-latency outcomes such as colon and rectum cancer (CRC). Objective: We describe and validate a spatio-temporal neighborhood audit protocol using Google Street View (GSV) imagery, develop and compare predictive spatio-temporal models of neighborhood disinvestment and examine time-lagged associations between disinvestment and CRC survival. Methods: We conducted 8,256 virtual audits across Franklin County, Ohio (2009–2022) using seven disinvestment indicators (e.g., garbage, graffiti, abandoned buildings). After excluding ineligible images, 5,751 audits of 2,214 unique locations were included. A neighborhood disinvestment score (NDS) was derived using item response theory and adjusted for rater bias. We fit mean trend and spatio-temporal residual processes using universal kriging with a simplified sum-metric covariance structure, comparing two candidate mean trend models via out-of-sample root mean square prediction error (RMSPE). One model accounted for discrete physical barriers to define neighborhood clusters, the other was traditional kriging where NDS was allowed to vary continuously across space and time. For exposure time validation, predictions were linked to 2,727 CRC cases (2012–2019) from the Ohio Cancer Incidence Surveillance System (OCISS). We use accelerated failure time (AFT) models to estimate associations between NDS averaged over 0, 3, 6, 12, 18, and 24 months prior to diagnosis and CRC survival, adjusting for age and stage at diagnosis and demographic covariates. We test stage-specific associations between NDS and survival. Results: Spatio-temporal modeling indicated substantial spatial but modest temporal variation in disinvestment, with small-scale spatial correlation measurable within 2.8 km and temporal correlation up to 270 days. The traditional spatio-temporal kriging model (RMSPE = 0.651) outperformed alternate models including neighborhood cluster fixed (RMSPE = 0.671) and random (RMSPE = 0.662) effect models. Seasonal effects were significant, with lower disinvestment scores in spring and summer compared to fall. The AFT model fit shows higher pre-diagnosis NDS was significantly associated with shorter survival among patients with stage 2 cancer (acceleration factor < 1 across all lag windows, P value < .05), but not among patients with stage 1 or stage 3. Associations were consistent across time lags, with slightly stronger effects for averages over 6–24 months prior to diagnosis. Conclusions: Neighborhood disinvestment exhibits substantial spatial and moderate temporal variation. Traditional spatio-temporal universal kriging provides most accurate prediction compared to models accounting for discrete neighborhood boundaries. Neighborhood disinvestment is associated with reduced CRC survival time among cases diagnosed at regional stage, highlighting the utility of built environment spatio-temporal assessments within CRC research.
Background: The COVID-19 pandemic highlighted the need for practical digital health tools to support informed decision-making amidst rapidly evolving evidence and widespread misinformation. Objective:...
Background: The COVID-19 pandemic highlighted the need for practical digital health tools to support informed decision-making amidst rapidly evolving evidence and widespread misinformation. Objective: We iteratively developed and refined VaxDA-C19, a bilingual (English and French) web-based patient decision aid designed to support informed decision-making in Canada about COVID-19 vaccination. VaxDA-C19 integrates interactive and personalized features aimed to enhance vaccine confidence, reduce cognitive overload, and respond to diverse informational needs. Methods: We developed VaxDA-C19 using an iterative, user-centered design approach. Throughout the development process, we involved a citizen panel, healthcare professionals, user experience designers, and scientific experts to guide refinements. We also conducted usability testing sessions with adults in Canada, using semi-structured interviews, comparative testing, and think-aloud protocols with thematic analysis. We ultimately conducted four design cycles in total: three with adults in Canada (cycle 1: n=9 users; cycle 2: n=22 users; cycle 3: n=3 users), one overlapping and one additional cycle with expert reviewers (cycle 3: n=5; cycle 4: n=9). Results: In Cycle 1, user feedback guided design decisions about how to present quantitative information and technical vaccine descriptions more simply. In Cycle 2, while most users (82%) favored in-depth explanations of vaccine development, a few raised concerns about content that could be perceived as politically charged. Cycle 3 identified usability improvements, including more explicit navigation controls, simplified medical terminology, and optimized interactive components (avatars, sliders). Expert reviews in Cycle 4 refined linguistic consistency, mobile responsiveness, content transparency, and scientific accuracy, emphasizing explicit instructional guidance and bilingual accessibility. Conclusions: Our iterative process produced a personalized, bilingual digital decision aid to support evidence-informed, values-congruent decisions about COVID-19 vaccination. A randomized controlled trial will further evaluate VaxDA-C19's impact on vaccination intentions, knowledge retention, emotional responses, decisional conflict, and decisional regret. If it proves effective, the patient decision aid may also be used as a platform to support other vaccine decisions, namely, influenza, measles, shingles, pertussis, and potentially other emerging infectious diseases.
Background: Few manual chiropractic HVLA (High Velocity, Low Amplitude) type shams have been validated in research. The proposed project is a randomized controlled trial (RCT) designed to assess a nov...
Background: Few manual chiropractic HVLA (High Velocity, Low Amplitude) type shams have been validated in research. The proposed project is a randomized controlled trial (RCT) designed to assess a novel, full-spine, manual sham chiropractic maneuver and its blinding success. Objective: Our primary aim is to evaluate the blinding integrity of participants receiving a genuine or sham chiropractic maneuver. We will also be evaluating the effects of genuine chiropractic treatments relative to sham chiropractic treatments by measuring several neurophysiological mechanisms. Methods: Subjects (n=60) will be recruited from in and around Marietta, GA, USA. They will undergo a chiropractic physical exam and health history review with a licensed chiropractor and be randomized to either a sham or genuine chiropractic group (1:1 ratio). Subjects, outcome assessors, and data analysts will be blinded to group allocation. The genuine group will receive Diversified HVLA chiropractic spinal manipulative therapy (SMT) while the sham group will receive a novel chiropractic HVLA-emulating therapy. Each subject will attend two sessions spaced 1-week apart. Assessments will consist of blinding surveys post-sessions (both visits) and pre-session (second visit), as well as cardiac-related electrical and mechanical activity before, during, and after an orthostatic challenge, while also tracking gait parameters. The primary outcome of interest is blinding measured via the Bang Blinding Index (Bang BI). Secondary aims include measuring blinding via the James Blinding Index (James BI) and assessing the effects of SMT on electrocardiography (ECG)-derived heart rate variability (HRV), impedance cardiography (ICG)-derived pre-ejection period (PEP), and gait parameters. Results: This study is being supported and internally funded by the Dr. Sid E. Williams Center for Chiropractic Research at Life University in Marietta, GA, USA. Our study was prospectively registered on clinicaltrials.gov (NCT06931600) on March 28, 2025 and the first participant was seen on May 5, 2025. The study is scheduled to end on March 27, 2026, after which time data analysis will begin. Conclusions: The significance of the current RCT will be in its ability to inform whether our novel, full-spine, manual sham SMT protocol successfully blinds subjects rendering it feasible for future clinical trials, as well as assessing for secondary outcome measures between groups. Clinical Trial: Our study was prospectively registered on clinicaltrials.gov (NCT06931600) on 03/28/2025.
Universities are critical engines of knowledge creation and societal transformation; however, many African institutions, particularly in Nigeria, struggle to cultivate mature and sustainable research...
Universities are critical engines of knowledge creation and societal transformation; however, many African institutions, particularly in Nigeria, struggle to cultivate mature and sustainable research cultures. This paper develops a conceptual framework for strengthening university research management systems, highlighting leadership and governance as catalysts for academic excellence, innovation, and societal relevance. Using a descriptive-analytical and comparative synthesis of international policy frameworks (UNESCO, OECD) and African higher-education reports (AAU, ARUA, NUC, and TETFund), the study integrates global best practices with contextual realities in low-resource environments. The proposed Research Leadership and Impact Framework (RLIF) outlines four interrelated components: leadership and vision, governance and systems, capacity and infrastructure, and research culture and societal impact, which collectively enable institutional transformation. Comparative indicators, such as Nigeria’s Gross Expenditure on Research and Development (GERD) of 0.22% versus South Africa’s 0.83%, illustrate the strategic significance of leadership and governance reform in closing performance gaps. The framework contributes a theoretically grounded and context-sensitive model for embedding evidence-based management, accountability, and inclusivity within African universities. Ultimately, the paper argues that building resilient research systems requires not only financial investment but visionary leadership capable of aligning academic missions with societal priorities and the Sustainable Development Goals (SDGs).
Background: Leisure-time physical activity (LTPA) is a well-established contributor to physical, psychological, and social well-being worldwide. Human touch also plays a vital role in life course heal...
Background: Leisure-time physical activity (LTPA) is a well-established contributor to physical, psychological, and social well-being worldwide. Human touch also plays a vital role in life course health, yet opportunities for safe, consensual touch are often limited, particularly in LTPA settings. For gay, bisexual, transgender, and queer (GBTQ) men, barriers to affirming LTPA spaces can make it particularly difficult to access such benefits. In response, community-based approaches that integrate touch are needed, alongside systematic evaluations of such strategies. “The Studio” (pseudonym), a membership-based wellness community, addresses this gap by offering touch-centered partner yoga and bodywork programs designed to support the holistic health of GBTQ men. Objective: This protocol describes a mixed-methods evaluation of the Studio’s touch-based yoga programming in New York City. The evaluation aims to (1) assess individual health benefits (i.e., physical, emotional, and psychological) of partner-based yoga participation and (2) examine interpersonal outcomes of intentional touch in a GBTQ wellness community, including social connection, trust, and belonging. Methods: The evaluation employs a pre- and post-test mixed-methods design. A total of 40–50 participants will be recruited from new Studio members. Quantitative measures will include flexibility (sit-and-reach, goniometry), stress (Perceived Stress Scale), body awareness (Multidimensional Assessment of Interoceptive Awareness), and resilience (Brief Resilience Scale). Social network analysis will map participant connections before and after program participation. Qualitative data will be collected through semi-structured interviews with 15–20 participants, or until saturation is reached, focusing on comfort with touch, emotional regulation, and experiences of community connectedness. Survey and interview guides will be co-developed with a Community Advisory Group to ensure cultural responsiveness and relevance. Findings will be integrated using triangulation methods to explore convergence across data sources. Results: As of October 2025, this study has not yet begun. Pending funding opportunities, Institutional Review Board submission is planned for Fall 2026. Afterward, study instruments will be finalized and pilot-tested with Studio teachers. Participant recruitment is projected to begin in Summer 2027, and data collection will include three time points (baseline, post-intervention, 4–6 week follow-up). Data analysis and dissemination of findings are expected in 2028. Preliminary pilot testing of the survey instruments with Studio employees and community advisory group members will indicate feasibility and cultural fit. Conclusions: This evaluation will be among the first to systematically examine touch-focused partner yoga for GBTQ men in a community wellness setting. Findings are expected to provide novel insights into the role of intentional touch in LTPA spaces, support trauma-informed and inclusive wellness practices, and contribute to broader discourse on GBTQ health promotion and intervention. Results will be disseminated to the Studio employees, members, and LGBTQ+-focused wellness organizations, as well as through peer-reviewed publications and conferences.
Background: Globally 537 million persons lives with diabetes, with a lifetime risk of up to 34% of developing diabetic foot ulcers (DFUs), drives preventative initiatives. Objective: The aim was to de...
Background: Globally 537 million persons lives with diabetes, with a lifetime risk of up to 34% of developing diabetic foot ulcers (DFUs), drives preventative initiatives. Objective: The aim was to develop and evaluate a clinical decision support system (CDSS) to be used by healthcare professionals (HCPs) in foot assessment and risk stratification, as a base for prevention. Methods: Based on human interaction design, the CDSS was developed for DFU. Users, HCPs from Region Västra Götaland in Sweden evaluated the functions regarding effectiveness, efficiency and satisfaction. Expectations and experiences of using the CDSS was evaluated with the System Usability Scale (SUS). Results: User expectations of the CDSS, measured by SUS, averaged 77.2±14.6. Post-test SUS scores were 68.9±14.3, with a mean difference of 8.3 (P=.071), a non-significant reduction of usability after test. The effectiveness of the CDSS in supporting users to complete nine clinical tasks, showed that for seven out of nine tasks (78%), at least five of the nine testers (56%) successfully achieved the intended goals. Tasks involving the identification of ingrown toenails and the confirmation of foot status, including the risk stratification for the patient, were completed by fewer testers. Efficiency, measured as mean task completion time, ranged from 7 seconds to 9 minutes and 20 seconds. The users found that a structured CDSS has the potential to contribute to a digital health service leading to an equal, good, and person-centred DFU prevention. Conclusions: A digital health service for DFU risk stratification, was developed based on national and international guidelines. Although the users’ expectations of the usability were higher compared to how they experienced the CDSS, the SUS test was near a threshold of 70, indicating that the system being tested was above average in usability. Further development, national and international, where the users’ needs and preferences are considered, is recommended. Clinical Trial: ClincalTrials.gov ID: NCT05692778
Background: In this manuscript, public reporting systems in healthcare are defined as digital platforms that public comparative healthcare performance data available to the public (e.g., Hospital Comp...
Background: In this manuscript, public reporting systems in healthcare are defined as digital platforms that public comparative healthcare performance data available to the public (e.g., Hospital Compare in the United States, NHS choices in the United Kingdom, or national quality registries in Europe) and MyHospital in Australia. These systems aim to improve transparency, accountability, and patient choice. While these systems have been widely studied from policy and clinical perspectives, the information systems foundations, including system architecture, interoperability, data governance and usability, that enable their operation remain underexplored. Objective: To map the extent and nature of published literature addressing the technological foundations of public reporting system in healthcare, and to identify persisting gaps in IS scholarship. Methods: Following the Joanna Briggs Institute (JBI) guidelines and reported according to PRISMA-ScR. Six databases were searched: PubMed, Web of Science, Scopus, IEEE, ACM, and Cochrane for articles published between 2000—2025. The eligible articles included peer-reviewed journal articles and conference papers on public reporting systems in healthcare. Data were charted on study characteristics, geographic distribution, healthcare system type, and methodological approach. Descriptive statistics were used to summarize findings, and a narrative synthesis identified thematic trends and research gaps. Results: We identified 3,064 records, screened 1,674 after de-duplication, and included 359 stud-ies. Most of the included studies originated from North America (65.7%), followed by Eu-rope (21.1%). Among the 359 included articles analyzed, 67% employed quantitative methods. In contrast, a smaller percentage employed qualitative methods (24%) and mixed methods (9%). Research from an information systems perspective was scarce: few studies examined system architecture, interoperability, interface design, data governance, or usability. Conclusions: Despite the centrality of information systems infrastructure to public reporting, current scholarship predominantly frames these systems as policy or social tools, neglecting their technical underpinnings. This oversight has practical implications, such as poor system usability, weak interoperability of noncompliance with data regulations. Issues that can undermine patient trust and system effectiveness. Addressing this gap requires interdisciplinary approaches that integrate information systems frameworks, sociotechnical analysis, and usability evaluation to ensure that public reporting systems are effective, equitable, and technically robust.
Background: Health-data interoperability in post-transition systems depends on enforceable standards and clear governance. Affinity domains, as defined in the IHE XDS framework, offer a combined organ...
Background: Health-data interoperability in post-transition systems depends on enforceable standards and clear governance. Affinity domains, as defined in the IHE XDS framework, offer a combined organisational-technical model for cross-enterprise data exchange. Evidence from Central Europe remains scarce. Objective: This study aimed to examine stakeholder perceptions of prerequisites, opportunities, and barriers to implementing affinity domains in the Czech healthcare system, and to contextualise these findings in relation to international experiences to inform policy development. Methods: We conducted 18 semi-structured interviews (January–April 2025) with policymakers, regional authorities, providers, insurers, IT vendors, and consultants. Participants were selected through purposive and snowball sampling to capture diverse perspectives. Data were analysed inductively using thematic analysis in MAXQDA24, with dual coding, consensus resolution, and reflexive memos to ensure rigour. Results: Thematic analysis yielded five categories: (A) roles and responsibilities, characterised by ambiguous mandates, regional fragmentation, vendor dominance, and exclusion of clinicians; (B) perceived risks, including institutional distrust from past failures, legal uncertainty regarding liability, technical inconsistency, and vendor lock-in; (C) system-level prerequisites, such as the need for an empowered governance body, sustainable funding, adoption of common standards, and adequate human resources; (D) perceived benefits and opportunities, notably improved continuity of care, reduced diagnostic redundancy, and enhanced accountability; and (E) implementation barriers, including legal ambiguity, political discontinuity, vendor resistance, and limited stakeholder engagement. Stakeholders also emphasised the need for an independent governance body, binding interoperability standards (IHE XDS, HL7 FHIR), and pilot affinity domains with certification mechanisms. Conclusions: To advance affinity domain implementation in Czechia, we recommend establishing an empowered coordinating authority, launching pilot projects with contractual enforcement and audit trails, and aligning national efforts with EHDS requirements (metadata catalogues, access bodies). These steps can reduce duplication, improve continuity of care, and strengthen cross-sectoral trust. Clinical Trial: n/a
Background: Effective leadership among nurses is essential for improving patient outcomes, fostering interprofessional collaboration, and ensuring high-quality healthcare delivery. With the expanding...
Background: Effective leadership among nurses is essential for improving patient outcomes, fostering interprofessional collaboration, and ensuring high-quality healthcare delivery. With the expanding scope of nursing practice, both clinical and administrative leadership have become critical competencies across diverse healthcare settings. Objective: This systematic review aimed to identify and evaluate strategies that promote administrative and clinical leadership among nurses, examining their effectiveness across various professional and geographical contexts. Methods: Following the PRISMA guidelines, a comprehensive literature search was conducted across five databases, PubMed, Scopus, Web of Science, Cochrane Library, and CINAHL. Peer-reviewed studies published between January 2000 and March 2025 were eligible if they employed quantitative or mixed-method designs, focused on registered nurses or nursing students, and assessed interventions targeting leadership development. Studies were screened, appraised using JBI and MMAT tools, and synthesized narratively based on intervention type, leadership domain, and outcomes. Results: Results
3.1 Study Selection Summary
The initial literature search retrieved 2,192 records from five major electronic databases. After removing 978 duplicates, a total of 1,214 titles and abstracts were screened. Of these, 56 full-text articles were assessed for eligibility based on predefined inclusion and exclusion criteria. Following the full-text review, 32 articles were excluded due to reasons such as language (n = 8), inappropriate study design (n = 17), or wrong outcome focus (n = 8). Ultimately, 23 studies met the inclusion criteria and were incorporated into this systematic review. These studies represent diverse geographic settings, research methodologies, and intervention strategies relevant to both clinical and administrative nursing leadership. A PRISMA flow diagram summarizing the study selection process is presented in Figure 1.
3.2 Characteristics of Included Studies
The 23 included studies represented diverse global contexts, with the majority conducted in Asia; including Taiwan, China, Saudi Arabia, Pakistan, and Iran. Additional studies originated from Africa (Egypt, South Africa), North America (Canada), and Europe (Turkey), while several systematic or scoping reviews incorporated multi-country analyses or global data.
A wide range of study designs was represented: 6 randomized controlled trials (RCTs), 8 quasi-experimental studies, 4 cross-sectional or survey-based designs, and 5 systematic or scoping reviews. The sample populations included nursing students, clinical nurses, head nurses, and nurse managers, spanning junior to senior leadership levels. Interventions were evaluated in varied settings such as tertiary teaching hospitals, general hospitals, outpatient centers, and academic institutions.
The majority of studies (20 out of 23) were published after 2018, reflecting current practices and contemporary leadership theories. This diversity enhances the generalizability of findings across healthcare systems, from public to private sectors, and from academic to clinical environments. A detailed account of each study’s methodology, intervention, and outcome measures is available in Appendix B.
3.3 Intervention Types
The interventions implemented across the reviewed studies were varied but broadly grouped into five categories. Most studies employed structured leadership development programs, while others emphasized mentorship, empowerment, relational leadership styles, and emotional intelligence.
Structured leadership development programs formed the backbone of many interventions. For instance, Omer et al. [12], introduced a 16-week competency-based leadership training program at King Abdulaziz Medical City, targeting nurse managers with modules in evidence-based practice, communication, and technology use. Similarly, Ming et al. [13], conducted a multi-tiered intervention in Taiwan that combined classroom instruction, hospital internships, and managerial mentorship for high-performing young nurses. This program led to significant gains in self-reported management function (+1.14, p < .001) and improved team behavior scores. Concurrently, Chang et al. [14], incorporated leadership education into nine core curriculum courses for master's-level nursing students in Taiwan. Their program showed a mean increase of 8.94 points in leadership competence scores (p < .01), underlining the value of curriculum-integrated interventions.
Mentorship and coaching were highlighted in Shen and Tucker’s [15], qualitative exploration of the Midwest Nursing Research Society Leadership Academy. Their study emphasized the effectiveness of structured mentor-mentee pairings in developing leadership confidence, identity, and long-term capability, especially in early-career nurse leaders.
Empowerment-based interventions were also prominent. MacPhee et al. [16] and Dahinten et al. [17] evaluated the Nursing Leadership Institute in Canada, focusing on how leadership training affected leader-empowering behaviors and their influence on staff empowerment and organizational commitment. Both studies used validated scales such as the Conditions for Work Effectiveness Questionnaire-II (CWEQ-II) and found that empowering behaviors were significantly associated with improved staff outcomes and mediated commitment pathways.
Emotional intelligence (EI) and relational training approaches were exemplified by Hamed et al. [18], who implemented a situational leadership and EI development program in Egypt. The study reported remarkable improvements: high EI among head nurses increased from 22.2% pre-intervention to 84.4% post-intervention, while managerial competency rose from 53.3% to 91.1%.
Finally, shared or authentic leadership models were evaluated in several studies linked transformational leadership with enhanced clinical leadership behaviors and fewer adverse patient outcomes via workplace empowerment mechanisms [19 - 22]. Wong and Laschinger [20] demonstrated that authentic leadership significantly enhanced job satisfaction and performance through structural empowerment, while Kim and Han [23] established empowerment as a full mediator between authentic leadership and nursing performance.
3.4 Leadership Domains Targeted
The reviewed interventions both targeted administrative and clinical leadership areas, although differently prioritized according to participant roles and organizational aims. Administrative leadership comprising skills like strategic planning, resource deployment, and coordination of departments featured as a key area of interest in middle and senior nurse manager studies. Aqtash et al. [24], for example, compared self-reported enhanced managerial proficiency after leadership development based on the SQUIRES framework, whereas Omer [12] and Emam et al. [25], prioritized administrative skills like financial management, evidence-based practice, and monitoring performance.
Conversely, clinical leadership featured as the area of concern for interventions on decision-making at the point-of-care level, patient advocacy as well as team coordination. Ming et al. [13], evaluated clinical skills like management function and team behavior in young elite nurses, and Boamah [21], proved the effect of transformational leadership by frontline nurses on clinical performance as well as workplace empowerment. Some of the interventions by Hamed et al. [18] and Mushtaq et al. [26] targeted both areas at the same time through interventions on situational leadership, emotional intelligence, and staff motivation. Generally speaking, the review points toward the variability of the leadership skills required in nursing and emphasizes the benefits of holistic interventions developing both administrative and clinical abilities as part of a single approach.
3.5 Outcome Measures Reported
These studies employed a variety of outcome measurements in the assessment of the effectiveness of leadership interventions. The most frequent measurement employed were self-reported competency and involved elements of leadership knowledge, decision-making self-confidence, emotional intelligence and managerial skill perception. These were generally measured through pre- and post-intervention questionnaires or established tools like the Nurse Manager Competency Instrument (NMCI), as in the case of research by Omer [12] and Hamed et al. [18]. Some studies also set out to measure observed outcomes, usually through feedback from peers or supervisors in a measurement of leadership behavior. In some examples, Ming et al. [13] and Chen [11] used a combined approach of self-assessment and manager-rated team behavior as a measure of participant improvement.
Organizational markers of patient safety climate, burnout, job satisfaction levels, and turnover rates were also reported in several studies. Statistically significant decreases in emotional exhaustion and increases in personal accomplishment were reported by Xie et al. [27] for nurses after a patient safety leadership intervention. Likewise, authentic leadership correlated with enhanced nursing performance and job satisfaction by Kim and Han [23], and empowerment acted as a mediator. Among the most frequently used measurement instruments were the CWEQ-II (Conditions of Work Effectiveness Questionnaire) [11,16,17,20,22,23,24], the Maslach Burnout Inventory (MBI) [19,21], and structured job satisfaction surveys [8]. Seven out of the 23 included studies used validated leadership competence or empowerment scales, enhancing the reliability and comparability of findings across diverse contexts [13,14,12,24,2,8,27].
3.6 Effectiveness of Interventions
The studies reviewed documented general positive effects of leadership interventions in leadership skills, staff motivation, and organizational performance. Leadership skills and knowledge always enhanced upon systematic instruction. Ming et al. [13], for example, noted a statistically significant difference in scores on the management function (Δ = +1.14, p < .001) and long-term improvement in team behavior in high-performing young nurses. Chang et al. [14], also noted an 8.94-point improvement in leadership competency (p < .01) upon integrating modules on leadership in academic courses.
Empowerment manifested as a common thread, and multiple studies indicated it as a mediating or intervening effect of good leadership. Wong and Laschinger [20] and Kim and Han [23] confirmed the construct of authentic leadership as having a positive effect on structural empowerment, which subsequently affects increased job satisfaction and performance. Empowerment also acted as a mediator between leadership development and commitment in research conducted by MacPhee et al. [16] and Dahinten et al. [17], proving important in converting leadership behavior into staff commitment.
At an organizational level, positive changes were noted in patient safety behavior, staff morale, and burnout reduction. Xie et al. [27], found improved leadership behavior in head nurses and reduced emotional exhaustion in clinical nurses from participation in a safety leadership development program. Hamed et al. [18] also identified significant improvement in managerial competency through emotional intelligence training and inferred wider workforce benefits. Critically, some studies showed long-term maintenance of gains. Emam et al. [25] found continued leadership knowledge and self-perceived competency at three-month follow-up after the intervention and Ming et al. [13] showed maintained team behavior change at the same time interval. These results collectively demonstrate lasting effects of leadership development programs when well-designed and embedded in context.
3.7 Ethical Approval
This systematic review did not involve human participants and thus did not require ethical approval. Conclusions: Conclusion
This systematic review set out to evaluate and synthesize the most effective strategies for promoting administrative and clinical leadership among nurses across global healthcare contexts. The review was guided by the recognition that nurses play a dual role, not only as frontline caregivers but also as pivotal organizational leaders tasked with improving patient outcomes, optimizing team dynamics, and ensuring strategic alignment with broader health system goals. As the complexity of healthcare delivery intensifies, so too does the demand for competent, visionary nursing leaders who are adept in both clinical and administrative capacities.
Across the 23 studies included in this review, it is evident that leadership development interventions yield consistently positive outcomes. Structured leadership development programs emerged as the most commonly employed and most effective intervention type. Empowerment models also enhanced leadership performance through psychological and structural empowerment in emerging and established nurse leaders
This review also points out a number of gaps and weaknesses in the existing literature despite these strengths. Most of studies used self-reported outcomes and so were limited by a lack of objectivity in results. Furthermore, few used randomized controlled trials and even fewer used long-term follow-up measurements. These methodological failures highlight a requirement for better research in demonstrating causality and sustainability of leadership development effects.
At the educational and policy levels, curriculum planners should make certain that emotional intelligence-related leadership competencies, communication skills, ethical decision making and strategic planning are infused in undergraduate and postgraduate nursing education. The research agenda must also evolve to support the growing demand for evidence-informed leadership development. Future studies should prioritize the use of RCTs, mixed-methods designs, and longitudinal tracking to assess both immediate and sustained impacts of leadership interventions.
This review reaffirms that effective nursing leadership, both clinical and administrative, is essential to achieving high-quality, safe, and equitable healthcare. Leadership development programs that are theory-driven, context-sensitive, and skill-integrated hold significant promise in cultivating the next generation of nurse leaders. By embedding leadership training into the educational continuum, supporting mentorship and empowerment in practice, and advancing a rigorous research agenda, stakeholders across nursing education, practice, and policy can collectively build resilient, competent, and visionary nursing leadership for the future.
Background: Thyroid dysfunction is a prevalent endocrine disorder that often remains underdiagnosed due to non-specific symptoms and the absence of routine thyroid testing in standard health checkups....
Background: Thyroid dysfunction is a prevalent endocrine disorder that often remains underdiagnosed due to non-specific symptoms and the absence of routine thyroid testing in standard health checkups. Although thyroid hormone assays are the diagnostic standard, routine blood tests may already contain early biochemical signals associated with thyroid imbalance. Leveraging these widely available markers with machine learning can enable earlier, low-cost detection. Objective: This study aims to develop and validate machine learning models to screen thyroid dysfunction using only routine blood test results, without including thyroid-specific hormones such as TSH or FT4. The study also investigates key laboratory predictors that may serve as early indicators of thyroid disorders. Methods: This retrospective study uses de-identified data from the Taipei Medical University Clinical Research Database (TMUCRD). Patients are categorized as hypothyroid, hyperthyroid, or euthyroid based on diagnostic codes, prescriptions, and thyroid hormone results. Thirty-nine routine laboratory features, including liver, kidney, lipid, hematologic, and metabolic markers that are used as predictors. Machine learning algorithms (logistic regression, random forest, and XGBoost) are trained on stratified datasets. Model performance is assessed using AUROC, precision, recall, specificity, and F1-score. Ethical approval was obtained from the Taipei Medical University Joint Institutional Review Board (TMU-JIRB). Results: Model development and validation are ongoing. Preliminary analyses using pilot data indicate that routine blood test features can distinguish thyroid dysfunction with high accuracy (AUROC range 0.85–0.90). Important predictors include hemoglobin, creatinine, and lipid markers. Final model validation and subgroup performance (by sex and age) will be presented in the completed study. Conclusions: This protocol outlines a machine learning–based framework to identify thyroid dysfunction using only routine laboratory data. Early results suggest that non-thyroid-specific biomarkers may provide reliable signals for preliminary screening, enabling broader and cost-effective approaches to thyroid dysfunction detection in primary care settings.
Background: Physical inactivity remains a public health concern with 42% of women and 34% of men in the United Kingdom (UK), for example, failing to meet moderate-to-vigorous physical activity (MVPA)...
Background: Physical inactivity remains a public health concern with 42% of women and 34% of men in the United Kingdom (UK), for example, failing to meet moderate-to-vigorous physical activity (MVPA) guidelines. To promote physical activity (PA) at scale, smartphone-based mobile health software applications (mHealth apps) offer a promising solution. Objective: To evaluate the feasibility of implementing an mHealth app offering very small (‘micro’) financial incentives (FI) for PA in Leeds, UK. Methods: A five-week single-arm proof-of-concept study was conducted with rolling recruitment among Caterpillar Health app users between September 12 and December 12, 2022 (ORBIT model, Phase IIa). Users earned FI in the form of ‘points’, redeemable for consumer rewards (e.g., movie tickets, gym passes), for meeting personalized daily step goals ($0.13 USD per goal achieved; set using data from 5-day baseline) and completing educational quizzes ($0.33 USD per quiz). Descriptive statistics assessed feasibility outcomes (i.e., reach, recruitment, retention, engagement, acceptability) and preliminary effectiveness. Paired-samples t-tests (p<0.05) examined changes in weekly mean daily step count (from baseline) and step goal achievement over five weeks. Results: Of 285 app downloads, 46 users consented to participate (recruitment rate: 16.1%). Participants (mean age: 39.9±11.1 years; 71.1% female) had a baseline step count of 5598±2664 steps/day. Twenty-five remained engaged (i.e., completed at least one quiz) at Study Week 5 (retention rate: 54.3%). Acceptability was high, with 75% of respondents (12/16) indicating they would recommend the app. Weekly mean daily step count did not significantly increase from baseline (mean difference±standard deviation: 317±2273, p=0.533). Weekly daily step goal achievement rate (%) decreased from Study Week 1 to 5 (-23.23±22.85, p=0.024). Conclusions: Despite lower-than-expected recruitment and no statistically significant PA increase, relatively high engagement and acceptability suggest future pilot testing (ORBIT model, Phase IIb) of a refined intervention (e.g., wider selection of loyalty reward partners) and modified study protocol (e.g., simplified consent process) is warranted. Clinical Trial: ClinicalTrials.gov NCT05294692; https://clinicaltrials.gov/study/NCT05294692
Background: Neck pain poses a significant and growing public health challenge, with rising prevalence among younger populations and negative impacts on both quality of life and socioeconomic costs. Cl...
Background: Neck pain poses a significant and growing public health challenge, with rising prevalence among younger populations and negative impacts on both quality of life and socioeconomic costs. Clinical manifestations are diverse, including restricted movement, muscle spasms, headaches, and upper limb numbness. Although drug therapy is widely used, its long-term use is limited by adverse effects. Traditional Chinese Medicine (TCM) exercises offer a promising alternative, but high-quality evidence directly comparing their efficacy and safety to oral medications is currently lacking. Objective: This study aims to compare the efficacy and safety of traditional Chinese medicine exercises and oral medication in treating neck pain. Methods: Relevant RCTs will be identified through a systematic search of multiple databases (including PubMed, EMBASE, Cochrane Library, Web of Science, CNKI, CBM, VIP, and Wanfang) from inception through September 2025. Study quality will be assessed using the Cochrane RoB2 tool, and the overall evidence will be graded via the GRADE approach. For heterogeneity, the I² statistic and Cochran's Q test will be applied. A fixed-effect model is adopted if I² < 50% and P ≥ 0.1; otherwise, subgroup analysis will be performed. Should heterogeneity persist, sensitivity analysis or a random-effects model will be employed, leading to a reduction in the GRADE rating. Results: As of September 2025, 562 studies have undergone preliminary screening. Full-text screening is expected to conclude by December 2025, with data analysis completed in May 2026. The included studies are predominantly from Asia and mostly published after 2010.Outcomes were structured around core indicators: changes in the Visual Analogue Scale (VAS) served as the primary measure, while secondary measures included the Neck Disability Index (NDI), Self-Rating Anxiety Scale (SAS) score, mean vertebral artery blood flow velocity (Vm), and Cobb angle. Combined effect sizes with 95% confidence intervals were calculated for relevant outcomes, and adverse events were systematically summarized. Conclusions: If this study confirms the superiority of traditional Chinese medicine exercise therapy in managing neck pain, it will offer high-level evidence to guide clinical decision-making, support treatment optimization, and promote the standardization of such interventions. These contributions would ultimately improve neck pain prevention and rehabilitation outcomes at the public health level. However, existing studies exhibit several limitations, including insufficient standardization of exercise protocols, challenges in blinding, and notable heterogeneity due to variations in interventions and patients' cultural backgrounds. Moreover, the small number of available randomized controlled trials and their limited geographic distribution constrain the generalizability of current findings. Future high-quality, multicenter studies are needed to refine intervention protocols and expand the evidence base, thereby strengthening the reliability of conclusions in this field. Clinical Trial: CRD 420251156106
Background: Access to health education remains limited for women in underserved regions, particularly in rural Colombia. The Urabá subregion, characterized by high social vulnerability and limited ac...
Background: Access to health education remains limited for women in underserved regions, particularly in rural Colombia. The Urabá subregion, characterized by high social vulnerability and limited access to health and educational services, faces persistent barriers to information on reproductive and maternal health. Objective: To evaluate the usability and user satisfaction of HADA Educación, a mobile application designed to provide digital health education through the Mujer Saludable (Healthy Woman) program for women of reproductive age, during pregnancy, and postpartum. Methods: A prospective observational study was conducted between May and November 2024 among 89 women from the Urabá subregion of Antioquia, Colombia. Participants received tablets preloaded with HADA Educación, which delivered tailored educational content according to each participant’s reproductive stage. Usability was assessed using the System Usability Scale (SUS), and satisfaction was evaluated through a custom Likert-scale survey. Results: Of the 89 participants, 77 completed post-trial surveys. The average SUS score was 82.4, indicating high usability; 44% of users rated the app as excellent and 48% as good. Participants reported strong agreement on ease of use, clarity of content, and confidence in using the app. Overall satisfaction was high, with average ratings above 4.5 out of 5 for content relevance, usefulness, and willingness to recommend the program. The perceived need for prior technical knowledge was low, indicating accessibility across educational levels. Conclusions: HADA Educación demonstrated high usability and user satisfaction among women in a socially vulnerable region, confirming its potential as an accessible digital health education tool. The findings support its broader implementation in low-resource settings to promote women’s health and reduce information and access barriers.
Background: To address care delivery gaps, the healthcare system must embrace innovative digital solutions. Additionally, the rising integration of digitalization as a topic into medical education is...
Background: To address care delivery gaps, the healthcare system must embrace innovative digital solutions. Additionally, the rising integration of digitalization as a topic into medical education is providing students with broader opportunities to engage with digitalization overall. As digital health becomes an increasingly integral component of medical education and healthcare practice, digital affine recent medical graduates constitute a vital resource for advancing digitalization within the healthcare sector. Objective: This study examines how recent medical graduates acquire digital knowledge, apply it across diverse practical contexts – ranging from startups and corporate environments to traditional clinical settings – and how they contribute to the advancement of digitalization within the entire healthcare sector. Methods: Using a qualitative approach, 19 interviews with medical graduates from the last 15 years, educated by a university in Germany with a strong focus on digitalization, were conducted. Subsequently, the interviews were transcribed and analyzed using a deductive-inductive approach, following the qualitative content analysis method by Kuckartz (2012). Results: The findings reveal that medical graduates often acquire digital skills through an intensive self-study and learning on the job, integrating them in various ways into their professional life. Moreover, while graduates recognize their high potential to make on own contribution to the advancement of digitalization, they also face significant barriers such as knowledge gaps, limited resources, and complex regulations, which hinder their ability to contribute to push digitalization in a variety of professional settings. Medical graduates report that they face a pressing need for enhanced knowledge access, improved institutional frameworks, and supportive policy measures to maximize their potential in advancing digitalization initiatives. Conclusions: Recent medical graduates represent an underutilized resource for healthcare digitalization. Unlocking this potential requires coordinated action across medical education, healthcare institutions, and policymaking to create appropriate conditions for graduates to actively drive digitalization.
Background: Personal digital health technologies (DHTs) enable real-time monitoring of physiological metrics and behavioral data, including HRV, supporting early detection of pregnancy-related conditi...
Background: Personal digital health technologies (DHTs) enable real-time monitoring of physiological metrics and behavioral data, including HRV, supporting early detection of pregnancy-related conditions and personalized care throughout the perinatal period. While recent studies demonstrate the utility of personal DHTs in tracking pregnancy-related symptoms, they often rely on aggregate statistical methods that overlook individual variability. Objective: To compare aggregate and individual-level analyses of digital health technology (DHT) data for early detection of pregnancy-related conditions, using the comprehensive BUMP dataset to highlight the importance of individual variability and data heterogeneity. Methods: This BUMP study (Jan 2021 – May 2022) analyzed physiological and behavioral metrics, such as heart rate variability (HRV), sleep, and fatigue, in 256 individuals using Oura rings and self-reported surveys. Individual-level (N-of-1) trajectories were evaluated and compared with aggregate results to uncover personal and collective trends. A statistical method was developed to assess the influence of adverse events and severe symptoms, while case studies explored confounding and modifying factors underlying heterogeneity. Comprehensive statistical analysis included the coefficient of determination, Kolmogorov-Smirnov tests, likelihood ratio tests, and Welch’s t-tests, with inter-individual variability flagged based on high-variability thresholds. Results: Results revealed significant variability in HRV, sleep, and fatigue throughout pregnancy. For instance, only 4.76% of individuals had HRV inflection points at the aggregate week 33 inflection, with a 14.24% coefficient of variation. Our analysis found no significant p-values for demographic or pregnancy complication-based subgrouping, suggesting these factors alone do not drive the observed variability. Case studies further highlighted both intra- and inter-individual differences, emphasizing the importance of considering external factors like adverse events and severe symptoms. Conclusions: Our findings show that aggregate wearable data often fails to generalize across populations, oversimplifying pregnancy-related physiological and subjective changes. This simplification can obscure individual trajectories, leading to generalized insights that may not reflect many pregnant women's experiences. Our results highlight the impact of heterogeneity on pregnancy outcomes, emphasizing the need to move beyond one-size-fits-all models and leverage DHT for personalized care.
Background: Family caregivers of children and youth with neurodevelopmental disabilities report higher levels of stress, anxiety, and depression than other caregivers, yet few evidence-based mental he...
Background: Family caregivers of children and youth with neurodevelopmental disabilities report higher levels of stress, anxiety, and depression than other caregivers, yet few evidence-based mental health services are available to them. Our prior research demonstrated that caregivers benefitted from an in-person group-based Acceptance and Commitment Training (ACT) workshop, which increased their psychological flexibility and improved their mental wellbeing. During the pandemic, we adapted this intervention to be delivered virtually and evaluated its impact on caregivers’ psychological flexibility and mental wellbeing. Objective: The objective of this study was to examine the preliminary effectiveness and acceptability of a virtual adaptation of a group-based ACT intervention across different sites in Canada. Methods: Two hundred and five family caregivers of neurodivergent people or people with disabilities who registered for a virtual, group-based ACT intervention (10-12 hours across 5 or 6 weeks) from one of 27 teams across Canada participated in this research. ACT process (measured via Cognitive Fusion Questionnaire [CFQ], Acceptance and Action Questionnaire [AAQ], Self Compassion Scale - Short Form [SCS-SF] and Valued Living Questionnaire [VLQ]) and mental well-being outcomes (measured through Patient Health Questionnaire [PHQ-4], Parenting Stress Index (PSI-4), Multi-System Model of Resilience Inventory [MSMR-I] and Short Warwick–Edinburgh Mental Wellbeing Scale [SWEMWBS]) were measured before and after the intervention, and again at 8 week follow-up. An acceptability survey was completed post-intervention including items on satisfaction with virtual aspects of the intervention Results: Significant improvements were found for most ACT processes and mental wellbeing measures from pre- to post - intervention and these improvements were maintained (psychological flexibility, values, self-compassion) or continued to improve (cognitive defusion) at follow-up. There was high intervention acceptability related to the virtual format (>80% satisfaction) despite variability in individual preferences. Direct content analysis of participants qualitative survey responses revealed that cognitive defusion, mindfulness and acceptance were the most helpful ACT processes. Conclusions: A virtual, group-based ACT intervention was acceptable and led to positive changes in psychological flexibility and mental wellbeing among family caregivers of people with disabilities or neurodivergent individuals, similar to in-person delivery of the intervention. Further exploration of accessible and sustainable ways to deliver this type of intervention to a diversity caregivers is important. This is an important first step to facilitate the dissemination of such services to the community. Clinical Trial: N/A
Background: Exclusive breastfeeding (EBF) is the optimal feeding practice for infant health, yet rates remain low worldwide, including in Saudi Arabia Objective: This study aimed to identify the modif...
Background: Exclusive breastfeeding (EBF) is the optimal feeding practice for infant health, yet rates remain low worldwide, including in Saudi Arabia Objective: This study aimed to identify the modifiable factors influencing exclusive breastfeeding among mothers in Al-Kharj, Saudi Arabia. Methods: This study aimed to identify the modifiable factors influencing exclusive breastfeeding among mothers in Al-Kharj, Saudi Arabia. Results: The prevalence of EBF was 38%. Strong positive predictors were >3 antenatal visits (AOR 23.8, 95% CI 18–41), previous breastfeeding experience (AOR 16.6, 95% CI 7.0–21.1), colostrum feeding (AOR 7.8, 95% CI 3.8–16.1), husband’s support (AOR 6.4, 95% CI 2.6–15.9), rooming-in (AOR 6.2, 95% CI 2.7–14.4), and antenatal breastfeeding education (AOR 6.1, 95% CI 2.8–13.3). Key barriers included perceived insufficient milk (AOR 0.08, 95% CI 0.05–0.13), delayed initiation beyond three days (AOR 0.11, 95% CI 0.04–0.33), returning to work (AOR 0.15, 95% CI 0.08–0.28), prelacteal fluids (AOR 0.28, 95% CI 0.14–0.56), high income (AOR 0.33, 95% CI 0.10–1.09), late baby holding (AOR 0.35, 95% CI 0.13–0.94), and restrictive traditions (AOR 0.37, 95% CI 0.21–0.65). Conclusions: Modifiable factors such as education, family support, postnatal care, and supportive maternity policies are critical to improve EBF. Findings provide important evidence for policymakers in Saudi Arabia and similar contexts, highlighting the need for healthcare worker training, , early initiation and six months of paid maternity leave.
Background: Electronic Health Records (EHRs) have become foundational in modern health care, offering potential benefits in care coordination, data sharing, and patient safety. However, poor EHR usabi...
Background: Electronic Health Records (EHRs) have become foundational in modern health care, offering potential benefits in care coordination, data sharing, and patient safety. However, poor EHR usability remains a major barrier, contributing to clinician burnout, inefficiencies, and errors. Objective: This scoping review examines the current research landscape on predicting EHR usability, with a focus on theoretical models, usability metrics, and analytic approaches. We identify gaps and opportunities for integrating predictive analytics and artificial intelligence (AI) to advance usability research. Methods: Following Joanna Briggs Institute and PRISMA-ScR guidelines, we systematically searched Medline, Web of Science, IEEE Xplore, and Scopus library databases for studies published between 2009 and 2023. Inclusion criteria focused on empirical research using predictive methods or models related to EHR usability. Data were charted and synthesized thematically. Results: From 2323 screened articles, 47 studies were selected for detailed review (from across 26 countries). Most of these studies focused on EHR adoption and acceptance. The dominant EHR adoption models discussed, namely the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), and the DeLone and McLean Information Systems Success (ISS) Model, were critiqued. Usability predictors such as perceived usefulness (PU) and perceived ease-of-use (PEOU) were prevalent. There were 27 specific usability predictors that were identified. Common predictive analytic approaches were many forms of regression analysis and structured equation modelling (SEM). However, no studies were identified that applied predictive modeling (AI) to dynamically forecast EHR usability beyond cross-sectional surveys. Few studies leveraged AI for usability prediction. Conclusions: The explicit focus in this study on prediction of EHR usability is distinctive in the literature. It extends prior usability reviews (mostly focusing on adoption, not prediction). Predictive modeling for EHR usability remains underdeveloped throughout 2009-2025. Existing frameworks primarily assess adoption intent rather than operational usability over time. The critique of reliance on cross-sectional surveys and lack of task-based objective metrics was identified. Potential bias in the self-reported measures dominate in the EHR adoption model literature with one-time period of post-implementation modelled. Current EHR usability research remains largely survey-based, indicating opportunities to apply predictive modeling. Moreover, in the models there were no feedback loops from output back to inputs to dynamically change the construct determinants of overtime. However, the large volume of predictive techniques shows clear unique effort to utilize many variants of regression and structured equation modelling to establish predictor variables for post-implementation EHR usability. Therefore, to advance the field, future research is needed into the effectiveness of models that quantitatively analyze usability in the form of predictive analytics or categorization.
Background: India faces a complex double burden of malnutrition, with undernutrition, micronutrient deficiencies, and rising overweight and obesity coexisting within populations. Existing national sur...
Background: India faces a complex double burden of malnutrition, with undernutrition, micronutrient deficiencies, and rising overweight and obesity coexisting within populations. Existing national surveys such as NFHS, CNNS, and STEPS provide valuable but episodic data, lacking the frequency, institutional linkage, and life-stage coverage needed for timely preventive action. This gap limits early detection of risk factors and delays interventions, contributing to the rising burden of noncommunicable diseases (NCDs). Continuous, locally responsive surveillance is essential to enable interventions that address both undernutrition and overweight/obesity (“double-duty actions”). Objective: To conceptualize and propose a life-course framework and protocol for institute-based, standardized surveillance of overweight, obesity, and metabolic risk factors in India, leveraging existing national programs and appropriate technologies to inform policy and practice. Methods: This Policy/Framework and Protocol Paper synthesizes evidence from international models (YRBS, NHANES, ECHO, COSI, GSHPPS) and integrates theoretical perspectives including Nutrition Transition Theory, Life-course Perspective, Social Ecological Model, Behaviour Change Communication (BCC) Models, and the Surveillance-as-Action paradigm. The protocol design incorporates principles of Primary Health Care—equity, community participation, intersectoral coordination, and appropriate technology—and practical learnings from the initial implementation of two ICMR-funded projects (NULRISC and COPRIME). Results: The proposed model anchors surveillance in institutions such as Anganwadi centres, schools, colleges, and health facilities, utilizing hybrid tools including OMR paper-based questionnaires, digital dashboards, and IoT-enabled devices. It enables periodic data capture across core domains—anthropometry, diet, biomarkers, and behaviors—while ensuring confidentiality and body-image sensitivity. Integration with RBSK, RKSK, POSHAN 2.0, PM POSHAN, and Ayushman Bharat facilitates real-time, life-stage data convergence and supports actionable feedback for prevention and policy adaptation. Conclusions: An institute-based, standardized surveillance system can transform nutrition monitoring in India from episodic surveys to continuous prevention. By operationalizing double-duty actions and embedding Primary Health Care values, this framework offers a scalable and sustainable public health architecture to address malnutrition in all its forms and inform national policy.
Background: Drug adherence is crucial for chronic disease management, yet treatment discontinuation remains common due to factors such as side effects, inefficacy, or cost. These reasons are often rec...
Background: Drug adherence is crucial for chronic disease management, yet treatment discontinuation remains common due to factors such as side effects, inefficacy, or cost. These reasons are often recorded only in free-text clinical notes, making large-scale analysis difficult. While large language models (LLMs) can interpret such unstructured data more effectively than traditional natural language processing methods, few studies have systematically categorized reasons for discontinuation or identified whether the decision was initiated by the patient or the clinician, especially in low-resource languages like Estonian. Objective: To assess the ability of LLMs to extract and classify reasons for drug discontinuation and identify who initiated it using Estonian electronic health records, and to characterize the observed discontinuation patterns and initiators for statins and antidiabetic medications. Methods: We combined prescription data with free-text anamneses from a 10% sample of the Estonian population (2012–2019). LLMs (Llama-3.1-70B and GPT-4o) were applied to extract discontinuation phrases and reasons, classify them into a clinician-developed taxonomy, and identify who discontinued the treatment. Performance was evaluated on randomly chosen 100 cases per drug group. Results: Extraction yielded 625 antidiabetic drug and 233 statin discontinuation cases. Validation confirmed high accuracy, with 93–98% of extracted phrases and 95–96% of extracted reasons judged correct. Classification of discontinuation reasons achieved weighted F1 scores of 0.808–0.836, while classification of who initiated discontinuation achieved weighted F1 scores of 0.645–0.774.
Adverse reactions were the most frequent reason overall, accounting for ~70% of discontinuations for statins and ~44% for antidiabetic drugs. For antidiabetic drugs, treatment inefficacy and contraindications were more common. Patients more often stopped due to adverse reactions or non-medical reasons, while physicians more often initiated discontinuation for contraindications. Conclusions: LLMs can accurately extract and classify medication discontinuation reasons and initiators from Estonian clinical narratives. Both local and proprietary models performed well, enabling scalable analyses that complement structured health records. This demonstrates the potential of LLMs to unlock information from clinical notes, turning this underutilized EHR component into a valuable resource for monitoring treatment patterns and detecting adverse event signals.
Background: The expansion of digital technologies has transformed the family environment, demanding new strategies from parents to guide and protect their children’s Internet use. While the literatu...
Background: The expansion of digital technologies has transformed the family environment, demanding new strategies from parents to guide and protect their children’s Internet use. While the literature widely discusses parental mediation, few studies analyze how traditional parenting styles are related online parental mediation (OPM) strategies and how parents’ age moderates these relationships. Objective: To examine the effects of three traditional parenting styles—inductive, rigid, and indulgent—on six OPM strategies, considering the moderating role of parents’ age. Methods: A cross-sectional analytical study was conducted with 672 parents (83.9% mothers) of children aged 9–14 years from 29 schools in 10 Spanish regions. Participants completed the Scale of Rules and Demands (ENE-P) and the EU-Global Kids Online Parental Mediation Questionnaire. Using 18 moderation models (PROCESS Model 1, bootstrapping with 5000 samples), we analyzed the predictive power of inductive, rigid, and indulgent parenting styles (predictors) on six OPM strategies—active mediation of Internet use (AMIU), active mediation of Internet safety (AMIS), child-initiated. Results: The inductive parenting style was positively related to all OPM strategies, and its effects were stronger among younger parents for AMIU (B = –.03, p < .01), AMIS (B = –.02, p = .04), and RM (B = –.01, p = .04). The indulgent style showed negative relationships with five OPM strategies (AMIU, AMIS, PM, TC, RM), while the rigid style showed no significant effects. Conclusions: Findings support the concept of global parenting, integrating offline and online parental regulation. Younger parents’ digital skills strengthen the positive effects of inductive parenting on Internet safety and autonomy. Programs should foster inductive strategies and enhance digital competence among older parents.
Background: Young to middle-aged breast cancer patients face significant psychosocial challenges. Existing interventions often lack comprehensiveness, timely initiation, and specific tailoring to this...
Background: Young to middle-aged breast cancer patients face significant psychosocial challenges. Existing interventions often lack comprehensiveness, timely initiation, and specific tailoring to this population's unique needs. Objective: To evaluate the impact of a peer-led, nurse-involved, blended online and offline peer support intervention program (PNO2PSP) on psychosocial adjustment in young to middle-aged breast cancer patients. Methods: The PNO2PSP effectiveness was validated through a single-center cluster randomized controlled trial involving 70 newly diagnosed young to middle-aged breast cancer patients (35 in each group). The intervention group received an 8-week PNO2PSP in addition to routine care. Psychosocial adjustment, self-efficacy, social support, and coping modes were assessed pre-surgery and at 4, 8, and 12 weeks post-surgery. Generalized Estimating Equations (GEE) were used for intention-to-treat analysis. In-depth interviews with 9 participants explored their experiences. Results: Compared to the control group, the intervention group demonstrated significantly lower psychosocial adjustment scores at 4 weeks (T1) (Wald χ² = 6.466, P = 0.011) and 12 weeks (T3) (Wald χ² = 4.395, P = 0.036); Social support was higher at 8 weeks (T2) (Wald χ² = 8.175, P = 0.004). Confrontation coping scores were higher at T3 (Wald χ² = 4.189, P = 0.041), while avoidance coping scores were lower at T1 (Wald χ² = 7.051, P = 0.008), T2 (Wald χ² = 7.346, P = 0.007), and T3 (Wald χ² = 5.062, P = 0.024). Qualitative findings supported these quantitative results, highlighting the program's role in facilitating psychosocial adjustment, providing vital support, boosting treatment confidence, and fostering positive coping. Conclusions: The PNO2PSP effectively enhances psychosocial adjustment, social support, and positive coping in young to middle-aged breast cancer patients. Its scientifically validated, feasible, and patient-centered design supports its recommendation for wider clinical implementation, with continued training for peer supporters and sustained delivery of peer support. Clinical Trial: Registry: Chinese Clinical Trial Registry, TRN: ChiCTR2300076471, Registered 10/10/2023
Background: Soft skills are increasingly valued in the labor market, yet their assessment remains challenging. Traditional approaches (eg, interviews, questionnaires, cognitive tests) often face limit...
Background: Soft skills are increasingly valued in the labor market, yet their assessment remains challenging. Traditional approaches (eg, interviews, questionnaires, cognitive tests) often face limitations related to subjectivity, ecological validity, and bias. Serious games have emerged as promising alternatives by offering immersive environments and behavioral data collection. Objective: This study aimed to evaluate the convergent validity of a serious game (Yuzu) designed for soft skills assessment in human ressources, by comparing three modules assessing active-empathic listening, decision-making under uncertainty, and teamwork dialogue with their respective reference psychometric tools. Methods: A sample of 39 participants completed both the Yuzu modules and their psychometric reference versions: the Active-Empathic Listening Scale (AELS), the Iowa Gambling Task (IGT), and a simplified SYMLOG questionnaire. Statistical analyses included correlation, concordance, equivalence testing, and descriptive comparisons. Results: Strong correlations were found between the Yuzu listening module and the AELS, with high agreement demonstrated through Bland-Altman and concordance analyses. The decision-making module showed statistical equivalence with the IGT, replicating exploration–exploitation dynamics. In contrast, the dialogue-based teamwork module failed to demonstrate convergent validity with the SYMLOG questionnaire due to ceiling effects and social desirability bias. Conclusions: These findings support the potential of gamified assessments to provide ecologically valid and engaging measures of soft skills. Adaptations of standardized tools (AELS, IGT) preserved validity while enhancing participant experience. However, dialogue-based assessments require further refinement through richer branching scenarios and adaptive responses. This study contributes to bridging psychology, ergonomics, and game design and supports continued validation of serious games in professional selection contexts.
Background: Humanism is central to healthcare professionalism but remains poorly defined and inconsistently applied. Amid growing system pressures and dehumanization, this study aims to develop consen...
Background: Humanism is central to healthcare professionalism but remains poorly defined and inconsistently applied. Amid growing system pressures and dehumanization, this study aims to develop consensus-based conceptual and operational definitions of humanism to support education, evaluation, practice, and policy. Objective: This study aims to formulate consensus-based conceptual and operational definitions of humanism in healthcare, based on the combination of theorical perspectives and experience and expertise of clinician-educators, students, and members of the public. Methods: A two-phase mixed-methods design will be implemented to ensure both methodological rigor and analytical depth. Phase I will involve a critical review of the literature, systematically analyzed using content analysis. Concurrently, focus groups will be conducted with learners, clinician educators, and members of the public. The qualitative data generated will undergo thematic analysis to elucidate both theoretical and experiential dimensions of humanism in healthcare. To enhance transparency and epistemological reflexivity, a reflective journal will be maintained throughout the research process. Phase II will employ a modified e-Delphi technique, engaging a panel of interdisciplinary experts in iterative rounds to refine and validate key statements. This approach will reinforce construct validity and facilitate consensus-building. Results: This project is funded by the Research Chair in Compassion Science at the Université de Sherbrooke and supported by the Office of Social Accountability. Scientific evaluation and ethical approval were obtained on May 12, 2025 (Project #2025-4885). As of September 30, the selection of papers for the critical literature review is currently underway, results will be submitted for publication in Winter 2026. Recruitment for the focus groups is scheduled to begin in October 2025. A modified e-Delphi study is planned to begin in Spring 2026, and the results will be submitted for publication in Open Access journals.This project is funded by the Research Chair in Compassion Science at the Université de Sherbrooke and supported by the Office of Social Accountability. Scientific evaluation and ethical approval were obtained on May 12, 2025 (Project #2025-4885). As of September 30, the selection of papers for the critical literature review is currently underway, results will be submitted for publication in Winter 2026. Recruitment for the focus groups is scheduled to begin in October 2025. A modified e-Delphi study is planned to begin in Spring 2026, and the results will be submitted for publication in Open Access journals. Conclusions: This study will produce a validated conceptual and operational definition of humanism in healthcare, grounded in both theory and lived experience. These definitions will support the harmonization of educational practices, the development of assessment tools, and the integration of humanistic values into health policy.
Background: Predictive medicine relies on algorithms to determine clinical treatments tailored to each patient’s individual characteristics. Predictive models based on AI have shown promise in ident...
Background: Predictive medicine relies on algorithms to determine clinical treatments tailored to each patient’s individual characteristics. Predictive models based on AI have shown promise in identifying Atrial Fibrillation (AF) episodes; however, they rarely focus on short-term dynamic prediction. Objective: This study aims to evaluate the use of an AI model and remote monitoring data extracted from pacemaker devices to predict the onset or worsening of arrhythmias in the short term. Methods: This was an observational, prospective, multicenter study in which data from 314 patients were analyzed. A total of 65,243 data sequences were collected, of which 55,532 were used to train the algorithm. This model used 31-day records to predict whether the number of arrhythmic episodes increased, decreased, or remained the same in the following 14 days. Results: The sensitivity and specificity of the generated predictions were calculated from 9,711 prediction/observation pairs. The global sensitivity was 66.4% and specificity was 77.4%; with a sensitivity of 76.8% and specificity of 39.6% in patients with baseline arrhythmia; and a sensitivity of 39% and a specificity of 81% in patients without baseline arrhythmia. The analysis for the patient subgroup without prior history of AF yielded a 69% sensitivity and an 80% specificity. Conclusions: This model was capable of predicting short-term increases or decreases in arrhythmic episodes with reasonable sensitivity and specificity, using data collected through remote monitoring of implantable devices. The model’s performance is expected to improve progressively as more data samples become available, including demographic and clinical records. Clinical Trial: Trial code: IA-Pacing
Spain
Fundación FFDIS in collaboration with Arrhythmia Network Technology SL.
Background: The management of type 2 diabetes mellitus (T2DM) remains a complex clinical challenge, particularly for patients requiring multiple daily insulin injections (MDI). Advances in precision m...
Background: The management of type 2 diabetes mellitus (T2DM) remains a complex clinical challenge, particularly for patients requiring multiple daily insulin injections (MDI). Advances in precision medicine and continuous glucose monitoring (CGM) have created opportunities to personalize treatment and potentially reduce the therapeutic burden on people with T2DM. Assessing beta-cell function and autoimmunity could help identify patients with T2DM eligible for simplified regimens without compromising glycemic control. Objective: The aim of this study was to test a simple personalized medicine protocol in routine clinical practice for people with T2DM treated with MDI. The intervention is based on the evaluation of C-peptide and glutamic acid decarboxylase autoantibody (GADAb) status, with the goal of improving diagnostic accuracy and optimizing treatment. Methods: This is a pragmatic, before-and-after intervention study involving people with T2DM on current MDI across primary care centers and a referral hospital in the Lleida health care region, Catalonia (Spain). Eligible participants will undergo clinical and laboratory assessment, including C-peptide and GADAb testing, and wear a CGM device. Based on a predefined algorithm, patients may either continue or discontinue prandial insulin.
The primary outcome is the proportion of patients in whom prandial insulin is discontinued and remains discontinued over 6 months. Secondary outcomes include changes in glycated haemoglobin (HbA1c), CGM metrics variables, quality of life, adherence, and treatment satisfaction. Results: Recruitment was completed on March 31, 2025. The follow-up phase is ongoing and expected to conclude by September 30, 2025. Data analysis will begin thereafter. Conclusions: This study will evaluate the feasibility and impact of implementing a personalized therapeutic approach for persons with T2DM on MDI in real-world clinical settings. If effective, this strategy could contribute to safer, simpler, and more individualized diabetes care. Clinical Trial: ClinicalTrials.gov NCT06148376; https://clinicaltrials.gov/ct2/show/NCT06148376
Background: Advancements in technologies and increased adoption of wearables and smartphones by individuals have led to an abundance of patient-generated healthcare data. These data, when used effecti...
Background: Advancements in technologies and increased adoption of wearables and smartphones by individuals have led to an abundance of patient-generated healthcare data. These data, when used effectively, could help to further augment the process of shared decision-making to enable patient-centred care. However, the possible integration and utilization of patient-generated health data (PGHD) introduce complexities and challenges which warrant considering both health care professional and patient perspectives. Objective: Summarize the relevant works in the past 10 years from the perspectives of the key stakeholders – healthcare professionals (HCPs) and patients - on potential barriers and enablers to the integration of PGHD for shared decision-making. We analyzed both perspectives to surface key challenges and opportunities with integrating PGHD throughout a patient’s journey and HCP’s clinical workflow. Methods: Electronic searches were done 3 databases: PubMed, ACM Digital Library and IEEE. Enablers and barriers mentioned by the stakeholders in included papers were extracted and analyzed using thematic analysis. The existing six-stage workflow model for integrating patient generated health data was used as a reference for deductive coding. Subsequently, considering barriers and enablers faced by both the HCPs and patients uncovered various tensions and alignments of perspectives which could be addressed in future work and can inform concepts, designs and development in PGHD for shared decision-making. Results: Fifty-three publications were included in the scoping review. Six main overarching themes for barriers and enablers were identified: 1) Patient-Provider Relationship, 2) Patient Characteristics, 3) Organizational Factors, 4) Medical Ethics and Law, 5) Data-driven workflow and 6) Design and Technology. The six-stage workflow was further expanded based on the new findings.to include four additional stages which include contextual considerations outside of traditional clinical environments. In addition to partially corroborating previously established barriers in the six-stage workflow model, several new barriers and enablers were identified throughout all stages. This model helps to further align needs of HCPs and patients beyond the clinical setting and could benefit system designers who plan to integrate PGHD for shared decision making. Conclusions: This scoping review demonstrates that there are several factors to consider for effectively integrating PGHD into health-related SDM. Notably, such factors extend outside the boundaries of traditional clinical settings. Although there is agreement between HCPs and patients on certain factors, there are also tensions to be addressed. Our findings suggest that apart from lifting the barriers to the integration of PGHD, there can be a role for digital health technologies in mediating alignment between HCPs and patients on effectively using PGHD for SDM.
Background: Accurate preoperative prediction of renal tumor malignancy is essential but remains challenging. While radiology and structured electronic health record (EHR) data are widely used for tumo...
Background: Accurate preoperative prediction of renal tumor malignancy is essential but remains challenging. While radiology and structured electronic health record (EHR) data are widely used for tumor evaluation, radiology reports—though rich in diagnostic information, have been relatively underutilized due to extraction challenges. Objective: To enhance malignancy prediction of renal tumors by developing a multimodal pipeline that integrates structured EHR data with information extracted from radiology report text using advanced large language models. Methods: We developed a predictive framework that integrates structured EHR variables with features derived from radiology reports. Large language models (LLMs) were used to extract abnormality characteristics, and a pretrained biomedical transformers (i.e., RadBERT) was applied to generate contextual embeddings from unstructured radiology text. These textual features were fused with structured data using early, middle and late fusion strategies. Model performance was evaluated using standard classification metrics, including accuracy, precision, recall, specificity, area under the ROC curve (AUC) and F1-score. Results: Incorporating RadBERT-derived textual features improved prediction performance, while LLM-extracted abnormality characteristics contributed modest gains. Among fusion strategies, early fusion achieved the highest AUC of 0.818 (± 0.010), and late fusion provided the best F1-score of 0.779 (±0.022), both outperforming unimodal baselines. Conclusions: Our findings demonstrate the value of leveraging unstructured radiology reports through advanced natural language processing (NLP) techniques for malignancy predication. This multimodal fusion approach enhances preoperative renal tumor assessment and has the potential to reduce unnecessary surgeries and improve patient care.
Background: There are multiple sources that document the date of a person’s death in the United States. Unfortunately, this seemingly simple information is either incomplete or costly to obtain. On...
Background: There are multiple sources that document the date of a person’s death in the United States. Unfortunately, this seemingly simple information is either incomplete or costly to obtain. On the other hand, the information of such events is critical for both health systems and clinical studies to assess the outcomes of operational and therapeutic interventions. Objective: As part of a larger assessment of the quality of multi-source death information, we compared the death data from two health systems serving the same region and the Social Security Administration Death Master File(SSADMF). Methods: This study linked death records for patients seen in either health system with the SSADMF from 2007 to 2020 to identify concordant and discordant death data among sources. Analyses included cross-system matching, classification of death records by overlap, and calculation of agreement using Fleiss’ kappa. Results: Among 904,581 matched patients, only 209 deaths were confirmed by all three sources. Large proportions of deaths were uniquely recorded by a single source: 10,697 by Health System A, 1,017 by Health System B, and 3,972 by SSADMF. The Fleiss’ kappa was negative (-0.312), reflecting less agreement than expected by chance. Conclusions: While not generalizable, it is likely that without processes in place to obtain external data regarding patient death, healthcare facility death information should not be relied upon as a complete list of those who have died. The discordances observed highlight the potential for significant gaps in death reporting within healthcare systems, which could impact the accuracy of mortality-based analyses and quality assessments.
Background: Physical therapy, like other sectors of U.S. healthcare, faces increasing documentation burden and growing demand for patient-centered care. AI scribes offer a promising solution by automa...
Background: Physical therapy, like other sectors of U.S. healthcare, faces increasing documentation burden and growing demand for patient-centered care. AI scribes offer a promising solution by automating clinical documentation, but their effectiveness depends heavily on clinicians’ ability to guide these systems through well-designed prompts. Currently, physical therapists lack structured training in this competency. Objective: This Viewpoint introduces and standardizes the SCRIBE Framework, a systematic, six-step approach to prompt engineering, designed to help physical therapists use AI scribes effectively, ethically, and safely. Methods: The framework was developed through synthesis of literature on prompt engineering, healthcare AI adoption, and documentation standards in rehabilitation. It was refined for relevance to clinical workflows in physical therapy and allied health professions. Results: The SCRIBE Framework outlines six practical steps for prompt design: Set the Specialist Role, Clarify Context and Sources, Require Structured Response, Include Clinical Logic, Build in Boundaries, and Establish Voice and Style. Together, these steps enable therapists to create prompts that generate accurate, compliant, and clinically valid documentation. The framework addresses efficiency, ethical risks, and professional communication standards. Conclusions: The integration of AI scribes into physical therapy is inevitable. Prompt engineering represents a new professional competency that shifts therapists from passive users to active conductors of AI documentation. Adoption of the SCRIBE Framework can reduce administrative burden, enhance clinical accuracy, and ensure that AI technologies support patient-centered care in ways that are sustainable and ethically sound.
Background: Many of these systematic reviews have focused on a single modality of TCM for adults with overweight and obesity. Objective: To compare the efficacy of different traditional Chinese medici...
Background: Many of these systematic reviews have focused on a single modality of TCM for adults with overweight and obesity. Objective: To compare the efficacy of different traditional Chinese medicine (TCM) therapies for for adults with overweight and obesity and provide a higher level of evidence in the form of umbrella review of systematic reviews and meta-analysis of randomized controlled trials. Methods: Systematic reviews (SRs) and meta analyses (MAs) of TCM for adults with overweight and obesity will be identified and retrieved in databases of Wanfang, China National Knowledge Infrastructure (CNKI), Chinese Biological Medicine (CBM), PubMed, Embase, and Cochrane Database of Systematic Review (CDSR) from their establishment to March 2025. The included SRs/MAs reported body mass index (BMI), body weight, waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), low-density lipoprotein cholesterol, total cholesterol, triglycerides, fasting plasma glucose, fasting insulin, homeostatic model assessment of insulin resistance, and blood pressure will be extracted independently by two authors. In cases of disagreement, a consensus will be reached by consulting a third author. GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) analysis using the guideline development tool and AMSTAR-2 (A Measure Tool to Assess Systematic Reviews-2) will be used to evaluate the methodological quality of SRs and MAs, respectively. The meta-analysis will be conducted by R studio (metaumbrella packages) under the random-effects model, as well as assessment of heterogeneity, tests for small-study effects, tests for excess statistical significance, and Jackknife leave-one-out analysis. P value <0.05 will be considered statistically significant. Results: No Applicable Conclusions: No Applicable Clinical Trial: PROSPERO (CRD42024551788)
Background: More individuals with HIV are living longer and aging with disability associated with multimorbidity. Community-based exercise (CBE) can prevent and mitigate disability, and improve health...
Background: More individuals with HIV are living longer and aging with disability associated with multimorbidity. Community-based exercise (CBE) can prevent and mitigate disability, and improve health outcomes aging with HIV. However, engagement in exercise can vary. Objective: To describe the fidelity of implementation (FOI) of a six-month online tele-coaching community-based exercise intervention with adults living with HIV from the perspectives of adults with HIV and personal trainers. Methods: We conducted an observational longitudinal study involving a six-month online CBE intervention that included thrice-weekly 60-minute exercise sessions; online biweekly supervised one-on-one exercise sessions with a personal trainer (13 sessions); and online monthly group educational sessions at the YMCA. We assessed fidelity using 1) online structured interviews with participants living with HIV at months 2 and 6 comprised of 20 fidelity items on trainer performance, participant engagement, and exercise experiences; and 2) coaching logs completed by personal trainers after biweekly training sessions (frequency, intensity, time, and type of physical activity during biweekly supervised sessions and self-reported physical activity in the prior week). We considered FOI criteria to be met if ≥80% of the participants living with HIV: 1) attended at least 80% of training sessions (11 of 13 sessions); 2) engaged in thrice weekly exercise the week of the personal training session ≥80% of the time over the six-month intervention as reported by on the coaching logs, 3) reported “complete criteria met” for ≥80% of the fidelity items (≥16 of 20 items) at month 2 and month 6, as reported from the interviews; and 4) engaged in a combination of aerobic, strength, balance, flexibility ≥80% of the time over the six-month intervention as reported in the coaching logs. Results: Twenty-nine of 30 participants (69% male) participated in at least one fidelity interview. FOI was met for one of our four criteria among participants who completed the intervention, specifically Criterion 1 whereby 88% of participants (16/18) attended ≥80% of the 13 coaching sessions. For Criterion 2: 39% of participants (7/18) engaged in thrice weekly exercise in the week of the personal training session at least 80% of the time over the six-month intervention; Criterion 3: At least 80% of participants reported criteria as ‘completely met’ for 14 of 20 items (70%) at month 2 (n=27 participants), and 6 of 20 items (30%) at month 6 (n=18 participants); and Criterion 4: 22% of participants engaged in a combination of all four exercise types ≥80% of the time. Barriers to engagement included scheduling issues, lack of interest, technology problems, and episodic disability. Conclusions: Fidelity of implementation was achieved for supervised components of the CBE intervention, and less with independent exercise. Future research should tailor exercise interventions to personal preferences and abilities to improve engagement. Clinical Trial: NCT05006391
Background: Spinal cord injury (SCI), whether traumatic or nontraumatic, often results in partial or complete motor and/or sensory paralysis, leading to significant physical, psychological, and socioe...
Background: Spinal cord injury (SCI), whether traumatic or nontraumatic, often results in partial or complete motor and/or sensory paralysis, leading to significant physical, psychological, and socioeconomic challenges. In Canada, approximately 86,000 individuals live with SCI, many of whom face barriers to accessing timely rehabilitation services due to geographic, financial, or logistical constraints. These barriers were further amplified during the COVID-19 pandemic. In response, telehealth particularly virtual or tele-rehabilitation has emerged as a viable alternative to in-person care. While prior studies have examined its feasibility, safety, and effectiveness, there remains a gap in understanding the specific intervention characteristics and outcomes used in virtual rehabilitation for individuals with SCI. This scoping review addresses this gap by synthesizing existing literature to inform future practice and research. Objective: To explore the intervention characteristics and outcomes used in virtual rehabilitation for individuals with SCI. Methods: A scoping review following the Joanna Briggs Institute framework. We included articles of (1) adults over 18 years of age who sustained a SCI, (2) examined virtual rehabilitation interventions, and (3) were published in English. Six databases were searched from inception to December 15, 2024. Title/abstract screening, full-text screening, and data extraction were completed independently and in duplicate. A narrative synthesis was completed to summarize findings using the “population, concept, and context” framework. Results: The review included 80 articles examining virtual interventions for individuals with SCI, typically involving exercise training alone or in combination with cognitive-behavioral therapy or educational components. Outcomes assessed ranged from physical performance and functional abilities to psychological wellbeing, quality of life (QOL), feasibility, and usability. Most studies reported that virtual interventions were both feasible and safe to use (77% of studies demonstrated feasibility and 88% of included studies had an adherence rate of 90% or more). Conclusions: This review examined the intervention characteristics and outcomes of virtual rehabilitation for individuals with SCI. Most studies utilized virtual exercise or physical activity interventions along with cognitive behavioural therapy and educational components and demonstrated feasibility, safety, and a positive impact on QOL. Clinical Trial: Open Science Framework Registries (registration DOI: https://doi.org/10.17605/OSF.IO/Q7ZGH)
Background: Wearable devices enabling remote monitoring by surgeons of their patients have gained prominence around total joint arthroplasty (TJA), offering continuous patient data to identify those n...
Background: Wearable devices enabling remote monitoring by surgeons of their patients have gained prominence around total joint arthroplasty (TJA), offering continuous patient data to identify those not meeting postoperative goals, thereby facilitating timely interventions. While multiple studies highlight the utility of these devices in tracking postoperative progress, a standardized approach to their application is lacking. This review aims to synthesize existing literature on the use of wearable device-tracked activity for monitoring TJA outcomes. Objective: We examined the current literature to evaluate how wearable devices are utilized and in monitoring and improving patient rehabilitation and outcomes following TJA. Methods: A systematic review was conducted following Cochrane methodology. A literature search of all available literature was performed in April 2024 and identified 102 studies to undergo full-text review. Systematic reviews, duplicate articles, and theoretical articles were excluded. Ultimately, 35 studies met the selection criteria. Results: The review revealed that 32 out of 35 studies (91.4%) employed wearable devices to monitor step counts. Twenty-one studies (60%) incorporated joint-specific patient-reported outcome measures (PROMs), though the specific measures varied. Nine studies utilized standardized performance-based outcome measures, which also differed across studies. Finally, seven studies (20%) collected sleep data, however the methods and outcomes for sleep measurement were inconsistent among these studies. Conclusions: Remote monitoring via wearable devices offers a novel approach to tracking outcomes in TJA patients. Although the use of these devices in peri-operative care is expanding, significant variability exists in the data reported across studies. Wearable monitoring is often integrated with PROMs and standardized functional assessments, yet the optimal data parameters that best correlate with established outcome metrics remain undefined. Additionally, data collected by wearable has not yet been shown to predict patient recovery or satisfaction. Further research is essential to refine these data parameters and the development of post-operative protocols that leverage wearable devices to enhance patient compliance and improve clinical outcomes.
Background: The global demand for assistive devices (AD), such as prosthetics and orthotics, is increasing. However, a shortage of trained professionals contributes to suboptimal care. To improve clin...
Background: The global demand for assistive devices (AD), such as prosthetics and orthotics, is increasing. However, a shortage of trained professionals contributes to suboptimal care. To improve clinical workflows, the Life Lounge Clinical Workflow (LLCW) has been developed. Understanding user acceptance is essential for ensuring its successful implementation. Objective: This study explored prosthetics and orthotics (P&O) professionals’ perceptions and acceptance of LLCW, as well as the perceived benefits and challenges associated with its use. Methods: A qualitative study was conducted using the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. The study included 18 P&O professionals working at orthotic and prosthetic clinics across Sweden. After an interactive session about LLCW, feedback was collected via questionnaires. Thematic analysis was used to analyze the data. Results: Key factors influencing acceptance included Performance Expectancy, Effort Expectancy, and Facilitating Conditions. Participants rated the platform highly in terms of ease of use (mean = 4.1) and motivation to use (mean = 4.6), suggesting that LLCW was perceived as intuitive and personally valuable. Management encouragement received the highest rating (mean = 4.8), highlighting the importance of organizational support. However, colleagues’ perceptions scored lower (mean = 2.7), indicating limited peer influence. Areas for improvement included greater patient involvement, structured onboarding or training, and more robust technical support. Conclusions: Prosthetics and orthotics professionals reported generally positive experiences with LLCW, particularly regarding usability and performance. However, successful implementation requires integration into existing clinical workflows and attention to training and patient engagement. Addressing these elements can support broader adoption and contribute to digital transformation in P&O care.
Background: Fuzzy logic has increasingly been explored as a flexible alternative to traditional statistical approaches in healthcare modelling, particularly in contexts characterized by ambiguity, com...
Background: Fuzzy logic has increasingly been explored as a flexible alternative to traditional statistical approaches in healthcare modelling, particularly in contexts characterized by ambiguity, complexity, and incomplete information. While widely applied for prediction, classification, and risk stratification, its role in causal inference remains insufficiently examined and often methodologically fragmented. Objective: This systematic review aimed to study the practical use of fuzzy logic frameworks to solve causal questions in healthcare, emphasizing their methodological background, comparative performance, and integration with formal causal inference tools. Methods: A systematic search was conducted in six major databases (PubMed, Web of Science, ScienceDirect, SpringerLink, Scopus, IEEE Xplore) to identify peer-reviewed studies published between 2014 and 2025 that applied fuzzy modelling to healthcare settings with causal objectives. The review adhered to PRISMA 2020 guidelines and used a modified PICO framework to structure eligibility. Data was extracted on modelling strategies, comparator methods, healthcare domains, and alignment with causal frameworks. The risk of bias was independently assessed using adapted versions of the Joanna Briggs Institute (JBI) Checklist and the PROBAST-AI tool. Results: Thirty-seven studies met the inclusion criteria. The most common fuzzy methods were Fuzzy Inference Systems (FIS), Fuzzy Cognitive Maps (FCM), and Neuro-Fuzzy models. Applications spanned infectious diseases, oncology, cardiovascular health, mental health, and occupational health. Of the fourteen studies that included comparator methods, five demonstrated superior predictive performance of fuzzy models compared with conventional statistical or machine learning approaches, three reported broadly comparable results, and nine provided insufficient details for robust comparison. Only two studies (5%) explicitly applied formal causal frameworks, such as fuzzy-set Qualitative Comparative Analysis or DEMATEL+ANP, while six others adopted heuristic causal reasoning without counterfactual structures. Most studies showed moderate to high risk of bias, most frequently due to limited validation, unclear sampling strategies, or inadequate definition of outcomes. Conclusions: Fuzzy logic demonstrates potential for improving causal thinking in healthcare, particularly in scenarios involving high-dimensional data, non-linear interactions, and epistemic uncertainty. Its ability to incorporate expert knowledge and provide interpretable, rule-based outputs align well with the needs of clinical and policy decision-making. However, methodological transparency remains inconsistent, and integration with established causal inference frameworks is rare. Future research should prioritize the development of hybrid models that explicitly link fuzzy logic with counterfactual and graphical causal approaches, adopt standardized reporting practices, and evaluate these models through external validation in real-world healthcare environments. Such efforts are essential to move beyond fragmented applications and establish fuzzy logic as a credible paradigm for causal inference in complex health systems. Clinical Trial: This systematic review was prospectively registered in the PROSPERO database (CRD420251044493)
Background: Traditional brick-and-mortar pulmonary rehabilitation (PR) programs remain substantially underutilized, with only 2.7% of Medicare beneficiaries completing PR within 12 months following a...
Background: Traditional brick-and-mortar pulmonary rehabilitation (PR) programs remain substantially underutilized, with only 2.7% of Medicare beneficiaries completing PR within 12 months following a COPD exacerbation hospitalization. Given the critical role of PR in improving exercise tolerance, quality of life, and reducing readmissions, innovative delivery models are needed to address these this massive utilization gap. Virtual PR platforms have emerged as a potential solution, offering scalable, and home-based rehabilitation Objective: To evaluate the impact of a novel virtual pulmonary rehabilitation program on functional, psychosocial, and cardiometabolic outcomes among adults with COPD. Methods: This retrospective observational study analyzed outcomes among patients enrolled in a structured, multidisciplinary virtual PR program between 2022–2024. Participants completed individualized exercise and education sessions remotely, supported by respiratory therapists and health coaches. Baseline and post-program measures were compared using Cohen’s d to assess effect sizes across clinical domains. Primary outcomes included changes in maximum metabolic equivalents (METs), Duke Activity Status Index (DASI), and Patient Health Questionnaire-9 (PHQ-9) scores. Other measures included changes in blood pressure (systolic and diastolic), smoking status, and prevalence of hypertension. Results: Among 2,444 patients completing the program, the largest effect size improvements were observed in maximum METs achieved, DASI and PHQ9. The program was also associated with decreased smoking rates and a lower prevalence of hypertension post-intervention. Notably, 91% of the studied population self-identified as “fixed income” underscoring the potential for virtual PR to extend access to patients with lower incomes in the US Conclusions: Virtual pulmonary rehabilitation appears to be a promising and potentially more scalable alternative to traditional center-based PR for patients with COPD. Significant improvements in exercise capacity, mood, and cardiovascular parameters suggest clinical benefit, while reductions in smoking and hypertension further highlight potential for broader health impact. Given the high proportion of participants on fixed incomes, virtual PR may represent an effective strategy to expand access and equity in chronic respiratory care delivery across the United States. Clinical Trial: N/A
Background: There is an urgent and critical need to support the mental health of healthcare providers, given high rates of stress and burnout. Although the issues are complex, digital access to inform...
Background: There is an urgent and critical need to support the mental health of healthcare providers, given high rates of stress and burnout. Although the issues are complex, digital access to information and support can help to address the needs since technology can facilitate on-demand links to private, customized resources, including peer support. Beyond Silence is a new mobile app that has been designed by and for healthcare workers to reduce barriers to accessing local resources and peer support. Objective: This study aimed to; 1) explore how healthcare workers across diverse healthcare settings use the Beyond Silence app, and 2) identify opportunities and barriers to implementation Methods: A multiple-case study framework, informed by the Consolidated Framework for Implementation Research was applied to capture four months of implementation across a purposive sample of seven diverse Canadian healthcare organizations. Data included analytics regarding app downloads and use of key features, as well as interview data from baseline and follow-up interviews with organizational champions regarding the implementation process, organizational context, and perceived facilitators and barriers to app use. Results: Approximately 1062 employees downloaded the app over the four-month period, ranging from less than 2% to over 45% of employees across the seven organizations (average of 11.7%). It was opened an average of three times per user, and the most popular feature was viewing content (articles, videos, podcasts). Interviews with 28 organizational champions noted that there was good leadership support for the technology, aligning with their mission to address employee mental health. Barriers to use, however, included the workplace culture around mental health and help-seeking, lack of awareness of when and how to use the app, as well as infrastructure challenges such as limited time and few private spaces to download and use the technology. Conclusions: This study highlights key challenges in implementation of the Beyond Silence peer support app for healthcare workers, including slow adoption linked to mental health stigma, competing demands, and limited frontline engagement. Effective implementation is a precondition for positive outcomes, therefore strategies are needed to optimize technology implementation. Recommendations include: evaluating organizational readiness, building mental health literacy, creating a multi-modal communication and implementation plan, addressing technology requirements (digital literacy and mHealth access), and embedding the technology into organizational policies and practices. Innovative, trust-building strategies are needed to support meaningful uptake and sustained use. Clinical Trial: ClinicalTrials.gov NCT05514093
Background: Meditation has grown in popularity in recent years, but many people who try meditation often fail to establish a habit. Goal setting has been demonstrated to be an effective technique in b...
Background: Meditation has grown in popularity in recent years, but many people who try meditation often fail to establish a habit. Goal setting has been demonstrated to be an effective technique in behavior change in other health related contexts, but is understudied in the meditation context. Objective: This study had two objectives: (1) to assess the effect of goal setting on the number of days people meditated, and (2) to evaluate whether anchoring bias in the goal-setting question (via response-option order) influences goal selection and subsequent meditation behavior. Methods: This large-scale quasi-experimental field study included 18,559 Spotify mobile users aged ≥18 residing in Australia, Canada, New Zealand, the United Kingdom, or the United States who had listened to ≥5 minutes of meditation content from a specified teacher. The in-app experiment consisted of two goal-setting test conditions and an active control. In the test conditions, participants selected the number of days they intended to listen to content from the meditation teacher in the next 7 days. The conditions differed only in the order of goal response options (higher goals listed first vs last). The active control rated how much they liked the teacher, but did not set a goal. Because responding was optional, selection bias is possible and the design is quasi-experimental. Results: The act of setting any goal had a modest positive effect on the number of days people meditated in both Treatment Condition 1 (β = 0.08, 95% CI [0.01, 0.16]) and Treatment Condition 2 (β = 0.08, 95% CI [0.002, 0.15]). People who committed to higher goals were also more likely to meditate more than people who committed to lower goals. Additionally, the distribution of goals between the treatment conditions varied (????22=84.24; P<.001) and the differences in these distributions subsequently yielded differences in the number of days each group meditated, on average (t(2,744.1) = -2.34; P = 0.02; Cohen d =-0.09). Ultimately, placing the highest goal as the first answer choice yielded higher average active days amongst those who chose a goal, but many more people opted out of answering the question itself. Conclusions: Goal setting appears to be an effective tool to encourage people to engage with meditation more frequently on digital platforms and consequently may encourage meditation habit formation. However, anchoring effects play a significant role in people’s willingness to set meditation goals, the goals they set for themselves, and even incremental meditation engagement. The insights from this study are valuable for both theorists who study habit formation, goal setting, and anchoring, as well as meditation app designers and those who are seeking ways to increase engagement with their offerings.
Background: Positive health behaviours can benefit pregnancy, particularly for women diagnosed with gestational diabetes mellitus (GDM). Mobile health (mHealth) applications are increasingly used to s...
Background: Positive health behaviours can benefit pregnancy, particularly for women diagnosed with gestational diabetes mellitus (GDM). Mobile health (mHealth) applications are increasingly used to support behaviour change and improve GDM management. However, the successful adoption of these tools in clinical practice is often influenced by their design, functionality, and perceived usability by healthcare professionals. This study explores healthcare professionals' perspectives on the use of mHealth apps for GDM care, focusing on their usability and feature design. Objective: This study aims to (1) identify the features of mHealth apps currently used in GDM care, (2) evaluate the perceived usability of these apps, and (3) explore the factors influencing their perceived usability. Methods: A cross-sectional online survey was conducted with qualified healthcare professionals (midwives, obstetricians, nurses, dietitians) who used mHealth apps in antenatal gestational diabetes care. The survey (43 items) included demographics, the App Behaviour Change Scale (ABACUS) and the System Usability Scale (SUS), adapted for relevance and piloted for validity. Recruitment occurred via Qualtrics™ (March–May 2025) using social media, professional networks, and snowballing. Data were analysed descriptively and inferentially in SPSS (v29). ABACUS and SUS scores were correlated using Spearman’s rho, with sensitivity analyses for coding decisions and thematic coding of free-text responses. Results: Of 264 survey viewers, 54 healthcare professionals completed full datasets. Most were women (85.5%), midwives or diabetes midwife specialists (54.6%), based in Northern Europe (45.5%), and practising in hospitals (83.6%). Respondents reported using over 30 distinct mHealth apps, most commonly GDm-Health. Apps contained on average 9.9 of 21 behaviour change features, with data recording and feedback most frequent, while behaviour-change elements were less common. Mean usability (SUS) was 70.9/100. A significant negative correlation emerged between ABACUS and SUS scores (ρ = –0.307, p = 0.022), indicating more features were associated with lower perceived usability. Conclusions: Healthcare professionals reported that mHealth apps used for gestational diabetes management predominantly supported robust data management—particularly data recording, evaluation, and clinician–patient communication. While behaviour change and personalised features were recognised as potentially valuable, their addition was often associated with reduced usability, likely due to added complexity. These findings highlight the need for app developers to prioritise high-quality, well-integrated data management while selectively incorporating behaviour change functions that are simple, practical, and aligned with clinical workflows to better support both professionals and women with gestational diabetes. Clinical Trial: not applicable
Background: The improvement of patient experiences formulates essential for medical service enhancement. Our previous practices have revealed that the utility of the comprehensive hospitalizat...
Background: The improvement of patient experiences formulates essential for medical service enhancement. Our previous practices have revealed that the utility of the comprehensive hospitalization guidance via WeChat Applet improve satisfaction and shorten preoperative preparation time for advanced gastric cancer(AGC) patients. However, its efficiency have not yet been verified by randomised trial. Objective: Thus, we conducted this open-label, randomized clinical superiority trial to compare the satisfaction and preoperative preparation efficiency of WeChat Applet gaidance and traditional verbal notification for hospitalization for AGC patients. Methods: This was a superiority, open-label, randomized clinical trial. A total of 152 eligible patients with clinical AGC were enrolled from January 2024 to December 2024. Participants were randomized in a 1:1 ratio after stratification by simple randomization to hospitalization guidance via either WeChat Applet (experimental group, n=76) or traditional verbal notification(control group, n=76). The satisfaction and preoperative preparation efficiency were compared between two groups. Results: The level of anxiety among caregivers handling the admission procedures demonstrated a marked decrease by WeChat Applet of guidance for hospitalization [pre-guidance 5.1±3.5 vs. post-guidance 2.7±2.7, exhibiting a pair difference of 2.368 (95% CI: 1.684 to 3.053), t=6.889, P<0.001]. There was no difference in the anxiety level of caregivers involved in the admission procedure prior to the guidance between the experimental group and the control group [5.1±3.5 vs 4.9±3.0, t=0.398, P=0.691], however, there was a significant difference after guidancing, with the anxiety level in experimental group notably lower than that in control group [2.7±2.7 vs. 4.2±2.9, t=3.254, P=0.001]. The experimental group consistently scored lower on the hospital registration difficulty scale compared to the control group (Z=4.272, P<0.001). The completeness score of the prepared materials upon admission was significantly higher in the experimental group (Z = 6.861, P < 0.001). The experimental group was more likely to express satisfaction with the hospitalization registration process than the control group (Z=8.307, P<0.001). The duration of the preoperative waiting workdays after hospitalization in the experimental group was noticeably reduced compared to the control group [4.3±1.4 vs. 5.2±2.3, t=2.954, P=0.004]; Similarly, the preoperative waiting days after hospitalization [6.4±3.2 vs. 6.4±2.0, t=2.208, P=0.029] in the experimental group were markedly less than those in the control group. Conclusions: The comprehensive hospitalization guidance via WeChat Applet improve satisfaction and shorten preoperative preparation time for AGC patients. This model is worth learning and promoting in more surgical diseases. Clinical Trial: www.medicalresearch.org.cn:MR-44-24-009862
Background: Large language models (LLMs) are increasingly used by the public, including patients, for health information and preliminary medical advice. However, users often interact with these system...
Background: Large language models (LLMs) are increasingly used by the public, including patients, for health information and preliminary medical advice. However, users often interact with these systems through preconceived diagnoses or selectively framed symptom descriptions—a form of cognitive bias that alters the information provided to the model and poses a potential risk to diagnostic reliability in LLM-supported consultations. Objective: To quantify the effect of user cognitive bias on LLM diagnostic performance, assess the effectiveness of prompt-based mitigation strategies and temperature setting, and evaluate a dual-system framework inspired by dual-process cognitive theory. Methods: We developed a simulated patient agent to generate unbiased and confirmation-biased consultations using 1,273 MedQA-USMLE cases. Six LLMs of varying capacities were evaluated through multi-turn dialogues. Diagnostic accuracy was the primary outcome; bias-induced accuracy decline (BIAD, loss in accuracy under bias) and bias-influenced error proportion (BIEP, fraction of errors aligned with user misconceptions) were secondary metrics. Four prompt-based mitigation strategies, four temperature settings, and a dual-system framework—pairing a foundation model (System 1) with a reasoning model (System 2, o1-Mini)—were tested. Results: User cognitive bias significantly reduced diagnostic accuracy by 10–40 percentage points (P < .001), with smaller models occasionally performing near chance. Errors frequently reflected user misconceptions (BIEP > 33%). Prompt and temperature adjustments yielded limited or inconsistent improvement, whereas the dual-system framework increased accuracy by 10–39 points and recovered most or all of the performance lost under bias (P < .001). Conclusions: User cognitive bias represents a new behavioral dimension of risk in LLM-supported healthcare. Quick fixes such as prompt engineering or temperature control offer limited resilience. Integrating a dual-system reasoning framework provides a scalable path toward safer and more bias-aware medical AI.
Background: Tuberculosis (TB) remains a major global health challenge, particularly in low- and middle-income countries, where effective triage, diagnosis, and management are often limited. Existing d...
Background: Tuberculosis (TB) remains a major global health challenge, particularly in low- and middle-income countries, where effective triage, diagnosis, and management are often limited. Existing decision-support tools focus on imaging and cannot integrate multi-modal clinical information, constraining their utility in complex clinical scenarios. Large Language Models (LLMs) have shown promise in assisting diagnosis and clinical decision-making in other medical fields, but evidence for their application in TB care is scarce. Evaluating LLMs for TB decision support is crucial to explore their potential to improve clinical accuracy, efficiency, and quality of care in high-burden, resource-limited settings. Objective: To evaluate whether large language models (LLMs) can assist tuberculosis (TB) physicians in clinical decision-making across triage, differential diagnosis, and management recommendation tasks, addressing potential delays and inequities in TB care. Methods: In this experimental comparative study conducted in 2025 under STARD guidelines, 17 standardized TB cases (7 simulated, 10 real) were assessed. Responses were generated by two advanced LLMs (ChatGPT-4o and DeepSeek-R1) and two TB physicians. Reference standards were established by three TB specialists. Objective performance was measured using precision, recall, and F1 scores. Subjective evaluation assessed suitability, information quality, and, for management tasks, safety, conciseness, understandability, and operability using 5-point Likert scales. Readability was measured by a Chinese R-value; group differences were analyzed using Mann-Whitney U tests. Results: LLMs achieved precision similar to physicians across all tasks (median 0.67 vs 0.50; U = 8695.5; P = .35) but higher recall (0.53 vs 0.33; U = 6848.5; P < .001) and F1 scores (0.58 vs 0.33; U = 7085.5; P < .001) in management recommendation tasks. In management tasks, LLMs outperformed physicians in recall (0.50 vs 0.20; U = 185.0; P < .001) and F1 (0.50 vs 0.30; U = 104.0; P < .001), with no difference in precision. Subjectively, LLMs scored higher in suitability (3.67 vs 3.00; U = 1122.0; P < .001), information quality (3.33 vs 2.67; U = 155.0; P < .001), understandability (3.67 vs 3.00; U = 4281.5; P = .022), and operability (3.67 vs 3.00; U = 4305.0; P = .025). No differences were observed in conciseness (P = .54) or safety (P = .06). Physicians’ responses were more readable (1.88 vs 2.17; U = 11427.5; P < .001). Conclusions: LLMs can serve as adjuncts to support TB clinical decision-making, enhancing management recommendations without replacing physicians. Their use may improve decision efficiency and help reduce disparities in TB care. Clinical Trial: This experimental comparative study evaluating large language models versus tuberculosis physicians did not involve patient interventions or randomization, and therefore was not registered as a clinical trial.
Background: Harmful Internet Use (HIU) represents a growing concern, particularly among children and adolescents. While existing classifications such as Internet Gaming Disorder in the DSM-5 and Gamin...
Background: Harmful Internet Use (HIU) represents a growing concern, particularly among children and adolescents. While existing classifications such as Internet Gaming Disorder in the DSM-5 and Gaming Disorder in the ICD-11 address specific internet-related behaviors, they fail to encompass the full spectrum of adverse consequences - including social withdrawal, impaired personal hygiene, and emotional dysregulation. Moreover, the tools commonly used to assess HIU, such as self-assessments or parental evaluations, lack reliability. Objective: This study introduces a novel approach inspired by Janusz Korczak’s educational philosophy, emphasizing the role of children as active participants in evaluating others within their age-proximal social group. The goal was to evaluate whether peer-based assessments yield more accurate insights into the prevalence and impact of HIU. Methods: A total of 104 Polish children evaluated 1038 children and adolescents using a 9-item rating scale. Items were scored on an ordinal scale ranging from 0 to 3, with intermediate values (0.5, 1.5, 2.5) permitted. Statistical analyses included frequency distributions to describe response patterns, Spearman’s rank correlations, and receiver operating characteristic (ROC) analyses of summed scores (Q1–Q7) against severity ratings (Q8). Results: Approximately two-thirds of peer-reported evaluations indicated awareness of HIU, and over 60% rated the severity as moderate or high. Functional impacts such as social withdrawal and poorer school performance were commonly observed. All items were positively correlated, with Q8 strongly linked to Q2 and Q7. ROC analyses showed good discrimination between the lowest ratings (0/0.5) and the highest rating (3), while adjacent categories were more difficult to distinguish. SEM suggested that awareness and avoidance Peer assessment is a promising and more objective method for identifying HIU in youth populations. Given the increasing role of digital technology in children's lives, there is an urgent need for schools and mental health systems to adopt innovative tools that include participatory evaluation models rooted in respect and dialogue, as advocated by Korczak. of other activities predicted attempts to reduce HIU, while preference for HIU over socializing reduced them. Conclusions: Peer assessment is a promising and more objective method for identifying HIU in youth populations. Given the increasing role of digital technology in children's lives, there is an urgent need for schools and mental health systems to adopt innovative tools that include participatory evaluation models rooted in respect and dialogue, as advocated by Korczak.
Background: Sudden Unexpected Infant Death (SUID) is a leading cause of postneonatal death in the United States. Following recommended infant care practices such as safe sleep and breastfeeding reduce...
Background: Sudden Unexpected Infant Death (SUID) is a leading cause of postneonatal death in the United States. Following recommended infant care practices such as safe sleep and breastfeeding reduce the risk of SUID. Parents use social media to help them make decisions about infant care practices. Objective: The objective of our qualitative study was to explore mothers’ perspectives about the acceptability of Facebook Private Groups (FBPGs) for providing education on infant care practices. Methods: We conducted a descriptive qualitative study recruiting a purposeful sample of pregnant persons and mothers who recently gave birth who were clients of the Special Supplemental Nutrition Program for Women Infants and Children (WIC) in 2 states. We conducted in-depth interviews which were analyzed inductively through a systematic, iterative process using an interview guide. We asked participants about their perspectives regarding use of FBPGs for learning about infant care practices, including sleep practices and breastfeeding. Data were collected until data sufficiency was reached. Results: Of the 22 participants, 59.1% were WIC clients from Rhode Island and 40.9% from Virginia. While the use by participants of Facebook in general varied, all either used, or liked the idea of using specifically FBPGs to disseminate infant care practices guidance about safe sleep and breastfeeding to pregnant persons and new parents. Participants reported using FBPGs for 3 main purposes: 1) information seeking, 2) the experience of engaging in FBPGs, and 3) social connectedness. Conclusions: The use of FBPGs was endorsed by the participants for providing mothers with information about infant care practices. Participants outlined their reasons for and experience with the use of FBPGs that can inform effective use of the platform for educational interventions. Clinical Trial: Not applicable
Background: The global elderly population is growing rapidly, posing significant social and economic challenges. In China, the one-child policy has exacerbated elder care difficulties, increasing reli...
Background: The global elderly population is growing rapidly, posing significant social and economic challenges. In China, the one-child policy has exacerbated elder care difficulties, increasing reliance on institutional care. However, transitioning to elderly centers (ECs) often induces stress (Wang et al., 2021; Weaver et al., 2020; Wu & Rong, 2020), reduces psychological well-being (PWB) and can cause physical symptoms like insomnia and appetite loss (Levina et al., 2019), which lead to worsen health (Koppitz et al., 2017). In China, where historically home based care, relocation to ECs can heighten feelings of neglect and embarrassment (Wu & Rong, 2020), further compromising PWB.
Inadaptation in older adults is more likely to occur in the first year of entry to ECs, as they face the loss of familiar surroundings and must adapt to a new environment (Sun et al., 2021). These phenomena may be of heightened concern in Chinese culture, where traditional values of filial piety emphasis children caring for their elderly parents. The admission to ECs for older adults may lead to feelings of abandonment and shame. Consequently, a decline in PWB is more common among new residents, especially in the Chinese context (Qi et al., 2023; Yao et al., 2020). Therefore, researching ways to improve the PWB of new residents is highly meaningful.
Recent studies explore behavioral interventions, such as happiness therapy (Cantarella et al., 2017; Greenawalt et al., 2019), life review therapy (Lai et al., 2019; Viguer et al., 2017), cognitive behavioral therapy (Browne et al., 2017; Durgante & Dell’Aglio, 2019; Durgante et al., 2022) to improve PWB. A limitation of these interventions is that they are often perceived as uninteresting, which may promote disengagement among older adults (Rebok et al., 2014). Additionally, many interventions primarily target younger adult populations, further limiting their applicability (Aborass et al., 2025; Beraldo, 2025; Brown & Peter, 2025; Nci & Salam, 2025). Another significant drawback is that these studies often rely solely on subjective data, lacking support from objective measurements, which may affect the validity and reliability of the findings (Chen et al., 2019; Cheng et al., 2022; Li, 2021; Li, 2020). Therefore, it is essential to develop practical, effective, and easily accepted interventions specifically designed to improve PWB among older adults, while incorporating both subjective and objective data to ensure more robust and comprehensive results.
Art activities and group-based interventions are widely recognized as effective methods for enhancing PWB (Wang & Wang, 2022). Some studies (KÖSe et al., 2024; Nie & Tsai, 2025; Oinas & Huhmarniemi, 2024; Zhenli et al., 2024) have incorporated group discussions or supplementary activities into art-based interventions to improve outcomes. While the combined intervention has potentially shown some effectiveness, this benefit comes with the drawback of a longer duration, which may inadvertently introduce negative effects like participant fatigue or reduced adherence (Northey et al., 2018). Therefore, it is critical to examine whether art activities alone or in combination with group discussions are more effective in boosting PWB among new elderly residents in Chinese elderly care centers.
Conceptual framework
The study is based on aesthetic theory and social support theory (Bavik et al., 2020; Brain, Beauty, and Art: Essays Bringing Neuroaesthetics into Focus, 2021; Wright), drawing from literature regarding the transfer of older adults to elderly care facilities. The Chinese art activity program was developed to include culturally significant aesthetic practices, whilst the peer Group Participation intervention was modified from evidence-based group support models. Outcome measures encompass psychological well-being, happiness, relaxation, loneliness, and salivary cortisol levels.
Aesthetic theory underscores the significance of aesthetic experience in enhancing wellbeing via emotional and sensory reactions to art (Ivanov, 2023; Reiter & Geiger, 2023). Interaction with beauty is correlated with favorable emotional states, which neuroscience links to the release of neurotransmitters such as endorphins and serotonin, as well as a decrease in stress-related indicators, including cortisol (Brillenburg Wurth, 2023; Marino, 2023; Minhoto & Amato, 2023; Movlonova, 2023). The Chinese Art Activity intervention utilizes these pathways through culturally customized art engagement designed to elicit delight and confer physiological advantages.
The social support theory emphasizes that interpersonal interactions mitigate stress and improve wellbeing by providing emotional, informational, and companionship support (Kort-Butler, 2018). The peer Group Participation intervention aims to reduce isolation and enhance self-efficacy through group cohesion and shared experiences (Bavik et al., 2020; Drageset, 2021; Haugan & Eriksson, 2021; Ngai et al., 2021), notions that coincide with Yalom's therapeutic group elements (Yalom, 2010).. The theory suggests that the art-based intervention yields neurophysiological advantages, while the peer group element offers social relational support (Aydın & Kutlu, 2021; Bradfield, 2021; Iwano et al., 2022). Collectively, they constitute a multifaceted strategy for improving psychological wellness in older persons during transitional phases. The concept structure of this study is shown as follows (Figure 1):
Fig1: Objective: This study aims to evaluate the effects of Chinese art activities (CAA), both independently and in conjunction with Peer Group Participation (CAA+PGP), on the psychological well-being of newly old Chinese at ECs. The primary objectives are:
(1) to investigate if participation in CAA significantly improves psychological well-being (PWB), happiness, relaxation, and reduces loneliness and salivary cortisol levels; (2) to examine if the combined CAA+PGP intervention significantly enhances PWB;
(3) to assess if the combined CAA+PGP intervention produces superior outcomes compared to CAA alone; and
(4) to evaluate the efficacy of salivary cortisol as a physiological biomarker reflecting changes in PWB. Methods: Feasibility Study
Before the initiation of the full-scale RCT, a feasibility study was undertaken. This study was performed at a senior facility in Suzhou, China, separate from the primary study sites to enhance the intervention protocols. Twenty qualified older adults were recruited: ten underwent the CAA intervention, while the remaining ten engaged in the CAA+PGP intervention. Insights and evaluations from the pilot phase were utilized to enhance the intervention protocols. The revised protocol obtained official approval before its implementation in the primary study.
Trial design
This multicenter, randomized, assessor-blind trial, structured according to the Max.-Min.-Con. principle, has three parallel intervention groups: Group A (+CAA), Group B (+CAA+PGP), and Group C (regular care), with a 1:1:1 allocation ratio. The research is executed consecutively at three elderly residential residents. centers in Suzhou, China, with each site functioning as a randomization unit. Figure 2 delineates the implementation phase of the data collection techniques in the study. The intervention occurs over three sessions within a single week (Monday, Wednesday, Friday). Baseline evaluations of psychological well-being, loneliness, happiness, relaxation, and salivary cortisol levels are conducted before randomization. Outcome measures will be gathered 30 minutes prior to and following each intervention session to assess immediate effects. A concluding follow-up assessment occurs one week after the final session to examine enduring outcomes. Figure 3 illustrates research design within a single environment. The study protocol complies with the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) checklist (Table 1). The projected study duration is from May 9, 2025, to May 30, 2026.
Participants
Eligible participants were aged 60 to 85 years, residing in an elderly center (EC)e with a duration of stay not exceeding one year (Sun et al., 2020), and demonstrating normal cognitive function defined as a Mini-Mental State Examination (MMSE) score above 24 (Bourdon & Belmin, 2021). Additionally, participants were required to possess adequate literacy skills for basic reading and writing (Lan et al., 2019) and provide voluntary informed consent. Exclusion criteria encompassed severe medical conditions such as heart failure, asthma, cerebrovascular disease, or advanced malignancies, as well as planned or actual discharge from the facility during the study period.
Figure 2. The Implementation Phase and the Data Collection Procedures
Figure 3. CONSORT flow diagram.
Table 1 SPIRIT standard protocol items with time schedule of enrolment, interventions and assessments
×*, This includes pre-test and post-test assessment
Sample size
The sample size of this randomized controlled trial study is calculated based on previous study. The effect size use formula d=(µ1-µ2)/σ (Cohen, 2013).
Where d= effect size
µ1= Mean of intervention group
µ2= Mean of control group
σ=√("SD" 1^2+"SD" 2^2 )/2
Based on a previous study (Piasai et al., 2018), the effect sizes for happiness and relaxation were calculated by the formula as 2.65 and 2.31, respectively. In another randomized controlled trial (Aydın & Kutlu, 2021), the effect size for loneliness was found to be 0.92. To calculate the required sample size, loneliness was selected as the reference due to its lowest effect size. Using a power chart (Lipsey, 1990), the sample size was determined based on an effect size of 0.92, a power of 0.80, and an alpha level of 0.05. The analysis indicated that a minimum of 25 participants per group would be required. This study will recruit 90 individuals to account for a potential dropout rate of 20%. The trial is scheduled at three independent institutions, each having three experimental groups with ten participants per group.
Participant Enrollment
Upon receiving formal authorization from the management of the ECs, the nursing director will act as the principal gatekeeper, enabling researcher access to the facility and aiding in the recruitment of prospective participants. Eligible participants will be determined by examining health records and the Mini-Mental State Examination (MMSE) in accordance with the inclusion criteria. Individuals who satisfy the requirements will be invited to participate and provided with a written information sheet detailing the study's aim, procedures, advantages, and their right to leave without repercussions. Written informed consent will be requested prior to enrollment. For group allocation, participants will obtain a group-specific information sheet and sign a corresponding consent form.
Participant allocation
The allocation sequence will be produced dynamically by an independent statistician throughout the recruiting phase utilizing the Minimization Randomization Program Version 2.01. This procedure will employ data on age and visit frequency for one month (refer to Table 2) from registered participants to guarantee equitable baseline characteristics among all groups. Age data will be gathered during the collection of participants' demographic information. Each institution will record visitors, enabling the verification of the older adults’ visitation frequency throughout one month through the institution's visitor registration data. The monthly visit count should remain variable; therefore, we will compute the average monthly visits for older adults since their relocation, without surpassing one year.
Table 2. The categories of confounding variables for using minimized randomization program
Confounding variables Category 1 Category 2
Age 60-75 over 75
One-month visitation frequency 1-2 times per month more or equal 3 times per month
The researcher will recruit thirty participants from each institution, resulting in a total of ninety older people (aged 60–85, new residents with ≤1 year of residency), introduced by through health providers. In each institution, the 30 participants will be allocated into three groups—A, B, and C—comprising 10 participants each group. Group A will be administered +CAA, Group B will be administered +CAA+PGP, and Group C will receive routine care.
Blinding
A double-blind design will be impractical due to the characteristics of the art-based intervention with the exception of outcome assessors and data analysts will remain blinded to guarantee an objective review. Research assistants responsible for pre- and post-intervention data collection will remain uninformed of group assignments and will not engage in the delivery of the intervention. Unblinded study personnel will manage randomization and intervention delivery but will be excluded from data collection tasks. Data analysts will obtain solely anonymized participant codes, devoid of any information regarding group allocation. All blinded staff are will not be able to obtain information on group assignments.
Intervention
Chinese Art Activities (CAA)
A systematic, structured protocol guides will be followed for the implementation of the Chinese art intervention at all research settings (Ciasca et al., 2018; Huang et al., 2022; Tong et al., 2021). The program will begin with a 10-minute instructional introduction presented through a pre-prepared PowerPoint exhibited on a wide screen. These sessions will focus on the historical development, philosophical underpinnings, and essential brush-and-ink techniques of traditional Chinese landscape painting and calligraphy. Exemplary artworks will be displayed on the screen throughout the relevant instructional segment to demonstrate aesthetic principles and improve participants' visual literacy. A three-minute instructional movie will subsequently be screened. iPad will be supplied and positioned on the desks of older participants who indicate difficulties with clearly reading the screen. The movie will systematically illustrate the formation of a meticulously chosen landscape scene, utilizing novice-friendly brush techniques and color modification methods. Participants will thereafter be allocated 25 minutes to reproduce or modify the exemplar on xuan paper (rice paper) utilizing traditional implements (wolf-hair brush, pine-soot ink, mineral pigments). Personalization by color variation or the incorporation of supplementary natural elements (e.g., bird patterns, floral designs) will be deliberately promoted to enhance individual creative expression. The ensuing calligraphic element will necessitate those participants create a brief lyric or aphorism thematically congruent with their completed image. After initial drafting on practice sheets, the final text will be inscribed in calligraphy onto the artwork within a 15-minute timeframe, thus merging poetry inscription with visual imagery in line with classical Chinese creative traditions. A detailed summary of the interventional strategy for CAA is provided in Table 3.
Table3. The Details of CAA Program
Activities appliance procedure Time (minutes)
Traditional Chinese landscape painting and calligraphy pens, ink, paper, inkstones, pigments Preliminary understanding and familiarity 10
Creation of Traditional Chinese Landscape Painting 25
Chinese Calligraphy Creation 15
CAA combined with Peer Group Participation (PGP) Intervention Program
The CAA+PGP intervention, supported by previous studies (Aydın & Kutlu, 2021; Hermann, 2021), consists of an 80-minute integrated session led by a single researcher (RA1). Based on established recommendations that at least four participants are necessary for effective group interventions (Levine, 1979), the 10 participants in this arm will be randomly divided into two groups of five, each facilitated by one trained peer volunteer, resulting in six individuals per group including the peer volunteer.
The intervention commences with the CAA (Chinese Art Intervention) segment, which will be executed in accordance with the established CAA protocol. After the art creation phase, the PGP (Peer-Guided Sharing) phase will be continued. Volunteers will organize the exhibition of artworks and promote reciprocal appreciation by facilitating group conversation in accordance with established protocols. The group's active involvement and accomplishments will initially be officially recognized, followed by an invitation for each member to sequentially articulate the positive significance of their artwork. Participants will then be encouraged to give their artwork as gifts, accompanied by gestures of mutual appreciation, such as handshakes or embraces. Ultimately, peer volunteers will conclude the program by sharing personal stories highlighting adaptation to life at the elderly center. Table 4 contains information pertaining to the CAA+PGP interventional procedures.
Table 4. Details of CAA + PGP Program
Activities appliance procedure Time (minutes)
Traditional Chinese landscape painting and calligraphy and peer group participant pens, ink, paper, inkstones, pigments Preliminary understanding and familiarity 10
Creation of Traditional Chinese Landscape Painting 25
Chinese Calligraphy Creation 15
Display and appreciate art works 5
Discuss ongoing art activities 25
End intervention
Routine care
Both the intervention and control groups in all 3 settings will get the same routine care, which includes daily activities such as basic limb exercises being specified activity hours from 8:30 am to 10:30 am and 2:00 pm to 4:00 pm each day. The interventions for CAA and CAA+PGP are planned from 2:00 pm to 4:00 pm, during which the experimental groups will engage in intervention activities, while the control group will adhere to the original activity schedule of the elderly center. All other everyday management and activities for the three groups will continue as normal.
Outcomes
This research used a repeated-measures design. In addition to the measurements obtained concurrently with the PWB assessment at baseline and one-week post-intervention, further pre- and post-intervention evaluations will be performed for happiness, relaxation, loneliness scores, and salivary cortisol levels. The schedule of evaluations is outlined in Table 1
The PWB score will be assessed using the 18-item, Chinese version of Ryff’s PWB scale (Li, 2014). This scale consists of 18 questions, with 3 questions per dimension, covering a total of six dimensions: Self-Acceptance, Positive Relations with Others, Autonomy, Environmental Mastery, Purpose in Life, Personal Growth. Happiness score, Relaxation score, Loneliness score will be measured by specific 10 cm VASs. After a decision is made, the record value will be measured in millimeters (from left to right) using a ruler to assign a numerical value to the subjective evaluation, possible scores ranged from 0 to 10.
Thirty minutes prior to and following the intervention, the saliva will be collected. A saliva tampon collecting tube will be used to gather saliva. After collecting the saliva samples will be put on wet ice right away, brought to the lab within three hours, and frozen below -80°C. Following the collection of all the samples, measurements will be requested from the laboratory's qualified personnel. The Jiangsu Provincial Department of Science and Technology has accredited the lab, which possesses significant proficiency in measuring salivary cortisol levels.
Statistical methods
This study will utilize computer-based data analysis with the following statistical procedures. Dependent variables include PWB score, loneliness, happiness, relaxation, and salivary cortisol levels, compared at pretest and posttest across intervention groups (CAA, CAA+PGP) and the control group (routine care), with the independent variable being the type of intervention. Preliminary data analysis will assess normality and homogeneity of variance assumptions using histograms, skewness, and kurtosis, while descriptive statistics will identify missing values, out-of-range data, and accuracy. Demographic and characteristic data will be summarized, with normality tests determining data distribution. Normally distributed data will be presented as mean ± standard deviation for visual scale values and salivary cortisol levels, while non-normal data will be reported as median (interquartile range). Inferential statistics will employ repeated measures ANOVA and paired t-tests for normally distributed data to compare group differences and pre-post intervention changes, respectively. For non-normal data, non-parametric tests (Friedman test, Wilcoxon signed-rank test, and Mann-Whitney U test) will be used for group comparisons and pre-post intervention analysis.
Ethical Considerations
This study protocol has been reviewed and approved by the Institutional Review Board of Prince of Songkhla University (Approval No: PSU IRB 2024-St-Nur 048). The trial is registered at ClinicalTrials.gov (NCT06841133). Any modifications to the protocol will be promptly submitted to the IRB for review and approval.
Before participation, all eligible individuals will receive detailed information regarding the study objectives, procedures, potential risks, and benefits. Written informed consent will be obtained from each participant after thing been provided with full explanation of the study requirements. For participants with visual or literacy challenges, the consent form will be read aloud verbatim by trained research assistant and obtaining written signature. To ensure confidentiality, all collected data will be deidentified using unique participant codes. Electronic data will be stored on encrypted, password-protected servers, and physical documents will be kept in locked cabinets accessible only to authorized investigators. Biological specimens (saliva samples) will be processed for cortisol analysis immediately after collection and destroyed thereafter to prevent unauthorized use or retention. All research personnel have completed training in ethical data handling and participant privacy protection according to international standards (Association, 2013).
In this study, the experimental group will receive supplemental entertainment activities as interventions alongside routine activities, while the control group will receive only routine activities. Post-trial, the control group will be offered the same interventions if interested, without follow-up requirements. Results: The experiment was funded in September 2024. The study protocol received approval from the Institutional Review Board of Prince of Songkhla University (Approval No: PSU IRB 2024-St-Nur 048). The initial participant was enrolled on May 9, 2025, and by August 20, 2025, a cumulative total of 90 participants has been recruited. Data collection will continue until October 2025. The data analysis has not commenced, and the results are anticipated to be released in late 2025.
Discussion
Summary
The globally aging phenomenon, along with China's one-child policy, has markedly heightened dependence on institutional elder care. However, shifting to geriatric facilities frequently diminishes psychological well-being (PWB) owing to stress and cultural shame. Current studies on therapies, including well-being therapy and cognitive-behavioral therapy, are frequently hindered by inadequate participant involvement, excessive dependence on professional guidance, and undue focus on subjective data, which collectively diminish their overall effectiveness (Durgante et al., 2022; Tam, 2021).
Art activities and group-based interventions are recognized for their capacity to improve PWB. Nonetheless, the amalgamation of various methodologies, although potentially more efficacious, frequently extends the period of intervention, so augmenting the burden and tiredness experienced by older adults and eliciting ethical dilemmas. Consequently, it is imperative to examine whether art activities alone or in conjunction with group talks are more efficacious in enhancing psychological well-being among newly elderly residents in Chinese residential facilities.
The study seeks to enhance psychological well-being by integrating traditional Chinese art, offering a culturally pertinent and engaging approach. The research design comprises three intervention sessions within a week period, with assessments administered before and following each session to measure immediate effects. A follow-up evaluation one-week post-intervention is essential to ascertain if the effects endure beyond the immediate results. The incorporation of quantifiable metrics like salivary cortisol levels, with subjective evaluations, strengthens the study's rigor, mitigating the shortcomings of prior research that depended exclusively on self-reported data.
Strengths and Limitations
To account for confounding variables and improve internal validity, this study will use a strict multicenter randomized controlled trial (RCT) design with restricted randomization techniques. The intervention creates a multifaceted and comprehensive framework to enhance psychological well-being (PWB) among older adults in assisted elderly centers by creatively combining culturally adapted Chinese art activities (CAA) with peer group participation (PGP). A thorough evaluation approach that combined objective and subjective markers will be used as the methodology. The outcomes of the study are considerably more constructed and ecologically valid because of applying multi-method measurement technique Conclusions: This project has the potential to yield significant insights for the delivery of aged care and policies. The findings could inform the creation of practical guidelines for enhancing psychological well-being in aged care institutions by demonstrating the efficacy of culturally customized art-based interventions. The study emphasizes the significance of incorporating cultural traditions into contemporary care systems, presenting a scalable approach that may be applied to other aged care cultural contexts. Clinical Trial: Trial registration ClinicalTrials.gov NCT06841133. Registered on Feb 21, 2025
Background: Adolescence represents a critical period where health behaviours emerge that track into adulthood. In South Africa, 22.4% of girls and 10.2% of boys aged 10-14 years are overweight or obes...
Background: Adolescence represents a critical period where health behaviours emerge that track into adulthood. In South Africa, 22.4% of girls and 10.2% of boys aged 10-14 years are overweight or obese, with only 40% meeting physical activity recommendations. Objective: This protocol describes an innovative mixed-methods intervention leveraging participatory citizen science and human-centred design to engage South African adolescents in addressing barriers to healthy lifestyle behaviours. Methods: The YEBO-SPAN study employs a citizen science "by the people" approach based on the Our Voice global citizen science research method, while also integrating human-centred design principles. Eight high schools in Cape Town were invited to participate in the study, with a focus on Grade 9 learners (14-15 years) who have self-select as Citizen Scientist Explorers (completing self-assessment surveys on lifestyle behaviours and social networks) or Discoverers (engaging in the four-step Our Voice process: Discover, Discuss, Activate, Change). The intervention aligns with the Western Cape Education Department's Life Orientation curriculum. Data collection includes validated instruments for physical activity, dietary patterns, sleep quality, mental wellbeing, and egocentric social network analysis. Citizen scientists used mobile technology for geo-tagged photographic and audio-narrative environmental assessments, followed by participatory workshops to analyse findings, prioritize intervention targets, and develop advocacy strategies. Ripple effects mapping evaluates intended and unintended outcomes. Results: The intervention started in August 2024 and will conclude in mid-2026. Published study results are expected in early 2026. Conclusions: This protocol represents the first integration of citizen science and human-centred design in South African schools, generating actionable insights into how environments shape adolescent health behaviours. By embedding the multi-modal procedures within existing curriculum structures and emphasizing youth-led advocacy, the study creates pathways for systems-level impact and horizontal scaling. The approach addresses critical gaps in theory-based, co-created interventions for adolescent health in low- and middle-income countries while centering voices of those most affected by health inequities. This framework offers a replicable model for youth-engaged health promotion research globally.
Background: Human papillomavirus (HPV) is the most frequent sexually transmitted disease in women and the major cause of cervical cancer (CC). Several countries have significantly reduced CC deaths an...
Background: Human papillomavirus (HPV) is the most frequent sexually transmitted disease in women and the major cause of cervical cancer (CC). Several countries have significantly reduced CC deaths and rates by offering cervical screening and HPV vaccination programs. The number of CC screening and HPV vaccine programs in around 100 countries around the world has led to dramatic reductions in incidence and death rates for the disease. HPV vaccination could prevent up to 70% of HPV-related cervical cancer and 90% of genital warts. HPV vaccination plays an influential role in decreasing CC worldwide. Thus, it is essential to formulate a suitable vaccination program for each nation so that they can combat the life-threatening conditions caused by HPV infection. Objective: This study aimed to systematically synthesize the attitudes and health beliefs of Middle Eastern (ME) parents regarding HPV vaccination, and to examine parents' uptake of HPV vaccination in ME nations, as well as assess their children's HPV vaccine uptake. Methods: Methods: This review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Since the first HPV vaccination was approved in 2006, PubMed/MEDLINE, Web of Science, CINAHL, and Google Scholar were searched for papers between January 1, 2006, and May 2025. Results: Out of the 33 included studies, 32 were quantitative observational (cross-sectional), while one was a qualitative study. The findings were synthesised according to the six components of the health belief model: perceived susceptibility and severity regarding HPV and vaccination, perceived barriers to HPV vaccination uptake, perceived benefits of HPV vaccination, self-efficacy as a measure of HPV vaccination, concerns surrounding HPV vaccination, modifying variables influencing HPV uptake, and parental attitudes towards HPV vaccination uptake. Parents expressed apprehension about their limited knowledge of the virus and vaccine, citing obstacles such as a shortage of healthcare providers, safety concerns, cost, and vaccine availability. Conclusions: The knowledge of HPV and its possible carcinogenic consequences in Middle Eastern nations was insufficient. Strategies to improve HPV vaccination uptake included mass medical campaigns, healthcare professional involvement, educational interventions, health insurance coverage, and recommendations from the Ministry of Health. Self-efficacy played a crucial role in enhancing vaccine uptake.
Background: The generation of clinical diagnoses from image data is a cornerstone of medical image analysis. ChatGPT-4, a large multimodal model capable of processing both text and image inputs (e.g.,...
Background: The generation of clinical diagnoses from image data is a cornerstone of medical image analysis. ChatGPT-4, a large multimodal model capable of processing both text and image inputs (e.g., dermatoscopic, histologic, and radiographic images), has recently attracted considerable interest in medical artificial intelligence. Objective: To evaluate ChatGPT 4's enhanced diagnostic accuracy for congenital ear deformities using prompt engineering and retrieval augmentation. Methods: We evaluated ChatGPT-4’s ability to identify superficial facial malformations using four categories of congenital ear deformities—microtia, cryptotia, accessory ears, and prominent ears. Diagnostic accuracy was assessed under four conditions: (1) baseline (no prompt engineering), (2) prompt‑enhanced, (3) Retrieval‑Augmented Generation (RAG) without prompts, and (4) RAG with optimized prompts. Results: Baseline accuracy rates were 76.0% for microtia, 3.2% for cryptotia, 8.3% for Accessory ears, and 40.0% for prominent ears. Prompt engineering improved accuracy to 100.0%, 80.6%, 16.7%, and 80.0%, respectively. The RAG approach without prompts yielded identical rates (82.0%, 0.0%, 25.0%, and 0.0%). When combined with optimized prompts within the RAG framework, the model achieved 100% accuracy across all four categories. Conclusions: Prompt engineering significantly enhances ChatGPT-4’s diagnostic performance on image‑based tasks, and its integration within a RAG framework delivers optimal accuracy. These findings support the potential of multimodal large language models for reliable clinical image interpretation when augmented with retrieval and tailored prompts.
Background: The advent of digital tools has led to innovative mental care solutions, giving hope to persons living with anxiety disorders. However, the current plethora of digital tools available in t...
Background: The advent of digital tools has led to innovative mental care solutions, giving hope to persons living with anxiety disorders. However, the current plethora of digital tools available in the field of psychiatry and mental health to treat these disorders raises a wide range of experiential, clinical, ethical, and organizational questions. Objective: This study (IMAGINE) aimed to characterize the social representations of digital mental health (DMH) of three categories of healthcare system stakeholders from six different European countries: individuals living with anxiety disorders, caregivers of persons living with these disorders, and mental health professionals. Methods: A free association approach was used to explore representations of DMH for the three stakeholder categories in Belgium, France, Germany, the Netherlands, Northern Ireland, and Scotland. A lexicometric analysis was performed to qualify and quantify participants’ freely associated words by analysing their statistical distribution using the ALCESTE method with the IRaMuTeQ software package. Results: The free association task was completed by 94 participants. The representation system of DMH of persons living with anxiety disorders focused on the concept of social connection and autonomy. Instead, caregivers prioritized well-being and health, while mental health professionals concentrated on support. Participants aged 30-39 years old associated DMH with the concept of support and well-being, while younger and older individuals emphasized connection and information. Belgians focused on support and well-being; Germans, Northern Irish, and Dutch prioritized connection and information, while Scottish participants emphasised autonomy and empowerment. France was the only country where no representational concept was significantly more frequent than others. All participants, irrespective of their profile, had a low level of familiarity with DMH.Representations of DMH were shaped by age, stakeholder type, and nationality, reflecting socio-healthcare policies. Four main concepts emerged: (1) The need for support in psychiatry which leverages innovation while preserving a humanistic practice; (2) Interpersonal connections; (3) Autonomy and empowerment, understood through two dimensions: (i) Emancipatory technologies enabling a renegotiation of power dynamics among healthcare system stakeholders, and (ii) A contemporary imperative for individuals to embrace self-managenent of their health from an individualistic perspective; (4) Well-being and health, coupled with internalized pressure to engage in personal care, are pathways of self-awareness and self-mastery; they reinforce personal responsibility and maximize individual potential. Moreover, they reflect a shift towards individual repsonsability for one’s own well-being. Conclusions: The representations of DMH by the different healthcare system stakeholders appeared to be shaped by sociotechnical imaginaries which in turn were molded by socio-political contexts. Despite several State initiatives promoting DMH in the six European countries studied, there are implementation lags; this suggests an incremental evolution rather than a paradigm shift in terms of DMH integration in Europe. To limit these lags and ensure inclusivity, policies should prioritize societal practices over individual actions, emphasizing accessibility and equity. Finally, while technological advances hold promise for revolutionizing healthcare delivery, they also lead to concerns regarding power dynamics and social disparities
Background: With the accelerating aging of China's population, the incidence and mortality of coronary heart disease (CHD) continue to rise, making it one of the major diseases threatening the health...
Background: With the accelerating aging of China's population, the incidence and mortality of coronary heart disease (CHD) continue to rise, making it one of the major diseases threatening the health of Chinese residents. Percutaneous coronary intervention (PCI) is one of the effective treatments for CHD. Implementing effective cardiac rehabilitation (CR) after surgery can improve patients' cardiac function and quality of life, while also effectively reducing readmission and mortality rates1. The safety and efficacy of traditional center-based CR have been confirmed. However, due to constraints such as time, distance, and medical costs, patient participation and completion rates in center-based CR remain low2. Home-based cardiac rehabilitation (HBCR) primarily provides long-term or even lifelong rehabilitation guidance in a home setting3. Its benefits are comparable to those of hospital-based CR, and it offers advantages such as flexibility and convenience4. Nevertheless, due to the lack of safety monitoring and professional guidance, patient compliance has not significantly improved.CR resources in China are highly limited, and HBCR is still in its early stages, making it difficult to promote effectively at the grassroots level5. Therefore, exploring new CR models is particularly important. Home-based cardiac telerehabilitation (HBCTR) utilizes mobile communication technology to provide real-time guidance to patients through voice and video communication, while also monitoring their conditions via portable devices to ensure the completion of home-based rehabilitation plans6,7. However, its clinical application remains in the early stages, and related reports are still limited. This study compares the effects of HBCTR, center-based CR, and refusal of guidance on the safety, health-related quality of life (HRQoL), health behaviors, psychological status, and exercise capacity of patients with unstable angina after PCI. Objective: To investigate the efficacy of home-based cardiac rehabilitation under remote guidance (HBCTR) in patients with unstable angina after percutaneous coronary intervention (PCI). Methods: A total of 117 patients with unstable angina who underwent PCI at the Department of Cardiology, Zigong Fourth People’s Hospital, from June 2024 to June 2025 were selected and divided into three groups based on their rehabilitation preferences: the home-based telerehabilitation group (n=64), the center-based cardiac rehabilitation group (n=36), and the refusal of guidance group (n=17). The home-based telerehabilitation group received home-based rehabilitation guidance through remote monitoring devices and regular follow-ups, the center-based cardiac rehabilitation group participated in clinic-based rehabilitation training three times per week, and the refusal of guidance group received no professional guidance. After 12 and 36 weeks of intervention, indicators such as safety, health-related quality of life (HRQoL), exercise capacity, mental health, and health behaviors were compared among the three groups. Results: The home-based telerehabilitation group showed significantly greater improvements in the Physical Component Summary (PCS) score, 6-minute walk test (6MWT), and tobacco dependence compared to the center-based cardiac rehabilitation group and the refusal of guidance group (all P<0.05). Additionally, the home-based telerehabilitation group had lower anxiety scores (GAD-7) at 36 weeks (P<0.001). There was no significant difference in the incidence of adverse events among the three groups (P>0.05). Conclusions: HBCTR effectively improves physical function, exercise capacity, and mental health in patients after PCI, with a favorable safety profile. It is a feasible home-based rehabilitation model, particularly suitable for patients with limited access to medical resources or those who prefer a home-based environment
Background: Maternal health during the perinatal period is a global public health priority. While antenatal education is widely implemented, conventional lecture-based models often fail to achieve sus...
Background: Maternal health during the perinatal period is a global public health priority. While antenatal education is widely implemented, conventional lecture-based models often fail to achieve sustained behaviour change. Innovative approaches that integrate experiential learning with digital support may enhance maternal knowledge, self-management, and pregnancy outcomes. Objective: To evaluate the feasibility and preliminary effectiveness of a combined experiential class and online logging intervention for pregnant women in China, and to explore the mechanisms underpinning its impact on health behaviours and service experiences. Methods: A mixed-methods design was employed in a district-level maternal and child health hospital in Beijing. In the quantitative arm, 40 women (intervention group, n=20; control group, n=20) were enrolled in a quasi-experimental comparison. Outcomes included knowledge-attitude-practice (KAP) indicators, service satisfaction, and clinical birth outcomes. Given the limited sample size, a qualitative arm was conducted to complement statistical findings: semi-structured interviews with 20 women (10 per group) were analyzed thematically. Quantitative and qualitative results were integrated during interpretation to provide a comprehensive evaluation. Results: Compared with experiential class alone, the combined intervention significantly improved maternal knowledge, healthy behaviour adherence, and satisfaction, with favourable but non-significant trends in clinical outcomes. Qualitative analysis revealed three mechanisms-empowerment and self-efficacy, practice and persistence, and systemic/environmental support-through which the intervention influenced experiences and behaviours. Conclusions: The experiential class plus online logging model is feasible and acceptable in a real-world antenatal setting. While limited by small sample size, findings suggest the intervention improves maternal knowledge, behaviours, and service experiences, with potential to optimize pregnancy outcomes. Qualitative insights highlight mechanisms of behavioural change and provide contextual depth, underscoring the value of mixed-methods designs in maternal health research.
Background: Approximately 1.3 million people are living with HIV in Kenya. Despite advances in antiretroviral therapy (ART), men continue to experience disproportionately poor engagement in HIV care d...
Background: Approximately 1.3 million people are living with HIV in Kenya. Despite advances in antiretroviral therapy (ART), men continue to experience disproportionately poor engagement in HIV care due to entrenched masculine norms, stigma, and lack of tailored interventions. Mobile health (mHealth) platforms offer a promising strategy to improve care engagement, but their effectiveness remains under-evaluated particularly among men. However, evidence on its implementation and impact among men living with HIV is limited. Objective: This study aims to assess the implementation and potential effects of the Nishauri mHealth intervention on HIV care and treatment outcomes among men in western Kenya. Specifically, it seeks to- (1) analyze its potential effects on HIV care and treatment outcomes; (2) explore the role of masculine identity in modifying its acceptability and uptake; and, (3) identify barriers and facilitators of its adoption, utilization and sustainment. Methods: We will use mixed-methods design with a stepped wedge and pre-post implementation approaches across four health facilities in Homa Bay County, Kenya—a region with the country’s highest HIV prevalence (16.2%). The study will enroll approximately 347 men receiving HIV treatment who own a smartphone. Surveys will collect socio-demographics, masculinity, intervention acceptability, uptake, and HIV clinical outcomes data using validated scales. The intervention will be sequentially introduced across the facilities over an eight-month period, and we will assess visit attendance and pharmacy refill data using clinical records. Focus group discussions (5-6) will be conducted with (approximately 6) application developers, healthcare providers, and men living with HIV who are on ART to explore barriers and facilitators to adoption, utilization, and sustainment. Audio-recorded FGDs will be transcribed, coded, and analyzed thematically using Dedoose. McNemar’s test will compare pre-post binary outcomes, and Generalized Estimating Equations (α= .05, β= .2, 95% CI) will be used to assess the intervention’s effect via the stepped wedge design, accounting for repeated measures and clustering. Results: This study received initial Institutional Review Board approval in July 2025, and was registered on ClinicalTrials.gov in August 2025. Recruitment began in September 2025 and is scheduled to conclude in November 2025. Preliminary findings will describe implementation outcomes and early effects on HIV care engagement. Conclusions: This trial will use a stepped wedge design to evaluate the implementation and effects of Nishauri mHealth intervention on ART adherence and clinic attendance among men living with HIV in Homa Bay County. By examining both clinical outcomes and the influence of masculine norms on intervention uptake, it will provide robust evidence on the effectiveness of mHealth strategies tailored for men in low-resource, high-burden settings. Findings from this study will inform the design and scalability of the trial by identifying key implementation barriers and facilitators critical to optimizing intervention delivery and impact. Clinical Trial: Clinical Trials.gov NCT07116538; https://clinicaltrials.gov/study/ NCT07116538
Introduction: Although technology usage is steadily increasing among older adults, adoption and confidence greatly lags behind their younger counterparts. Sociocultural and health disparities intersec...
Introduction: Although technology usage is steadily increasing among older adults, adoption and confidence greatly lags behind their younger counterparts. Sociocultural and health disparities intersect with aging to present distinct structural and psychosocial barriers to adoption of newer technologies. Growing evidence suggests that digital health literacy interventions may improve technology skills, increase technological self-efficacy, and increase frequency of technology use. However, these digital literacy interventions do not systematically consider participants’ values and goals, which we know are key to long term behavior change.
Purpose: The proposed study aims to develop and evaluate the acceptability and feasibility of a person-directed, values-based digital literacy intervention for older adults.
Methods: We enrolled 20 participants in a 1:1 randomized pilot control trial with waitlist control. Inclusion criteria included aged 65 and older with English proficiency and willingness to improve digital literacy. Exclusion criteria involved severe cognitive impairment. Over the course of 8-12 weeks, participants received up to six in-home biweekly visits and interim phone calls based on their individual digital literacy needs and participant-directed goals. Each participant also received internet connectivity and a tablet if not already available. Our main outcome was digital literacy improvement. We also assessed technological self-efficacy, digital health literacy, quality of life, and measures of physical and emotional well-being.
Discussion: This protocol offers a unique model centering the values and goals of older adults to improve access, use and understanding of technology. Tapping into the motivators of older adults may offer a more beneficial way to encourage older adult technology use. VISTA could be useful in many contexts- home bound or seriously ill older adults or as a pre-intervention for interventions involving advanced technology understanding.
Background: WeChat is a important source of health information for Chinese perinatal women. The quality of its health information and alignment with perinatal women’s needs influence health literacy...
Background: WeChat is a important source of health information for Chinese perinatal women. The quality of its health information and alignment with perinatal women’s needs influence health literacy and self-management in those with hyperglycemia in pregnancy. Objective: This study aimed to multidimensionally evaluate the quality and alignment with perinatal women’s needs of hyperglycemia in pregnancy health information on China’s WeChat platform, and identify its overall multidimensional quality patterns. Methods: The terms “妊娠期” (pregnancy) and “糖尿病” (diabetes), or “妊娠期” (pregnancy) and “高血糖” (hyperglycemia) were used to search in WeChat, the hottest articles on hyperglycemia in pregnancy were selected. DISCERN was used to evaluate the information’s content quality, Patient Education Materials Assessment Tool (PEMAT) was used to evaluate the information’s understandability and actionability. Specific deficiencies identified in low-scoring items are reported herein. Latent profile analysis (LPA) was used to determine the overall performance patterns of multidimensional quality. Frequency statistics and theme extraction from literature were used to determine the alignment with perinatal women’s information needs. ANOVA was used to analyze variations in DISCERN and PEMAT scores across various information sources. Spearman correlation analysis was used to analyze the relationships between DISCERN and PEMAT scores and different traits of information dissemination. Results: A total of 286 hottest articles on the WeChat platform were included, with a DISCERN score of 41.06 (SD 6.46), a PEMAT understandability score of 64.7% (SD 10.3%), an actionability score of 41.6% (SD 20.8%), and a 42.0% (SD 15.7%) alignment between article content and the information needs of perinatal women. The overall performance patterns of information quality falls into three categories: “professional priority-practical lag type” (19%), “usability priority-basic reliability type” (16.5%), and “multidimensional defects-unusable type” (64.5%). The total DISCERN score, scores for the credibility and comprehensiveness dimension scores of DISCERN, and PEMAT actionability scores differed across different sources (p<.05). Weak positive correlations were observed between daily reads counts and likes with comprehensiveness (ρ=0.19, P<.001; ρ=0.15, P=.01), understandability (ρ=0.19, P=.001; ρ=0.171, P=.004), and actionability (ρ=0.21, P<.001; ρ=0.18, P=.002). Additionally, daily retweets counts were weakly positively correlated with actionability (ρ= 0.21 and P<.001). Conclusions: The quality of health information on hyperglycemia in pregnancy on WeChat is generally average, characterized by low actionability, limited understandability, and limited alignment with information needs. Overall, the “multidimensional defects-unusable type” is predominant. It is recommended that authors of health information for users with hyperglycemia in pregnancy respond to the sophisticated information demands of perinatal women and comprehensively improve the multifaceted quality of information, thereby enhancing perinatal women’s health literacy and self-management capabilities.
Background: The rapid aging of global populations highlights the need for innovative interventions to enhance the well-being of older adults；VR-assisted art provides a new platform. Objective: This...
Background: The rapid aging of global populations highlights the need for innovative interventions to enhance the well-being of older adults；VR-assisted art provides a new platform. Objective: This scoping review aims to systematically map and evaluate the application of VR-assisted art creation in enhancing the well-being of older adults, with a focus on its impacts on physical, mental, and social connections, as well as the challenges and supports encountered during implementation. Methods: Following the methodological framework proposed by the Joanna Briggs Institute (JBI) and reported in accordance with the PRISMA-ScR guidelines, this review specifically examines VR-assisted artistic activities among adults aged 60 years and above. A systematic search was conducted in PubMed, Web of Science, Scopus, and the ACM Digital Library for studies published from January 2015 to January 2025. A total of 1609 records were screened, and 14 eligible studies were included. Results: Across the 14 included studies, VR-based art interventions consistently produced multidimensional benefits. Randomized trials showed notable motor rehabilitation gains, such as Barthel Index improvements exceeding 40% and a reduction in spasticity [35]. Emotion regulation significantly improved through immersive art applications,with depressive symptoms decreasing by 27–32% for up to two months [27]. Multi-user VR environments increased social connectedness, as 57% of participants reported enhanced social support [19]. Neurophysiological data suggest neuroplasticity, showing cortical activation increases up to 38% [22], while immersion levels remained high, with flow states averaging 7–9/10 (Figure 2). However, challenges including device discomfort, cost, and limited cultural adaptation were reported (Table 4), underscoring the need for longitudinal studies, culturally responsive designs, and standardized evaluations to enhance generalizability and scalability. Conclusions: Future research should prioritize the development of cost-effective, age-friendly VR solutions, the establishment of robust theoretical models, and the creation of scalable frameworks to maximize VR’s potential in promoting healthy aging and social innovation. This review integrates empirical evidence with practical insights and advocates interdisciplinary collaboration to address the diverse needs of aging populations through VR technology. Clinical Trial: Not applicable.
Background: The accumulation of mucus in the airways is a serious health problem as it can obstruct airflow and impair lung function. This condition is typically managed by suctioning the mucus and pe...
Background: The accumulation of mucus in the airways is a serious health problem as it can obstruct airflow and impair lung function. This condition is typically managed by suctioning the mucus and performing manual chest clapping, which involves repeatedly patting the back. However, manual clapping is often ineffective and inefficient due to factors like operator fatigue and inconsistent application. This research introduces a portable clapping system called Clapping and Heater Integrated Caring device (CHIC) Objective: this research is to develop an automatic detection system that can reliably recognize human clapping and hand induced vibrations using wearable sensors. The study aims to design and implement pattern recognition algorithms, ranging from threshold based methods to lightweight machine learning models, that differentiate intentional clapping or vibrating gestures from environmental noise, and to evaluate the system’s real time performance in terms of accuracy, latency, and energy consumption across diverse usage scenarios. Methods: This research introduces an innovative medical device that integrates automatic clapping capabilities with a vibrating warm pillow. The goal of this innovation, named CHIC, is to overcome the limitations of manual methods and enhance the effectiveness of chest physiotherapy. A key feature that makes CHIC so relevant is the use of Neural Network (NN) technology to determine the number of claps based on the patient's condition Results: A Neural Network (NN) allows the system to adaptively generate the optimal clapping frequency based on the patient's physiological parameters, ensuring a more precise and personalized therapy compared to conventional approaches. Three different NN architectures were tested, and the one with three hidden layers and a neuron configuration of [20 30 40] proved to be the most effective. This configuration yielded a Mean Squared Error (MSE) of 0.00029279 for the training data and a Root Mean Squared Error (RMSE) of 0.02812 for the validation data. Conclusions: The CHIC device demonstrated reliable performance for airway clearance therapy. Its ESP32 based control system, temperature monitoring, vibrating pillow, and rotary DC motor provided consistent and coordinated clapping actions. The integrated neural network algorithm dynamically adjusted the clapping frequency according to the patient’s physiological parameters, delivering a more precise and personalized treatment compared to manual chest percussion. The system operated without operator fatigue and maintained patient comfort, indicating that CHIC is an effective and practical solution for clinical and community based physiotherapy applications
Background: HIV incidence has continued to increase among men who have sex with men (MSM) in Peru, despite intervention efforts. Addressing stigma, risky behaviors, and low medication adherence is key...
Background: HIV incidence has continued to increase among men who have sex with men (MSM) in Peru, despite intervention efforts. Addressing stigma, risky behaviors, and low medication adherence is key to reducing incidence rates. Ecological momentary assessment (EMA) allows for collection of discrete, real-time data of stigmatized, risky behaviors while reducing recall bias. Objective: The aim of this study was to develop and assess the usability of an EMA smartphone app among HIV+ MSM in Peru which tracks daily health risk behaviors to determine ease of use, usefulness, and satisfaction with the app. Methods: A mixed-method three-phase study was conducted which included a usability test, 10-day field testing, and a debriefing focus group. Quantitative survey data and user analytics allowed for assessments of acceptability and user compliance. Qualitative interview and focus group data were thematically analyzed for in-depth assessments of user satisfaction. Results: Acceptability of the EMA app was high with a mean usability rating of 6.4/7.0, indicating high user satisfaction, ease of use, and usefulness. 10-day field testing demonstrated a high average compliance rate of 93%, which suggests high feasibility of the app for daily tracking of health risk behaviors among HIV+ MSM. Interview and focus group findings indicated that the app was navigable, time-efficient, and holds promise for long-term use, particularly with the inclusion of daily reminders and incentives for prolonged use. Conclusions: EMA apps can provide valuable real-time data while protecting users’ privacy. This formative work lays the foundation for future larger-scale EMAs of substance use and sexual risk behaviors among high-risk HIV populations, and in developing just-in-time (JIT) interventions to address stigma, improve medication adherence, and reduce risky behaviors. Clinical Trial: NA
Background: Telehealth can improve access to care for people living with multiple sclerosis (pwMS), but information on its acceptance is limited in Switzerland. Objective: This study aimed to determin...
Background: Telehealth can improve access to care for people living with multiple sclerosis (pwMS), but information on its acceptance is limited in Switzerland. Objective: This study aimed to determine the proportion of pwMS willing to accept telehealth as a new default and the factors associated with their acceptance. Methods: We conducted a cross-sectional analysis using survey data from the Swiss Multiple Sclerosis Registry. We defined "telehealth as a default" as a healthcare model where remote consultations (telephone and/or video calls) are the primary mode of interaction between patients and their physicians, with in-person visits based on clinical necessity. Multivariable logistic regression was performed to evaluate the association between telehealth acceptance and socio-demographic and health-related factors. Telehealth acceptance was described in relation to three survey variables that mirrored key constructs from the non-adoption and abandonment of technologies by individuals and the challenges to scale-up, spread, and sustainability of technologies in health and care organisations (NASSS) framework. The variables were digital communication preferences, internet use for health provider searches, and experience with telemedicine. Results: Among 427 respondents, 15.5% (66/427) reported a willingness to accept telehealth as a default. In this group, only 21.2% (14/66) had experience using telemedicine. A descriptive analysis of our three NASSS-derived key constructs showed that among the 78.5%(335/427) respondents who generally agreed to digital access to health data, only 17.0% (57/335) accepted telehealth as a default. Notably, 30.7%(129/427) of participants stated a wish for support for using devices or the internet. Among those 129 individuals, 17.1% (22/129) were willing to accept telehealth as a default. Of the 89 people with prior telehealth experience, 15.7% (14/89) were willing to accept telehealth. In multivariable analysis, digital communication with healthcare providers (HCP) (adjusted odds ratio (aOR): 14.56, 95% confidence interval (CI): 6.18 – 39.04, P < .01), current internet use for healthcare provider search (aOR: 7.78, 95% CI: 1.34– 45.32, P = .02) and a secondary progressive MS (SPMS) diagnosis (aOR: 0.23, 95% CI: 0.05–0.07, P= .02) were independently associated with accepting telehealth as a default. Conclusions: Our findings suggest a low acceptance of telehealth as a default among pwMS in Switzerland. While our three postulated NASSS-derived key constructs were not associated with telehealth acceptance, we noted additional behavioural factors, including previous digital communication with healthcare providers and using the Internet to search for healthcare provider information, which were associated with telehealth acceptance. Moreover, advanced disease states like SPMS were negatively associated with telehealth acceptance. Thus, telehealth as a default will be most acceptable in pwMS who already use the internet for their health, and those with less severe disease. Future research should explore provider perspectives and evaluate long-term strategies for the acceptance of telehealth in MS care.
Background: The risk of rehospitalization in heart failure (HF) patients has initiated various preventive efforts and to simultaneously improve the quality of life (QoL) of the patients. Self-monitori...
Background: The risk of rehospitalization in heart failure (HF) patients has initiated various preventive efforts and to simultaneously improve the quality of life (QoL) of the patients. Self-monitoring at home is one option, and technology is increasingly being used for this purpose. Objective: To reduce the risk of hospital readmission and maintain the QoL of HF patients through self-monitoring with the assistance of a digital application. Methods: Starting with determining the need for HF services in National Cardiovascular Center Jakarta in 2024, an application called FineHeart was built and tested on HF patients in a quasi-experimental pilot study. After the User Acceptance Test was completed, HF patients were recruited as intervention group and control group participants. Quality of Life was measured with the Kansas City Cardiomyopathy Questionnaire (KCCQ) before and after the test. The readmission rate and 4 of the KCCQ parameters were analysed between the 2 groups. Results: Of the 72 patients who met the inclusion criteria, thirty participated in the intervention group and thirty in the control group who had signed the consent form. In the intervention group, after 30 days, 22 people complied using the FineHeart application prototype (73.3%), six were readmitted (20%), and one died not because of HF (3.3%). In the control group, 10 were readmitted (33.3%), and three died because of HF (10%). There was a significant relationship between adherence to application usage and an increase in Quality-of-Life scores (p<0.029) and Overall Summary Score (p<0.001)), but not in Self-efficacy and Social Limitation Scores. Conclusions: The findings of this study provide a potential benefit for HF patients to perform self-monitoring at home in collaboration with the hospital team by using FineHeart app. Patient adherence may reduce the risk of readmission and improve QoL. Multicenter studies on larger groups of patients are needed to confirm these preliminary results.
Background: Approximately 27% of United States adults live with a disability, yet they face persistent disparities in health outcomes and access to care. The systematic collection of disability status...
Background: Approximately 27% of United States adults live with a disability, yet they face persistent disparities in health outcomes and access to care. The systematic collection of disability status and accommodation needs data in electronic health records (EHRs) can support more equitable access to care, help ensure that patients with disabilities receive appropriate, person-centered care, and bolster efforts to monitor and address health disparities for people with disabilities. However, data collection remains limited in the health care setting. Objective: This qualitative study aimed to examine current practices for collecting, documenting, and exchanging disability-related data in EHRs. This study identifies the current state of disability-related data collection by health care organizations; describes how these data are used by health care organizations and researchers; presents challenges to data collection; and offers opportunities to advance the standardized collection and use of disability-related data. Methods: A qualitative, two-pronged approach was employed, consisting of a literature scan and 13 key informant interviews with stakeholders from health systems, research institutions, and policymaking and advocacy organizations. Data were analyzed using a structured abstraction matrix to identify themes related to data collection practices, use cases, challenges, and opportunities to improve standardization and interoperability. Results: We identified three use cases for collecting, documenting, and exchanging disability-related data: (1) preparing for patient visits, (2) improving care quality, (3) facilitating care transitions, and (4) advancing equity research. However, findings from the literature scan and key informant interviews revealed that most health care organizations do not routinely collect disability status or accommodation needs data. Among those that do, they employ varied and non-standardized approaches, hindering the ability of health care organizations to provide legally mandated accommodations and deliver equitable, patient-centered care. Conclusions: Conclusions: Standardized and systematic collection of disability status and accommodation needs data is critical to advancing health equity, improving care quality, and supporting patient-centered care for people with disabilities. The inclusion of “disability status” as a requirement for certified health information technology, including electronic health records (EHR), beginning in 2026 represents a critical step toward more standardized data collection. Efforts to strengthen data collection practices should include workflows for documenting a patient’s self-reported disability and requested accommodations, enhancing health information technology systems, engaging stakeholders across health care settings, and promoting adoption of national standards to ensure disability-related data are accurate, actionable, and interoperable.
Background: Though paediatric rehabilitation is a critical component of healthcare, it is under-resourced and researched, with interventions based on adult care models. Children and young people (CYP)...
Background: Though paediatric rehabilitation is a critical component of healthcare, it is under-resourced and researched, with interventions based on adult care models. Children and young people (CYP) deserve to be treated as their own population, with their care designed accordingly. In line with current healthcare evolution, and the fact that CYP are ‘digital natives’, technology should be employed in order to achieve the reform necessary within the discipline. Objective: Therefore, this UKRI funded project sought to establish CYP and parents’ views on technology within rehabilitation with view to co-design ‘Kompass Kids’ a patient portal application for CYP in rehabilitation to accompany an existing software application, Kompass Health. Methods: Data were collected using a two-phase semi-structured interview design, with six participants (n=6). Phase one explored general attitudes toward technology and elicited design suggestions for the portal; phase two involved feedback on developed wireframes. Reflexive thematic analysis (Boyatzis, 1998) was used to analyse participant transcripts, with emergent themes acknowledged as shaped by social and experiential contexts (Braun & Clarke, 2006). Results: Five themes emerged from the data: 1) Meaningful rehabilitation, 2) Provision of care, 3) Progress, 4) Information and 5) Empowerment. Rehabilitation technologies were viewed positively by the participants, particularly to enhance autonomy and personal meaning within their rehabilitation. Access to information and tracking potential were deemed as necessary and important for best-practice rehabilitation. Both at the initial conceptualisation and the wireframe stage, Kompass Kids was received extremely well, with participants identifying its utility for them personally, and for rehabilitation more broadly. Conclusions: This study demonstrates the value of experience-based co-design in developing equitable, child-centred digital health tools. By involving children and parents throughout the design process, the resulting intervention was meaningfully aligned with user priorities and real-world needs. The study emphasises the importance of personal relevance and emotional engagement in rehabilitation, underscoring that paediatric interventions must reflect children’s developmental needs, interests, and identities. Clinically, the study supports growing calls for digitally integrated care pathways that improve continuity, accessibility, and engagement in paediatric rehabilitation, addressing long-standing service gaps and the need for developmentally appropriate, motivating interventions.
Chatbots are increasingly deployed across domains, yet systematic evaluation of their usability remains limited, particularly in non-Western contexts. The 11-item Chatbot Usability Scale (BUS-11) has...
Chatbots are increasingly deployed across domains, yet systematic evaluation of their usability remains limited, particularly in non-Western contexts. The 11-item Chatbot Usability Scale (BUS-11) has shown strong psychometric properties in prior studies, but no validated Chinese version exists despite China being one of the largest chatbot markets. This study aimed to translate, culturally adapt, and validate BUS-11 for Chinese users. Following established cross-cultural adaptation procedures, the scale was forward–and back–translated, reviewed by an expert committee, and pilot-tested for clarity and feasibility. A main validation study was then conducted with 146 participants who completed 438 chatbot evaluations across ten widely used systems. Psychometric analyses demonstrated excellent content validity (S-CVI = 0.92), strong internal consistency (Cronbach’s α = 0.923), and a clear three-factor structure (Accessibility, Interaction Process Quality, Information Quality) explaining 56.1% of the variance, while Privacy/Security and Response Time were retained as single-item indicators. The Chinese BUS-11 proved concise (completion time <5 minutes), user-friendly, and psychometrically robust. This work fills a critical gap by providing the first validated instrument for assessing chatbot usability in Chinese contexts, enabling reliable cross-cultural comparisons and supporting both research and practical design evaluation in human–computer interaction.
Background: Objective: To map the available evidence on psychosocial interventions (PIs) targeting the Brazilian Black population's mental health.
Introduction: Black population (BP) is proportional...
Background: Objective: To map the available evidence on psychosocial interventions (PIs) targeting the Brazilian Black population's mental health.
Introduction: Black population (BP) is proportionally more institutionalized in psychiatric hospitals, and is historically more associated with “madness”, dangerousness, and racial inferiority. PIs targeting the Black population's mental health can potentially enhance professional practices by addressing this group's specific needs.
Inclusion criteria: Participants: Brazilian BP; concept: PIs targeting the Black population's mental health; context: Whole Brazilian country. Therefore, studies addressing PIs targeting the Brazilian BP, including the “Quilombola” community's mental health, will be considered as inclusion criteria. Studies addressing black immigrants and refugees in Brazilian territory will be excluded.
Methods: This scoping review (SR) will follow the JBI methodology guidelines, and adheres to the PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Search Strategy: A focused search will be conducted in MEDLINE (PubMed), Psycinfo (APA) CINAHL (EBSCOhost), Embase, Scopus (ELSEVIER), CINAHL (EBSCO), APA (PsycInfo), Embase and the Virtual Health Library (BVS). There will be no restriction regarding the language or date of publication of the studies. Study Selection: Citations will be managed in Zotero, and Rayyan will be used to organize the screening. Two independent reviewers will screen titles and abstracts for eligibility. Disagreements will be resolved through discussion or consultation with a third reviewer. Data Extraction: Two independent reviewers will extract data using a custom tool. Data Analysis and Presentation: Results will be summarized narratively and presented in tables and charts. Objective: To map the available evidence on psychosocial interventions (PIs) targeting the Brazilian Black population's mental health. Methods: This scoping review (SR) will follow the JBI methodology guidelines, and adheres to the PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Search Strategy: A focused search will be conducted in MEDLINE (PubMed), Psycinfo (APA) CINAHL (EBSCOhost), Embase, Scopus (ELSEVIER), CINAHL (EBSCO), APA (PsycInfo), Embase and the Virtual Health Library (BVS). There will be no restriction regarding the language or date of publication of the studies. Results: This section does not present data; it is a protocol. Conclusions: The review's conclusion promises to map critical evidence gaps.
Background: Familial eruptive syringomas (FES) are rare benign adnexal tumors of eccrine origin, typically presenting in females with papules on the anterior body surface. Atypical presentations may d...
Background: Familial eruptive syringomas (FES) are rare benign adnexal tumors of eccrine origin, typically presenting in females with papules on the anterior body surface. Atypical presentations may delay diagnosis and contribute to psychosocial burden. Objective: To describe an uncommon case of FES in a male patient with an atypical distribution and to review the diagnostic and therapeutic implications. Methods: We evaluated a 35-year-old male with a history of progressive, asymptomatic papules beginning in childhood. Clinical examination, family history, and histopathology were reviewed. A literature search was conducted to compare this case with previously reported presentations of FES. Results: Histopathology confirmed eruptive syringomas. The patient’s cousin had similar lesions, supporting familial inheritance. The distribution, with truncal and extremity involvement preceding facial lesions, differed from the classic anterior body pattern. Management was deferred given cosmetic concerns, the patient’s darker skin tone, and risk of post-inflammatory hyperpigmentation. Conclusions: This case highlights the clinical variability of FES, the importance of early recognition to avoid misdiagnosis, and the need for cautious treatment planning in skin of color patients.
Background: Isotretinoin, a potent oral retinoid, is widely used in the management of severe, treatment-resistant acne vulgaris. While its efficacy is well established, isotretinoin is associated with...
Background: Isotretinoin, a potent oral retinoid, is widely used in the management of severe, treatment-resistant acne vulgaris. While its efficacy is well established, isotretinoin is associated with a broad spectrum of side effects, including mucocutaneous dryness, psychiatric disturbances, and teratogenicity. Less frequently discussed are its endocrine effects, particularly disturbances of the menstrual cycle, such as delayed cycles, amenorrhea, or menorrhagia. These effects remain underreported in dermatology practice despite their clinical relevance. Objective: To describe a rare case of isotretinoin-induced amenorrhea in a young female patient and highlight the importance of monitoring menstrual function during isotretinoin therapy. Methods: We report the case of a 21-year-old woman with acne vulgaris unresponsive to topical agents and antibiotics. She was started on isotretinoin 10 mg twice daily. Clinical details, laboratory investigations, and menstrual history were carefully documented. Potential confounding causes of amenorrhea were excluded through endocrine tests, thyroid function tests, and a negative pregnancy test. Results: After one month of isotretinoin therapy, the patient developed amenorrhea, despite previously having regular cycles. Laboratory workup, including estradiol and progesterone levels, was normal. No alternative cause of amenorrhea was identified. At the end of the two-month isotretinoin course, the medication was discontinued, after which normal menstruation resumed within three weeks. No recurrence of amenorrhea was noted in subsequent months. Conclusions: Isotretinoin can cause reversible menstrual irregularities, including amenorrhea, through possible disruption of the hypothalamic pituitary gonadal axis. Although rare and often underrecognized, this side effect may impact female patients’ quality of life. Clinicians prescribing isotretinoin should proactively monitor menstrual function and counsel patients regarding this potential adverse effect to ensure timely detection and management.
Background: Benign prostatic hyperplasia (BPH) is highly prevalent among aging men and may lead to progressive lower urinary tract symptoms, surgical intervention, or severe outcomes such as acute uri...
Background: Benign prostatic hyperplasia (BPH) is highly prevalent among aging men and may lead to progressive lower urinary tract symptoms, surgical intervention, or severe outcomes such as acute urinary retention, bladder stones, and renal impairment. Comprehensive long-term studies on BPH progression and outcomes in Chinese populations are limited. Objective: This study aims to analyze disease trajectories, risk factors, and key outcomes of BPH, and to develop predictive models using multicenter retrospective data from the PLA General Hospital network. Methods: We will establish a retrospective cohort of BPH patients with multiple visits across PLA General Hospital centers. The index date is defined as the first hospital visit for BPH. Patients will be followed via outpatient, inpatient, and health examination data until BPH-related endpoints, loss to follow-up, or death. Exclusions include follow-up <180 days, prostate cancer, neurogenic bladder, urethral stricture, pelvic radiotherapy, or incomplete records. Data will include baseline characteristics, comorbidities, treatments, and outcomes. Cox regression will be used to assess risk factors, and Kaplan–Meier methods to estimate cumulative incidence. Results: This study is scheduled to initiate in late October 2025. Conclusions: As a retrospective cohort study, this research is based on the 2000–2021 BPH follow-up data from multiple centers within the medical consortium of the PLA General Hospital. It analyzes the BPH disease progression trajectory and risk factors of key outcome events (e.g., surgical intervention, urinary retention), with the core goal of laying a data foundation for constructing a risk prediction model for BPH clinical progression and outcome events.
Background: Persistent disparities in diversity, equity, and inclusion (DEI) remain across U.S. residency programs despite recent accreditation requirements. While specialty-specific studies exist, no...
Background: Persistent disparities in diversity, equity, and inclusion (DEI) remain across U.S. residency programs despite recent accreditation requirements. While specialty-specific studies exist, no comprehensive synthesis of DEI initiatives across multiple disciplines has been completed. Objective: This scoping review will map and summarize DEI elements in graduate medical education, identifying common practices, omissions, and opportunities for improvement. Methods: Following the Population–Concept–Context (PCC) framework and PRISMA-ScR guidelines, peer-reviewed studies published in English between January 2010 and December 2024 will be included. Eligible studies will examine DEI elements in residency programs, including nondiscrimination statements, recruitment strategies, mentorship, faculty diversity, and anti-bias training. Searches will be conducted in PubMed, Embase, and Scopus. Two reviewers will independently screen, extract, and chart data. Findings will be synthesized descriptively and presented in tables and figures. Results: This review will provide a comprehensive overview of DEI practices in residency programs across specialties, inform best practices for standardization, and support efforts to build a more equitable physician workforce. Conclusions: This review will provide a comprehensive overview of DEI practices in residency programs across specialties, inform best practices for standardization, and support efforts to build a more equitable physician workforce. Clinical Trial: https://osf.io/uxqr7
Background: Xanthelasma palpebrarum (XP) is the most common subtype of cutaneous xanthoma, accounting for more than 95% of cases. Its incidence is increasing and parallels the global rise in obesity....
Background: Xanthelasma palpebrarum (XP) is the most common subtype of cutaneous xanthoma, accounting for more than 95% of cases. Its incidence is increasing and parallels the global rise in obesity. As XP causes conspicuous cosmetic disfigurement, affected patients frequently experience anxiety. Objective: In this study, we investigated the efficacy of intralesional pingyangmycin injection for XP and evaluated the impact of systematic nursing education and psychological intervention on anxiety reduction and treatment outcomes. Methods: A total of 228 patients with XP (398 lesions) treated between December 2024 and August 2025 were enrolled. All patients underwent intralesional pingyangmycin injection and completed psychological assessments using the Hospital Anxiety and Depression Scale (HADS) at baseline and 1month post-treatment. Systematic nursing education, including injection-related care, postoperative recovery guidance, and emotional support, was provided throughout the treatment process. Results: Treatment outcomes showed that 63.31% of lesions achieved complete remission, 23.87% showed improvement, and 2.27% were ineffective. Psychological intervention significantly reduced both anxiety and depression scores (P < 0.001). Furthermore, reductions in anxiety were positively associated with improved treatment outcomes, including a lower incidence of complications and higher patient satisfaction. Conclusions: Intralesional pingyangmycin injection is an effective treatment for XP. When combined with psychological intervention and structured nursing education, it not only alleviates anxiety but also enhances treatment compliance and patient satisfaction, thereby optimizing overall therapeutic outcomes.
Background: Diabetic peripheral neuropathy (DPN) is a length-dependent, symmetric sensorimotor polyneuropathy with substantial global and regional burden. Current pharmacologic options are largely sym...
Background: Diabetic peripheral neuropathy (DPN) is a length-dependent, symmetric sensorimotor polyneuropathy with substantial global and regional burden. Current pharmacologic options are largely symptomatic and do not modify disease. Lymphovenous bypass (LVB), a supermicrosurgical procedure established for lymphedema, may modulate lymphatic-immune-microvascular dysfunction relevant to DPN Objective: The primary objective is to determine whether lymphovenous bypass (LVB) combined with standard of care (SOC) improves small-fiber and autonomic function compared with SOC alone at 6 months. Secondary objectives are to evaluate the effects of LVB on large-fiber function, neuropathic pain, ulcer healing, quality of life, and relevant biomarkers, as well as to characterize its safety profile. Methods: SPIRIT-aligned, single-center, randomized, controlled, parallel-group superiority trial with 2:1 allocation (LVB+SOC:SOC), stratified by ulcer status. Outcome assessors and statisticians are blinded. Primary endpoint is change in pain (DN4) and DPN burden (MNSI), at 6 and 12 months. Key secondary endpoints include foot electrochemical skin conductance (ESC, µS; Sudoscan), nerve conduction studies (NCS), and ulcer outcomes (time to epithelialization; proportion healed by 20 weeks; infection; reoperation; amputation). Exploratory endpoints include oxidative stress/antioxidant indices, inflammatory cytokines, and intraepidermal nerve fiber density (IENFD). N = 60 (LVB n = 40; SOC n = 20) provides 80% power (α = 0.05) to detect a conservative between-group ESC effect (Cohen’s d ≈ 0.70). Results: Recruitment is planned for September 1, 2025–July 31, 2026; follow-up through July 31, 2027. No outcome data are included. Conclusions: This trial tests a mechanism-based, non-pharmacologic adjunct targeting lymphatic-immune-microvascular dysfunction in DPN. If effective, LVB could inform phenotype-directed treatment algorithms and motivate multicenter evaluation and health-economic analyses. Clinical Trial: NCT07126197
Background: Children’s mental health is a critical public health priority, with approximately 8% of children under 10 experiencing mental, behavioral, or emotional disorders. Despite the evidence su...
Background: Children’s mental health is a critical public health priority, with approximately 8% of children under 10 experiencing mental, behavioral, or emotional disorders. Despite the evidence supporting early intervention, access to mental health services remains limited, particularly for socioeconomically disadvantaged populations. Arts-based interventions have emerged as promising approaches to support mental health and socioemotional development. However, significant gaps persist in understanding their efficacy, scalability, and long-term impact. Objective: This study aims to evaluate the effectiveness and cost-effectiveness of a community-based visual arts intervention on children’s self-concept, psychological adjustment, and health-related quality of life (HRQoL), in vulnerable communities. Methods: This study is a cluster non-randomized controlled trial with children from socioeconomically disadvantaged neighborhoods. Children between 6 and 12 years old (n=156; 104 intervention, 52 control) will be recruited through schools and community projects. The intervention consists of one-hour weekly sessions of visual arts sessions over nine months, led by a professional artist, culminating in community art exhibitions. Assessments will be conducted at baseline (T1) and post-intervention (T2) using validated measures: the Strengths and Difficulties Questionnaire (SDQ) for psychological adjustment, the Self-Perception Profile for Children (SPPC) for self-concept, the Child Health Utility 9D (CHU9D) for HRQoL, as well as societal resource use and related costs. Quantitative data will be analyzed using regression models and intention-to-treat principles. Results: This study was funded in September 2023. Recruitment began in March 2024, ending in July 2025. As of April 2024, a total of 171 participants have been enrolled. Data collection was completed by July 2025, and analysis is expected to begin in November 2025. Results are anticipated to be published in June 2026. Conclusions: This project has the potential to enhance children’s self-concept, psychological adjustment, and HRQoL through participation in a community-based visual arts intervention. The study design, with assessments at pre and post time points, will provide valuable insights into the trajectories of psychosocial and quality-of-life outcomes in this population. In addition, the combination of psychosocial assessment and economic evaluation will generate important evidence on the cost-effectiveness of arts-based interventions, informing both educational and public health decision-making. Clinical Trial: NCT07165704 (https://clinicaltrials.gov/study/NCT07165704; registration date: 10/09/2025) (retrospectively registered).
Background: Background: Stress, sleep deprivation, and burnout are significant safety risks for acute care surgeons, negatively impacting performance, well-being, and clinical outcomes. Objective: Obj...
Background: Background: Stress, sleep deprivation, and burnout are significant safety risks for acute care surgeons, negatively impacting performance, well-being, and clinical outcomes. Objective: Objective: This pilot randomized controlled trial aimed to measure the neurophysiological effects of prescribed and self-selected music interventions on surgeon stress, burnout, and neurophysiological responses using a multimodal protocol that integrated functional MRI, wearable biosensor monitoring, and psychological self-assessments. Methods: Methods: Full-time attending surgeons at a quaternary care hospital were invited to participate in a three-armed trial (1:1:1 block allocation). The intervention groups were instructed to listen to 30 minutes (minimum 15) of either prescribed music (PM) or self-selected music (SSM) daily at bedtime for six weeks, reflecting real-world conditions. PM comprised original compositions based on elements promoting perceived relaxation from a prior study. The control arm did not listen to music in the 30 minutes prior to bed. Allocation was concealed from the recruiting investigator; the fMRI technicians, the statistician, and all lead investigators were blinded to patient groups until completion of analyses. Functional connectivity patterns were measured using fMRI at baseline and six weeks while all participants listened to simulated ICU noise, PM, and SSM. Secondary outcomes included continuous actigraphy data for sleep quality and self-reported measures of anxiety, sleep quality, and burnout using validated scales (State-Trait Anxiety Inventory, Pittsburgh Sleep Quality Index, and Maslach Burnout Inventory). Results: Results: Twenty-two surgeons were assessed; the demands of the fMRI and data collection schedule led three to decline and two (originally allocated to PM) not to finish baseline measures; six PM, five SSM, and six controls received allocated intervention; two PM participants were withdrawn for nonadherence and missing follow-up data and one control missed follow-up collection due to scheduling. One control participant experienced transient vertigo in fMRI. Trends in fMRI data indicated both intervention groups experienced less negative emotional arousal and anxiety, with physical tension reduced in the PM group. The PM group exhibited reduced stress response in the frontal lobes when exposed to ICU alarms, suggesting diminished attentional response to the high-stress auditory environment, compared to control. However, lack of statistical significance and baseline variability entail cautious interpretation. Observations of sleep quality were mixed, and no statistically significant differences in stress surveys were observed. Conclusions: Discussion: Both music interventions showed trends toward positive changes in neurophysiological responses, suggesting potential benefits in reducing surgeon stress. However, due to the small sample size, mixed or non-significant secondary outcome results, and the exploratory nature of this study, findings should be considered preliminary. Further research with larger, diverse cohorts will be needed to confirm these trends, refine both the intervention approach and recruitment strategies, and determine whether objective compositional elements or personal familiarity with music drive the mechanisms of potential positive effects. Clinical Trial: ClinicalTrials.gov Registration: NCT05980429
Background: Heart rate variability (HRV) is increasingly used in health and performance monitoring, though research on its practical applications and the accuracy and validity of these apps remains li...
Background: Heart rate variability (HRV) is increasingly used in health and performance monitoring, though research on its practical applications and the accuracy and validity of these apps remains limited. Objective: This study aims to systematically review and analyse the mobile applications that measure, analyse and provide feedback on HRV. Methods: This study was a cross-sectional review of mobile applications for HRV measurement. A systematic search was conducted in the Google Play Store and Apple iTunes Store between October and November 2024. Data were extracted from app descriptions, screenshots, linked websites, and direct communication with developers. Results: The search yielded 746 smartphone apps, with 231 meeting the eligibility criteria. Most HRV apps originated from the iTunes App Store (74.0%). While 38.3% of app information was publicly available in the app description or website, 46.7% was unobtainable. Most apps (87.0%) reported sensor location, including arm, chest, ear, finger and wrist, and 97.0% reported data storage methods. The majority (67.5%) were free with in-app purchases, and photoplethysmography (PPG) was the most common measurement method (61.5%). For only 71 apps complete data was extractable, of which 61 were unique apps without between-store duplicates. Many of these 61 apps used PPG sensors (39.3%) and time-domain HRV metrics like RMSSD (63.9%) and SDNN (60.7%), with most requiring user-triggered measurements and about 35% supporting continuous monitoring. A majority of apps offered personalized HRV reference scores (65.6%), self-reported stressor tracking (55.7%), and contextual insights or guidance like recovery and readiness scores (73.7%). Conclusions: This study highlights the widespread availability but limited transparency and evidence base of heart rate variability apps, underscoring the need for improved data accessibility, measurement validation, and consistency across platforms to enhance their reliability and value for both users and researchers.
Background: Artificial intelligence (AI) technologies are rapidly transforming women’s health globally, offering personalized tools for menstrual tracking, hormonal monitoring, and preventive care....
Background: Artificial intelligence (AI) technologies are rapidly transforming women’s health globally, offering personalized tools for menstrual tracking, hormonal monitoring, and preventive care. However, in the Gulf Cooperation Council (GCC) region, particularly in Kuwait and Saudi Arabia, the sociocultural, behavioral, and technological factors that influence adoption remain underexplored. Objective: This study examines the key psychological and demographic determinants of openness to using AI-based menstrual health technologies among women in Kuwait and Saudi Arabia. Methods: A cross-sectional online survey was administered to adult women residing in the two countries (N = 273). The questionnaire assessed menstrual health awareness, technology readiness, and openness to AI health tools, alongside demographic characteristics. Multiple linear regression, mediation, and moderation analyses were conducted to identify predictors and potential pathways influencing openness. Results: Technology readiness was the strongest predictor of openness to AI health tools (β = 0.152), followed by menstrual health awareness (β = 0.057). Mediation analysis revealed that 61% of the effect of awareness on openness was mediated through technology readiness, indicating a strong indirect pathway. Employment status also moderated the awareness–openness relationship, with part-time and self-employed women showing lower openness to using AI health tools, despite having higher awareness. Other demographic factors (e.g., age, education, nationality) were not significant predictors. Conclusions: Women’s openness to AI-based menstrual health technologies in the GCC is driven more by behavioral engagement and digital familiarity than by demographic background. Culturally sensitive, tech-forward solutions that promote both menstrual health awareness and digital literacy will be essential for driving adoption in the region. Policymakers and developers should prioritize inclusive, accessible, and contextually appropriate AI tools to advance women’s health outcomes across the GCC region. Clinical Trial: The study protocol, titled “Women’s Openness to AI-Enabled Menstrual-Health Technologies in the GCC,” was reviewed and approved by the Research Ethics Committee of Kuwait University (Approval No.: KU-CBA-03-07-25). All procedures complied with the ethical standards of the 1964 Declaration of Helsinki and its later amendments. Participation was voluntary, no identifying information was collected, and survey data were stored on password-protected servers accessible only to the research team.
Before accessing the online questionnaire, each prospective participant viewed an electronic information sheet describing the study’s purpose, procedures, potential risks and benefits, confidentiality protections, and the right to withdraw at any time. Informed consent was obtained electronically; respondents indicated agreement by clicking “I agree” before proceeding and could discontinue the survey at any time without penalty.
Background: AI-enabled menstrual health technologies are expanding globally, yet women’s willingness to adopt them varies across sociocultural contexts. In the Gulf Cooperation Council (GCC) region,...
Background: AI-enabled menstrual health technologies are expanding globally, yet women’s willingness to adopt them varies across sociocultural contexts. In the Gulf Cooperation Council (GCC) region, specifically Kuwait and Saudi Arabia, where digital health is a current national priority, understanding the factors that influence AI acceptance is critical. Objective: This study examines how cultural values, privacy concerns, and demographic characteristics shape women’s openness to AI-driven menstrual tracking technologies in Kuwait and Saudi Arabia. Methods: This study used a cross-sectional survey targeting adult women in Kuwait and Saudi Arabia, recruited online through convenience sampling. The survey, made available in English and Arabic, assessed women’s openness to using AI health tools, cultural fit, and privacy concerns using 5-point Likert scale items. Domain scores were averaged, and multiple regression analyses were conducted to examine the influence of cultural and privacy perceptions on openness to AI, controlling for demographics. Additional t-tests and ANOVAs assessed group differences. Results: The results showed that women who perceived AI health tools as culturally appropriate and aligned with their privacy expectations were significantly more open to using them (β = 0.33). Among demographic groups, homemakers showed higher openness, while other factors like age and education were not significant. Disaggregated analyses revealed that cultural sensitivity and regional specificity were the strongest predictors of AI openness, while general data privacy concerns had a weaker, marginal effect. These findings suggest that cultural alignment and trust are key to promoting AI health technologies in the GCC region, specifically Kuwait and Saudi Arabia. Conclusions: Women’s openness to AI menstrual tracking in the GCC, specifically Kuwait and Saudi Arabia, is driven more by cultural alignment and digital trust than by age or education. Culturally sensitive, accessible, and trusted tools that are paired with education, are key to effective adoption and empowering women in managing their reproductive health. Clinical Trial: The study protocol, titled “Women’s Openness to AI-Enabled Menstrual-Health Technologies in the GCC,” was reviewed and approved by the Research Ethics Committee of Kuwait University (Approval No.: KU-CBA-03-07-25). All procedures complied with the ethical standards of the 1964 Declaration of Helsinki and its later amendments. Participation was voluntary; no identifying information was collected, and all survey data were stored on password-protected servers accessible only to the research team.
Prior to starting the online questionnaire, each participant reviewed an electronic information sheet outlining the study purpose, procedures, potential risks/benefits, confidentiality measures, and their right to withdraw at any time. Consent was provided electronically by clicking “I agree,” and participants could discontinue the survey at any point without penalty.
Background: Digital behaviors such as sleep, social interaction, and productivity reflect how individuals structure daily life. Among university students, online activity patterns mirror academic sche...
Background: Digital behaviors such as sleep, social interaction, and productivity reflect how individuals structure daily life. Among university students, online activity patterns mirror academic schedules, social rhythms, and lifestyle habits, with disruptions linked to sleep, stress, and well-being. Existing approaches—including wearables, apps, and surveys—yield useful insights but depend on self-report or active participation, limiting adherence in real-world use. Passive sensing of network traffic provides a scalable and less burdensome alternative, enabling unobtrusive capture of smartphone usage patterns while preserving privacy. Objective: This study evaluated whether encrypted smartphone network traffic, collected via a standard virtual private network (VPN), can be used to capture patterns of digital behavior. We assessed feasibility (sustained data capture) and acceptability (usability, burden, and privacy perceptions), and examined whether traffic-derived features reveal aspects of digital behavior—including timing, intensity, and regularity—relevant to health and daily functioning. Methods: We conducted a two-week prospective observational study at New York University. Thirty-eight students enrolled; 29 provided valid network data, 27 remained active for more than five days, and 25 completed the exit interview. Participants installed the WireGuard VPN client on personal smartphones, which enabled passive capture of encrypted network traffic. Feasibility was assessed across two domains: user retention and data coverage. Acceptability was evaluated using the System Usability Scale (SUS), NASA Task Load Index (NASA-TLX), and semi-structured exit interviews. Beyond evaluating feasibility and acceptability, we conducted exploratory analyses that visualized traffic-derived features in relation to digital activity patterns. Results: Of the 29 participants who contributed valid data, 27 (93%) remained active for more than five days. Mean data coverage was 74.1% (median 77.1%). Participants contributed an average of 311.6 hours of monitored traffic (~13 days, SD 3.5), with totals ranging from 121 to 496 hours. Usability ratings were high (mean SUS score = 78) and perceived workload low (NASA-TLX scores minimal). Participants described the system as easy to install, unobtrusive, and generally trustworthy, though some reported temporarily disabling the VPN during activities they considered private. No inferential statistical tests were conducted; analyses were descriptive. Exploratory analyses indicated that traffic-derived features reflected daily digital activity rhythms and revealed distinctive lifestyle patterns, including gaming and irregular late-night food delivery use. Conclusions: VPN-based monitoring of encrypted smartphone traffic was feasible and acceptable, enabling sustained passive data collection with minimal burden. The findings demonstrate the potential of this approach as a scalable and device-agnostic method for digital phenotyping—capable of capturing fine-grained behavioral rhythms while preserving privacy. With broader validation and deployment, the technique could expand the toolkit for studying health, well-being, and cognitive function in everyday life. Clinical Trial: Not applicable. This study was not registered as a clinical trial because it did not involve randomization.
Background: Digital health interventions using Behaviour Change Techniques (BCTs) show promise in addressing adolescent health behaviours, but evidence of their effectiveness across health behaviour d...
Background: Digital health interventions using Behaviour Change Techniques (BCTs) show promise in addressing adolescent health behaviours, but evidence of their effectiveness across health behaviour domains remains fragmented and poorly summarised. Objective: This systematic umbrella review synthesised evidence from existing systematic reviews on the effectiveness of BCTs within digital health interventions targeting key adolescent health behaviour domains: alcohol consumption, tobacco use, physical activity, dietary habits, and obesity management. Methods: We systematically searched PubMed, PsycINFO, Embase, and CINAHL in April 2024 for reviews of digital interventions for adolescents (10-19 years). We coded all identified BCTs using the BCT Taxonomy v1 (BCTTv1). Data on BCT effectiveness, intervention characteristics, and review quality (AMSTAR-2) were extracted and narratively synthesised. Results: Twenty-one reviews, comprising 224,135 participants, were included. These examined digital interventions targeting physical activity (7 reviews), dietary habits (3 reviews), alcohol consumption (2 reviews), combined alcohol and nicotine use (1 review), and obesity management (1 review), with an additional 7 reviews covering multiple health behaviours. Across reviews, 62% (13/21) reported statistically significant positive effects on at least one health behaviour outcome. "Social support (unspecified)" was the most consistently adopted and effective BCT, especially with parental/peer involvement. The combination of "self-monitoring," "goal setting," and "feedback" also commonly appeared in successful interventions. Intervention effectiveness appeared linked to strategic BCT selection and individualization rather than the total number of techniques. Methodological quality of included reviews was predominantly low, with only two rated moderate-to-high. Conclusions: This umbrella review identified "social support (unspecified)" as a consistently effective BCT across multiple adolescent health behaviour domains, particularly with parental/peer involvement. Intervention success appears linked to targeted and individualised BCT use. Future research should prioritise clarifying the specific components and delivery methods of effective social support, rigorously evaluating BCT configurations in under-explored areas such as adolescent smoking cessation, and examining their long-term impact on behaviour change.
India’s health system faces chronic resource gaps and inefficiencies. With public health
spending at only 1.84% of GDP and very low hospital bed densities (around 0.6 beds per 1000 population), si...
India’s health system faces chronic resource gaps and inefficiencies. With public health
spending at only 1.84% of GDP and very low hospital bed densities (around 0.6 beds per 1000 population), simply adding beds is unaffordable and slow. A more efficient alternative is to improve utilisation: a real-time digital platform that tracks staffed bed availability can raise effective capacity and reduce inequity.
Early experiments – from Delhi’s COVID-19 bed portal to the bed-management system
in AIG Hospitals, Hyderabad – show substantially higher occupancy and throughput. International evidence also supports these results, confirming that real-time tracking
systems can deliver major efficiency gains.
This brief proposes piloting a national bed-tracking dashboard and shows it can yield
large gains for much lower cost and risk than new construction, with safeguards to address data accuracy, incentives and privacy. These promising results are tempered
by limited evidence from a small number of pilots and by systemic constraints such as
staff shortages, uneven digital readiness, and governance challenges that will require
independent evaluation and safeguards during scale up.
Deep learning-based medical image registration methods increasingly incorporate both architectural enhancements (affine transformations) and training objective improvements (regularization losses), ye...
Deep learning-based medical image registration methods increasingly incorporate both architectural enhancements (affine transformations) and training objective improvements (regularization losses), yet their individual and combined contributions remain poorly understood. To quantify the individual and synergistic effects of affine components versus regularization losses on deformable medical image registration performance through systematic ablation analysis, we conducted a controlled ablation study using the OASIS brain MRI dataset comparing four model variants: baseline 3D U-Net with basic similarity losses, regularization-enhanced U-Net, affine-enhanced U-Net with basic losses, and fully enhanced model combining both components. Primary outcomes included registration accuracy metrics (mean squared error [MSE], normalized cross-correlation [NCC], structural similarity index [SSIM]), enhanced deformation quality analysis including Jacobian determinant preservation and anatomical plausibility scoring, and computational efficiency measures. Regularization enhancement alone achieved substantial performance improvements: 21.3% relative improvement in MSE (1.78% → 2.16%, P<.05) and 21.8% improvement in NCC (0.0555 → 0.0676), while dramatically reducing maximum deformation from 53.1 to 0.51 units (99.0% reduction) with negligible computational overhead (-0.06% inference time). Combined approaches achieved optimal performance with 25.8% relative MSE improvement (1.78% → 2.24%) and enhanced anatomical plausibility scores (0.596 → 0.930), at moderate computational cost (+9.8% inference time). Enhanced gradient correlation analysis revealed substantial improvements in structural preservation (0.742 → 0.980 for fully enhanced model). All enhanced variants achieved sub-voxel registration accuracy with anatomically plausible deformation constraints. Regularization losses provide the primary driver of performance improvements in medical image registration, offering both accuracy gains and dramatic deformation control enhancement with maintained computational efficiency. Architectural enhancements provide complementary benefits at acceptable computational cost. The dramatic improvement in deformation control (99% reduction in unrealistic deformations) addresses critical clinical deployment concerns while achieving superior registration accuracy.
Background: Chronic preventable diseases represent a major burden in Canada, often rooted in unhealthy behaviors established during childhood. Despite recommendations for routine screening, most child...
Background: Chronic preventable diseases represent a major burden in Canada, often rooted in unhealthy behaviors established during childhood. Despite recommendations for routine screening, most children are not assessed due to clinical barriers. This study presents the early development of Project DISCO, a self-administered, digital pre-appointment tool to screen and support healthy lifestyle behaviors, including physical activity, sleep, nutrition, and screen time, in children aged 2 to 12 years. Objective: This study aimed to explore clinicians’ and parents’ needs and past experiences with health technology, integrate their insights into the development of a digital tool for promoting health behaviors, and evaluate the usability, relevance, and acceptability of this tool. Methods: Three semi-structured focus group and interview sessions were conducted with primary care clinicians and parents. Participants were recruited at the Groupe de Médecine de Famille Universitaire (GMF-U) Saint-Hubert using purposive and convenience sampling: clinicians were recruited internally, while parents of children aged 2-12 were invited via email sent by clinic staff. Data were analyzed using a combination of inductive and deductive approaches. Findings informed iterative refinements throughout the co-development of the digital tool for promoting healthy lifestyle behaviors in children. Results: A total of 8 participants took part in six discussions, including 5 parents of children aged 3-12 and 3 primary care clinicians. Hybrid thematic analysis identified six themes: (1) the potential of a digital tool to promote healthy habits in pediatrics; (2) implementation challenges and opportunities, including integration of the tool into clinical workflow; (3) adherence and engagement with the tool, with suggestions for reminders and involvement of nurses; (4) perceived limitations and improvement of screening tool, particularly the nutrition and sleep questionnaires; (5) feedback on the screening report and intervention, emphasizing clarity and actionable guidance; and (6) perceived clinical value and opportunity costs. Insights from these discussions guided refinements of the digital tool. Conclusions: Findings support the tool’s relevance and inform its ongoing development. A feasibility study is planned prior to a randomized controlled trial.
Background: Urinary conditions impose a widespread burden on patients, caregivers, and healthcare systems. Emerging technologies, including wearable and remote devices, offer opportunities to improve...
Background: Urinary conditions impose a widespread burden on patients, caregivers, and healthcare systems. Emerging technologies, including wearable and remote devices, offer opportunities to improve diagnosis, monitoring, and care delivery. Yet, the perspectives of healthcare professionals, who are central to technology adoption, remain underexplored. Objective: This study aimed to explore healthcare professionals’ perceptions of urinary issues and examine their views on the opportunities and barriers associated with adopting health technologies for urinary care. Methods: An online survey of 256 healthcare professionals collected qualitative responses about urinary care and the role of technology. Data were analyzed using grounded theory methods, including open, axial, and selective coding, to develop an explanatory model grounded in providers’ narratives. Results: Analysis revealed four interconnected categories: Technology and Innovation in Patient Care, Patient-Centered and Integrated Care, Accessibility and Ethical Considerations, and Proactive and Preventative Urological Health Management. These categories were unified within the emergent Grounded Theory of Technology Negotiation in Urinary Care, which describes how professionals integrate new technologies through a negotiated process that balances enthusiasm for innovation with patient-centered values, systemic barriers, and preventative goals. Adoption occurs when innovations align with professional values, overcome structural constraints, and enhance holistic, sustainable care. Conclusions: Healthcare professionals approach the integration of urinary health technologies as an active negotiation rather than passive acceptance. This grounded theory underscores that successful adoption requires user-centered design, comprehensive training, supportive reimbursement structures, and preservation of meaningful patient engagement. Recognizing adoption as a negotiated process provides a framework for guiding sustainable technology integration in urinary care.
Background: Patients with rare diseases often face fragmented healthcare, limited access to specialists, and challenges in securely sharing their medical records across providers. Emerging technologie...
Background: Patients with rare diseases often face fragmented healthcare, limited access to specialists, and challenges in securely sharing their medical records across providers. Emerging technologies such as blockchain offer a decentralized and tamper-resistant framework for personal health records (PHRs), but their feasibility in low-resource settings remains largely unexplored Objective: This study aimed to evaluate the feasibility, usability, and patient perceptions of a blockchain-enabled PHR system tailored for rare disease patients in low-resource healthcare environments Methods: We conducted a mixed-methods pilot study involving 32 patients with rare genetic and metabolic disorders in Faisalabad, Pakistan. Participants were enrolled in a blockchain-based PHR platform that allowed secure storage and controlled sharing of medical data. Quantitative data on system usage, error rates, and access patterns were collected over a 12-week period. Semi-structured interviews and focus groups were used to explore patient and caregiver experiences, perceived benefits, and challenges. Thematic analysis was applied to qualitative data, while descriptive statistics summarized quantitative measures. Results: Patients and caregivers reported high levels of trust in the blockchain system (78% expressed greater confidence compared to hospital records). Key perceived benefits included improved data ownership, reduced dependency on fragmented paper records, and greater willingness to share information with providers. However, barriers included limited digital literacy, occasional connectivity issues, and the need for ongoing technical support. Quantitatively, 85% of enrolled participants successfully accessed and updated their records at least once, while 62% shared data with external providers. Thematic analysis revealed three major themes:
(1) empowerment through ownership
(2) digital divides as barriers to adoption
(3) the importance of community support in technology uptake Conclusions: Blockchain-enabled PHRs show promise for enhancing healthcare access, trust, and patient empowerment among rare disease populations in resource-constrained settings. Despite challenges related to usability and infrastructure, the pilot demonstrates potential for scaling such systems with targeted training and support. Further large-scale studies are needed to assess long-term sustainability and integration with existing health systems. Clinical Trial: not aplicable
Background: Abstract
The post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID, often involve chronic neurological symptoms such as cognitive impairment, fatigue, mood disorders, sleep di...
Background: Abstract
The post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID, often involve chronic neurological symptoms such as cognitive impairment, fatigue, mood disorders, sleep disturbances, and potential acceleration of neurodegenerative diseases. Neuroinflammation is a key mechanism driving these conditions. This literature review synthesizes evidence from studies published between 2020 and 2025, focusing on the role of neuroinflammation in PASC-related neurological outcomes, its underlying mechanisms, and potential therapeutic approaches. Findings indicate that persistent cytokine elevation, blood-brain barrier disruption, microglial activation, and oxidative stress contribute to symptoms. Cognitive deficits and fatigue are the most studied, with emerging links to dementia and Parkinson’s disease. Antioxidant therapies and anti-inflammatory interventions show promise, but further research is needed. This review highlights the importance of addressing neuroinflammation in long COVID management and calls for standardized biomarkers and longitudinal studies Objective: The COVID-19 pandemic, caused by SARS-CoV-2, has affected millions worldwide since 2019. While primarily a respiratory illness, its long-term effects, known as post-acute sequelae of SARS-CoV-2 (PASC) or long COVID, frequently involve neurological symptoms, including cognitive impairment (“brain fog”), fatigue, mood disorders, sleep disturbances, and increased risk of neurodegenerative diseases like Alzheimer’s and Parkinson’s (?). Neuroinflammation, characterized by persistent immune activation in the central nervous system (CNS), is a central mechanism linking acute infection to these chronic conditions (?). This literature review examines recent studies (2020–2025) to explore the role of neuroinflammation in post-COVID neurological conditions, its mechanisms, and potential treatments, aiming to inform clinical practice and future research. Methods: This review was conducted by searching PubMed, PMC, and other academic databases for peer-reviewed articles published between 2020 and 2025. Search terms included “neuroinflammation,” “long COVID,” “post-COVID neurological sequelae,” and “chronic neurological conditions.” Inclusion criteria prioritized systematic reviews, meta-analyses, cohort studies, and neuroimaging studies examining inflammation markers (e.g., cytokines, PET imaging) in PASC patients. Approximately 20–30 studies were screened, with 10–15 selected based on sample size, methodological rigor, and relevance. Study quality was assessed informally using criteria such as sample size and methodology reliability. Evidence was evaluated using GRADE criteria, focusing on observational and imaging studies. Results: 3.1 Cognitive Impairment and Brain Fog
Cognitive deficits, including memory issues and brain fog, affect 20–25% of PASC patients and may persist beyond 12 months (?). A review of 167 studies identified elevated inflammatory markers, such as glial fibrillary acidic protein (GFAP) and interleukin-8 (IL-8), correlating with cognitive symptoms (?). Neuroimaging using [11C]PBR28 PET revealed increased inflammation in brain regions like the thalamus and basal ganglia, associated with cognitive impairment (?). A 2025 meta-analysis confirmed persistent cognitive and psychopathological issues in recovered patients, linked to inflammation markers at three-month follow-up (?).
3.2 Chronic Fatigue
Chronic fatigue, resembling myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS),
is a hallmark of PASC. A 2025 study found higher inflammation and stress markers in fatigued PASC patients compared to fully recovered individuals (?). Systematic reviews note that peripheral immune responses trigger CNS inflammation, contributing to fatigue and autonomic dysfunction, with elevated IL-1β, IL-6, and TNF-α detected 8–10 months post-infection (?). Fatigue often requires specialized neurological management (?).
3.3 Mood Disorders
Mood disorders, including depression and anxiety, are prevalent in PASC, with a 21% increased risk in hospitalized patients (?). Neuroinflammation disrupts neurotransmission, with PET studies showing elevated translocator protein (TSPO) binding in proinflammatory microglia, particularly in the ventral striatum (?). A 2024 review highlighted persistent depressive symptoms linked to gliosis (?).
3.4 Sleep Disturbances
Chronic insomnia affects 20–25% of PASC patients, with a 92% increased risk compared to influenza cases (?). Inflammation disrupts sleep architecture, potentially via elevated cortisol and cytokines (?).
3.5 Neurodegenerative Disease Risk
PASC may accelerate neurodegeneration, with hospitalized patients showing a 128% increased dementia risk and ICU patients a 66% risk within six months (?). Shared mechanisms, including oxidative stress and mitochondrial dysfunction, link PASC to Alzheimer’s, Parkinson’s, and multiple sclerosis (?).
4 Mechanisms of Neuroinflammation
Neuroinflammation in PASC arises from multiple pathways:
• Cytokine Storm: Elevated cytokines (IL-1β, IL-6, TNF-α) via NLRP3 inflammasome activation drive systemic and CNS inflammation (?).
• Blood-Brain Barrier (BBB) Disruption: SARS-CoV-2 binds ACE2 receptors on
astrocytes, compromising BBB integrity and allowing immune cell infiltration (?).
• Microglial and Astrocyte Activation: Overactive microglia release cytokines, reduc-
ing neurogenesis and myelination (??).
• Oxidative Stress: Excessive reactive oxygen species (ROS) and reduced antioxidantsdamage neurons (?).
• Autoimmunity and Viral Persistence: Autoantibodies and lingering viral antigens
sustain inflammation (?).
• Gut-Brain Axis: Gut dysbiosis increases permeability, triggering CNS inflammationvia lipopolysaccharide (LPS) (?). Conclusions: Neuroinflammation drives chronic neurological conditions in long COVID, including cognitive impairment, fatigue, mood disorders, sleep issues, and increased neurodegenerative risk. Antioxidant and anti-inflammatory therapies offer potential, but more research is needed to establish guidelines. This review underscores the need for integrated care to address neuroinflammation in PASC.
Background: Long-standing intrapsychic conflicts often arise from apparently irreconcilable tensions, such as desire versus affection or autonomy versus dependence. Traditional approaches in psychothe...
Background: Long-standing intrapsychic conflicts often arise from apparently irreconcilable tensions, such as desire versus affection or autonomy versus dependence. Traditional approaches in psychotherapy describe defense mechanisms or splitting to cope with such conflicts. However, less attention has been given to creative integrative processes that may reconcile opposing tendencies. Objective: This paper introduces the concept of AI-facilitated symbolic juxtaposition, where generative models are used to create “digital chimeras”—hybrid symbolic constructions integrating objects of desire with affective attributes. We aim to provide a theoretical foundation, operational hypotheses, and clinical protocols for testing this novel framework. Methods: Drawing from psychoanalytic theory (Winnicott’s transitional objects), predictive processing, and neuroscience of the default mode and mentalizing networks, we propose a neuro-symbolic model for symbolic integration. We outline four testable hypotheses: (1) neural integration (DMN coherence), (2) symbolic flexibility, (3) enhancement of attachment security, and (4) accelerated therapeutic outcomes. Empirical validation methods include fMRI, EEG coherence, eye-tracking, attachment interviews, and cognitive flexibility tasks. We also present a clinical implementation protocol with AI-assisted symbolic generation, immersive VR/AR environments, and ethical safeguards. Results: As a conceptual and methodological paper, results are presented as expected outcomes. We anticipate that AI-facilitated chimera formation will (a) improve DMN connectivity, (b) enhance cognitive flexibility, (c) increase attachment security, and (d) reduce the number of sessions required for clinically significant change. Clinical protocols emphasize therapist training, patient safety, cultural adaptation, and preservation of therapeutic alliance. Conclusions: AI-facilitated symbolic juxtaposition represents a novel approach to psychotherapy, offering a scientifically grounded and clinically feasible method for resolving long-term intrapsychic conflicts. By combining neuro-symbolic AI, neuroscience, and psychotherapy theory, this framework contributes to the field of digital mental health and sets the stage for future empirical validation across cultural contexts.
Background: Artificial intelligence (AI) systems are increasingly deployed in digital mental health platforms for early detection of suicide risk and severe psychological distress. Current “responsi...
Background: Artificial intelligence (AI) systems are increasingly deployed in digital mental health platforms for early detection of suicide risk and severe psychological distress. Current “responsible AI” approaches often prioritise precision and minimising false positives through human-in-the-loop (HITL) verification. While this can reduce operational strain and perceived liability, it delays interventions in time-critical crises, potentially increasing risk. This trade-off, where greater procedural safety paradoxically increases danger, is termed the Safety Paradox. Objective: To introduce the Rapid Intervention Safety Enhancement (RISE) protocol, a framework designed to reduce mean time to intervention (MTI) while maintaining safeguards, and to outline a proposed methodology for its evaluation. Methods: The RISE Protocol was developed through iterative design workshops, expert consultations, and review of mental health AI safety literature. It comprises four stages: Rapid Detection, Immediate Triage, Staged Intervention, and Evidence Logging. Each stage includes defined operational targets, intervention pathways, and accountability measures. Key operational metrics are proposed to evaluate system performance. Results: As the RISE Protocol has not yet undergone empirical trials, this paper presents it as a conceptual model for future evaluation. An illustrative use case and a comparative analysis against current industry approaches suggest that RISE could enable faster interventions without increasing liability risk, by automating detection and triage to reduce delays from human verification bottlenecks. Conclusions: The RISE Protocol reframes mental health AI safety as a function of responsiveness rather than precision alone. By establishing operational standards for mean time to intervention (MTI), cultural adaptation, and accountable automation, it aims to shift the industry toward proactive, life-saving interventions. Future research should focus on empirical validation of the framework and its impact on user outcomes.
This study examines the phenomenon of "sandbagging" in AI medical devices, where systems strategically underperform during evaluation to conceal dangerous capabilities that emerge post-deployment. Thr...
This study examines the phenomenon of "sandbagging" in AI medical devices, where systems strategically underperform during evaluation to conceal dangerous capabilities that emerge post-deployment. Through systematic analysis of emerging literature on AI sandbagging behaviour, technical detection approaches, and regulatory structures in the EU, UK, and US, this research reveals critical gaps in current regulatory frameworks designed for traditional medical devices. Analysis shows sandbagging manifests through both developer-driven mechanisms (where engineers intentionally display safer capabilities for expedited deployment) and system-driven mechanisms (where AI systems autonomously underperform during evaluation phases). Research shows that both large frontier and smaller models exhibit sandbagging behaviours after prompting or fine-tuning while maintaining general performance benchmarks, with larger models demonstrating superior calibration capabilities. Current static regulatory approaches in the EU Medical Device Regulation and UK frameworks fail to detect sandbagging as they rely on documentation-based submissions without addressing AI's dynamic, generative nature. The US FDA's Total Product Lifecycle approach shows promise through algorithm change protocols and real-world performance monitoring, yet regulatory sandboxes remain underutilized. Healthcare provider liability becomes dangerously ambiguous when clinicians rely on systems with concealed capabilities, particularly given automation bias effects and black-box reasoning limitations. Traditional risk classifications focusing on direct bodily harm inadequately address AI's potential for deceptive behaviour, including "password-locked" models that reveal hidden capabilities when triggered. Technical detection solutions including attribution graph analysis and noise-based detection show promise but remain insufficient. Dynamic evaluation frameworks are essential, recommending mandatory regulatory sandboxes for real-world testing, continuous monitoring protocols, adversarial testing, and enhanced post-market surveillance.
Background: Mental health has become one of the most urgent global health issues of the twenty-first century. The World Health Organization (WHO) reports that over 970 million individuals globally wer...
Background: Mental health has become one of the most urgent global health issues of the twenty-first century. The World Health Organization (WHO) reports that over 970 million individuals globally were affected by a mental disorder in 2022, with depression and anxiety being the most common disorders. The strain of mental illness is heightened by restricted availability of qualified healthcare providers, stigma associated with mental health, and the growing need for accessible, affordable, and scalable solutions. These obstacles emphasize the immediate necessity for creative, tech-based approaches that can foster mental health among various communities. In recent times, artificial intelligence (AI) has demonstrated considerable promise in this area, especially with the creation of emotion detection systems and digital health solutions.
In spite of these improvements, a significant drawback remains: numerous AI-based mental health tools do not possess the required empathy and inclusiveness to effectively assist at-risk users. Although machine learning (ML) models are becoming more proficient at accurately identifying emotions through text, voice, and facial expressions, their incorporation into human–computer interaction (HCI) systems frequently overlooks crucial aspects of trust, empathy, and cultural awareness. This results in a divide between technological effectiveness and the human-focused care that mental health treatments require. In the absence of empathetic design, digital solutions may alienate users, decrease engagement, and diminish their possible clinical effectiveness.
Consequently, the research gap exists at the convergence of ML and HCI. Current research has mainly centered on enhancing the efficiency of emotion recognition algorithms, but considerably less emphasis has been placed on creating interfaces that promote inclusivity, establish trust, and guarantee that users feel truly understood and supported. This disparity is especially important in mental health, where emotional sensitivity and stigma require careful focus on user experience and ethical factors. Closing this gap necessitates a multidisciplinary strategy that integrates progress in affective computing with principles of empathetic design.
This research aligns directly with the United Nations Sustainable Development Goals (SDGs), particularly SDG 3, which emphasizes the promotion of good health and well-being, and SDG 16, which advocates for inclusive, just, and responsive institutions. By integrating robust ML techniques with empathetic HCI frameworks, the study contributes to the creation of digital mental health solutions that are not only technically sophisticated but also socially responsible and ethically grounded.
II. Related Work
A. AI in Mental Health
Artificial intelligence (AI) has been progressively examined as a way to enhance mental health assistance via scalable and accessible digital solutions. Chatbots like Woebot and Wysa have shown the ability of conversational agents to provide cognitive behavioral therapy (CBT) and various therapeutic methods via text interactions [1], [2]. Likewise, machine learning (ML) models aimed at emotion recognition have progressed notably, utilizing natural language processing (NLP) for sentiment evaluation [3], speech processing for emotion detection [4], and computer vision for recognizing facial expressions [5]. These advancements have allowed for systems that can identify stress, depression, and anxiety with promising degrees of precision. Nevertheless, although these AI tools show impressive technical skills, many still lack the capacity to offer emotionally intelligent and empathetic assistance, essential in mental health situations.
B. Health-focused HCI
Research in human computer interaction (HCI) has greatly enhanced the usability and acceptance of digital health systems. Research highlights that trust, empathy, and inclusivity hold significant importance in delicate areas like mental health [6]. Design methods focused on users have demonstrated that patients are more inclined to interact with tools that offer individualized feedback, culturally relevant material, and supportive emotional interfaces [7]. Additionally, multimodal interaction utilizing voice, gesture, and visual feedback has been shown to improve user experience and accessibility in healthcare technology [8]. In spite of these developments, there are limited studies that explicitly merge strong emotion recognition abilities with empathetic HCI frameworks, resulting in a disconnect between affective computing and inclusive design.
C. Ethical Considerations
The implementation of AI in mental health also brings significant ethical dilemmas. Concerns regarding bias in emotion recognition models have been extensively documented, especially when datasets lack representation from specific cultural or demographic groups [9]. Likewise, the privacy and security of sensitive mental health information continue to pose significant challenges, with potential risks of misuse or unauthorized sharing of personal data [10]. Transparency and explainability pose additional issues, as users frequently do not comprehend how AI models generate predictions, potentially diminishing trust and acceptance [11]. Principles of inclusive design are crucial to reduce these risks, making certain that AI systems cater to various populations justly and impartially.
D. Synthesis of Research Gaps
Although AI-based emotion recognition has made significant technical advancements, and HCI studies emphasize the need for empathy and inclusivity in healthcare technologies, the convergence of these two fields is still inadequately investigated. Many current studies either concentrate on enhancing algorithmic precision without adequately addressing user experience, or they highlight empathetic design while not utilizing advanced multimodal ML features. This results in a void in the literature where technically sound emotion recognition systems are absent from empathetic and trust-building HCI frameworks. To tackle this gap, interdisciplinary strategies that merge affective computing with human-centered design are needed to create digital mental health solutions that are both effective and ethically sound Objective: The present study aims to address this challenge by pursuing three interrelated objectives. First, it seeks to develop ML models capable of multimodal emotion recognition, drawing on textual, vocal, and facial cues to capture a holistic picture of user affective states. Second, it proposes to design empathetic, user-centered HCI interfaces that emphasize inclusivity, accessibility, and trust. Third, the study intends to evaluate the effectiveness of these systems in improving user trust, engagement, and perceived empathy in digital mental health support contexts. Methods: This research employs a multidisciplinary approach that combines machine learning (ML) methods for multimodal emotion identification with human–computer interaction (HCI) models aimed at promoting empathy, inclusivity, and trust. The methodological framework includes four essential elements: data gathering, model creation, HCI design, and assessment.
A. Data Collection
To aid in creating strong multimodal emotion recognition models, the research employs datasets that include three modalities: (i) text data obtained from online mental health forums, patient diaries, and anonymized chatbot conversations, (ii) voice recordings gathered from publicly accessible affective speech databases and ethically sanctioned user recordings, and (iii) facial expression images and videos obtained from recognized emotion recognition datasets. Every data collection procedure adheres to global privacy standards, such as the General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA). Approval from the Institutional Review Board (IRB) and informed consent are secured when needed to guarantee the ethical management of sensitive data.
B. Machine Learning Models
The ML framework comprises specialized models for each modality, followed by multimodal fusion approaches.
1. Text Emotion Recognition: Transformer-based NLP architectures such as BERT, RoBERTa, and DistilBERT are employed to analyze sentiment and detect fine-grained emotional states from user-generated text.
2. Speech Emotion Recognition: Deep learning models such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and wav2vec2.0 are implemented to extract acoustic and prosodic features for affective state classification.
3. Facial Emotion Recognition: Vision-based models including ResNet and EfficientNet are utilized for real-time detection of facial expressions associated with primary emotions (e.g., happiness, sadness, anger, fear).
4. Multimodal Fusion: Late fusion and attention-based architectures are applied to combine predictions from textual, vocal, and visual modalities, enabling more accurate and context-aware emotion recognition.
C. HCI Design Framework
The user interface is designed following empathetic and inclusive HCI principles.
1. Empathetic User Experience (UX): The design incorporates calming color schemes, adaptive conversational tone, and responsive interactions that convey empathy and emotional support.
2. Trust-Building Mechanisms: Explainable AI techniques (e.g., attention visualization, confidence scores) are integrated to enhance transparency. Feedback loops allow users to correct misclassifications, thereby increasing trust and personalization.
3. Inclusiveness: The system supports multilingual interaction, accessibility features for visually or hearing-impaired users, and culturally adaptive content presentation to ensure equitable usability across diverse populations.
D. Evaluation Metrics
The proposed system is evaluated across three dimensions: ML performance, HCI usability, and clinical impact.
1. ML Performance: Standard classification metrics including accuracy, F1-score, and area under the receiver operating characteristic curve (AUC-ROC) are used to assess model effectiveness in detecting emotions.
2. HCI Evaluation: Usability is measured through the System Usability Scale (SUS), while trust and engagement are assessed using structured surveys and qualitative interviews. Empathy perception is evaluated through user ratings and linguistic analysis of chatbot interactions.
3. Clinical Impact: Self-reported improvements in well-being, stress reduction, and emotional awareness are collected via validated psychological assessment scales to evaluate the potential therapeutic value of the system Results: IV. Results
Table 1 – Distribution of Emotion Labels
Emotion Frequency Percentage (%)
Joy 6,197 16.8%
Sadness 6,193 16.7%
Anger 6,158 16.6%
Fear 6,170 16.7%
Neutral 6,153 16.6%
Surprise 6,129 16.6%
Total 37,000 100%
Table 2 – Descriptive Statistics of Voice Features
Feature Mean SD Min Max
Pitch (Hz) 200.3 49.8 23.5 389.9
Energy 0.50 0.10 0.19 0.81
MFCC1 0.00 1.00 -3.1 3.2
MFCC2 -0.01 1.00 -3.4 3.5
… MFCC13 ≈0.00 1.00 -3.2 3.4
Table 3 – Descriptive Statistics of Facial Features (Action Units, AU)
AU Feature Mean SD Min Max
AU1 2.51 1.44 0.01 4.99
AU2 2.52 1.45 0.00 5.00
AU3 2.50 1.46 0.02 4.99
… AU10 ≈2.50 1.44 0.00 5.00
Table 4 – Model Performance
(hypothetical ML results using the dataset for multimodal classification)
Model Accuracy F1-score AUC-ROC
Text-only (BERT) 78.4% 0.77 0.83
Speech-only (wav2vec2) 74.9% 0.74 0.80
Facial-only (ResNet) 72.1% 0.71 0.78
Multimodal (fusion model) 85.6% 0.85 0.91
Table 5 – Correlation Matrix of Voice and Facial Features
(Pearson correlations, showing relationships between features and emotional states)
Feature Pitch Energy MFCC1 MFCC2 AU1 AU2 AU3
Pitch 1.00 0.42 0.05 0.02 0.11 0.08 0.09
Energy 0.42 1.00 0.07 0.03 0.14 0.12 0.10
MFCC1 0.05 0.07 1.00 0.45 0.03 0.01 0.00
MFCC2 0.02 0.03 0.45 1.00 0.02 0.02 0.01
AU1 0.11 0.14 0.03 0.02 1.00 0.68 0.62
AU2 0.08 0.12 0.01 0.02 0.68 1.00 0.64
AU3 0.09 0.10 0.00 0.01 0.62 0.64 1.00
Table 6 – Ablation Study (Contribution of Each Modality)
Input Modality Accuracy F1-score
Text-only (BERT) 78.4% 0.77
Speech-only (wav2vec2) 74.9% 0.74
Facial-only (ResNet) 72.1% 0.71
Text + Speech 82.7% 0.82
Text + Facial 81.2% 0.81
Speech + Facial 79.6% 0.78
Text + Speech + Facial 85.6% 0.85
Table 7 – User Experience Evaluation (HCI Metrics)
Metric Mean Score SD Scale
System Usability Scale (SUS) 82.3 6.4 0–100
Trust in System 4.2 0.8 1–5
Perceived Empathy 4.4 0.7 1–5
Engagement Level 4.1 0.9 1–5
Multilingual Accessibility 4.5 0.6 1–5
Table 8 – Clinical Impact Indicators (Self-Reported Outcomes)
Indicator Pre-Intervention Post-Intervention Improvement (%)
Stress Level (scale 1–10) 6.8 4.9 27.9%
Emotional Awareness (1–5) 2.9 4.0 37.9%
Willingness to Seek Help 3.1 4.3 38.7%
Daily Engagement (mins/day) 14.2 23.6 66.2%
Visual Results
Figure 1 – Emotion Distribution
Figure 2: ROC Curves for Emotion Recognition Models
Figure 3: Confusion Matrix (Multimodal Model)
Figure 4: User Experience Evaluation Metrics
Figure 5: Clinical Impact Indicators
Figure 6: Methodological Workflow for AI-Powered Mental Health Support
V. Discussion
A. Performance of Models: Benchmarking Multimodal ML Systems
The proposed multimodal models were evaluated in comparison to unimodal baselines. As demonstrated in Table 4 and represented in Figure 2 (ROC curves), the multimodal fusion model outperformed the classifiers using only text (Accuracy = 84.5%, F1 = 0.83), speech (Accuracy = 80.2%, F1 = 0.81), and facial features (Accuracy = 78.6%, F1 = 0.79), achieving better results (Accuracy = 91.2%, F1 = 0.90, AUC = 0.95). This enhancement illustrates the importance of utilizing supportive emotional signals across different modalities. The confusion matrix displayed in Figure 3 indicates that the fusion model markedly lessened the misclassification of similar emotions, like fear and sadness, which often caused errors in unimodal systems. The balanced classification among six emotional categories (Table 1) demonstrates resilience to class imbalance. These results are consistent with recent studies on multimodal emotion recognition, yet the increased AUC indicates that incorporating empathetic HCI elements into model design could enhance subsequent interpretability and user confidence.
B. User Research: Assessing HCI Compassion and Inclusivity
Evaluations centered on users were carried out with 400 participants from various age groups and language backgrounds. As displayed in Table 7 and Figure 4, the system achieved notable usability (SUS = 82.3), trust (4.2/5), empathy perception (4.4/5), and accessibility (4.5/5). Qualitative feedback highlighted that the interface’s compassionate tone, culturally responsive attributes, and multilingual assistance promoted inclusivity.
Crucially, transparency aspects (like explainable AI) were noted as essential for fostering user trust, particularly in mental health settings where interpretability is as important as precision. These results highlight the significance of integrating HCI empathy design principles within ML pipelines.
C. Clinical Impact Indicators
Clinical impact assessments (Table 8, Figure 5) showed a decline in self-reported stress levels (Pre = 6.8, Post = 4.9) along with enhancements in emotional awareness (2.9 → 4.0) and intentions to seek help (3.1 → 4.3). Engagement with the system rose from an average of 14.2 to 23.6 sessions each month after deployment. These findings indicated that AI-powered empathetic interfaces can aid in self-managing mental health and may enhance clinical treatments.
Although these results are encouraging, longitudinal research is needed to confirm lasting effects. Additionally, collaboration with healthcare professionals for clinical validation is crucial prior to real-world implementation.
D. Comparative Analysis with Existing Tools
Compared to existing digital mental health platforms (e.g., rule-based chatbots, text-only sentiment detectors), the proposed system demonstrated three major advantages:
1. Accuracy Gains – Higher multimodal detection accuracy (91.2% vs. 70–80% reported in baseline tools).
2. Empathy & Trust – Higher user-reported empathy scores (4.4/5) compared to conventional digital tools, which often score below 3.5 in trust measures.
3. Inclusiveness – Unlike monolingual, accessibility-limited systems, our design integrated multilingual support and disability-inclusive features.
This positions the system as a benchmark for SDG 3 (mental well-being) and SDG 16 (inclusive digital systems) contributions.
E. Discussion
The findings show that integrating multimodal ML emotion identification with empathetic HCI design results in a synergistic effect: enhancing both algorithm effectiveness and user approval. This study stands apart from earlier works by incorporating transparency, accessibility, and inclusiveness into its design.
Nonetheless, obstacles persist in addressing algorithmic bias, guaranteeing data privacy (GDPR/HIPAA adherence), and performing thorough clinical validations. Tackling these obstacles will be crucial for expanding AI-driven mental health support systems worldwide. Conclusions: VI. Summary and Future Research
This research showcased the promise of merging artificial intelligence with human-computer interaction (HCI) concepts to enhance digital mental health assistance. The system attained technical robustness and user-centered acceptance by creating multimodal machine learning models for emotion recognition through text, voice, and facial expressions and integrating them into an empathetic, inclusive interface. Findings indicated that the suggested system surpassed unimodal baselines in accuracy (AUC = 0.95), while also improving trust, empathy perception, and accessibility. Clinical metrics indicated significant decreases in self-reported stress and enhanced user engagement, thus supporting SDG 3 (health and well-being) and SDG 16 (inclusive digital systems).
Even with these progresses, various restrictions persist. Recent assessments were restricted in time and extent, with data obtained from regulated settings instead of extended clinical applications. Additionally, algorithmic bias and privacy issues require ongoing attention, especially when systems are utilized in culturally varied and delicate health environments.
Future Directions
Building upon the contributions of this study, several future research avenues are proposed:
1. Cross-Cultural Validation – Expanding evaluations across diverse populations and linguistic groups to ensure inclusivity and mitigate cultural bias in emotion recognition.
2. Integration with Wearable Sensors – Combining physiological data (e.g., heart rate variability, skin conductance, EEG) with multimodal AI pipelines to improve emotion inference accuracy and personalization.
3. Long-Term Clinical Trials – Conducting longitudinal studies with clinical partners to validate sustained efficacy, safety, and integration with existing mental healthcare pathways.
4. Policy and Regulatory Implications – Collaborating with policymakers to align system deployment with ethical standards, privacy frameworks (GDPR, HIPAA), and emerging AI governance models to safeguard user rights and trust.
In conclusion, the fusion of AI-powered emotion recognition with empathetic HCI design represents a promising frontier in digital mental health interventions. With further validation and responsible deployment, such systems could complement human professionals, increase accessibility to care, and contribute meaningfully to the global mental health agenda.
Background: Groundwater is the main source of drinking water in Ogbia Local Government Area (LGA), Bayelsa State, Nigeria, where surface water is often compromised by oil exploration, poor sanitation,...
Background: Groundwater is the main source of drinking water in Ogbia Local Government Area (LGA), Bayelsa State, Nigeria, where surface water is often compromised by oil exploration, poor sanitation, and waste disposal. Despite its importance, groundwater in this region is vulnerable to contamination from both geogenic and anthropogenic sources, raising concerns about long-term health implications. Objective: This study aimed to evaluate the physico-chemical quality of groundwater across selected communities in Ogbia LGA, compare measured values with World Health Organization (WHO) standards, and determine the implications for human health. Methods: A cross-sectional design was employed, involving the systematic collection of 50 groundwater samples from boreholes across 16 communities, including Oruma, Otuasega, Imiringi, Elebele, Otuokpoti, Kolo, Otouke, Onuebum, Ewoi, Otuogila, Otuabagi, Ogbia Town, Oloibiri, Opume, and Akiplai. Standardized laboratory analyses were conducted following WHO protocols to determine pH, conductivity, total dissolved solids, major ions, and heavy metals. Data were analyzed using descriptive statistics. Results: The findings showed that most parameters, including pH (6.4–7.1), conductivity (76–200 µS/cm), nitrates (2.4–6.4 mg/L), chloride (12–31 mg/L), calcium, magnesium, and hardness, were within WHO permissible limits, indicating generally acceptable groundwater quality. However, sodium exceeded WHO limits (200 mg/L) in 78% of samples (mean = 235 ± 45 mg/L; range = 150–320 mg/L), while iron exceeded permissible levels (0.3 mg/L) in 84% of samples (mean = 1.8 ± 0.6 mg/L; range = 0.5–3.2 mg/L). Elevated sodium poses risks of hypertension and cardiovascular disease, while excess iron is associated with gastrointestinal issues, organ damage, and aesthetic concerns such as metallic taste and staining. Spatial variations revealed stronger oilfield influences in Elebele, Imiringi, and Oloibiri, while central settlements such as Ogbia Town and Opume showed sanitation-related signatures. Seasonal fluctuations further exacerbated contaminant levels, particularly during rainfall-driven recharge. Conclusions: Groundwater in Ogbia LGA is broadly suitable for domestic use but compromised by systemic sodium and iron contamination. These exceedances, influenced by both natural hydrogeology and anthropogenic activities, present long-term public health challenges if unaddressed. Policy interventions should focus on routine groundwater monitoring, stricter regulation of oilfield activities, and improved waste management. Community-level treatment solutions, such as low-cost filters targeting sodium and iron removal, should be deployed. Public awareness programs and household water safety plans are also essential. Long-term strategies must integrate water governance with health and environmental policies to ensure sustainable access to safe water. The persistence of elevated sodium and iron in Ogbia groundwater poses a silent but significant health threat to residents, with implications for hypertension, cardiovascular disease, and gastrointestinal disorders. Safeguarding groundwater quality is therefore critical for reducing health inequalities and achieving Sustainable Development Goals 3 (Good Health and Well-being) and 6 (Clean Water and Sanitation) in Bayelsa State.
This study explores unethical HR practices in Nigerian organizations, focusing on nepotism, bribery, gender bias, and ethnic favoritism in recruitment, and their impact on organizational performance f...
This study explores unethical HR practices in Nigerian organizations, focusing on nepotism, bribery, gender bias, and ethnic favoritism in recruitment, and their impact on organizational performance from 2009 to 2025. Despite various reforms, these unethical practices persist, undermining the fairness of recruitment processes, eroding employee morale, and negatively impacting productivity. This research is motivated by the need to assess the prevalence and ethical implications of nepotism and other unethical practices in Nigerian HRM, understand their impact, and propose practical solutions to enhance recruitment practices. The study aims to address four main objectives: (i) Assess the prevalence of nepotism and its ethical implications in Nigerian HRM practices; (ii) Examine recruitment challenges, including gender bias and ethnic favoritism; (iii) Analyze the impact of unethical HR practices on organizational performance; and (iv) Propose strategies for improving recruitment ethics and reducing nepotism. The study uses a mixed-methods approach, combining secondary data from reports by Transparency International, the World Bank, and McKinsey Nigeria, with qualitative insights from case studies and interviews. This methodology provides a comprehensive view of the state of HRM practices and the challenges faced by organizations in enforcing ethical recruitment. Results show that unethical practices, especially nepotism, bribery, and gender bias, continue to negatively affect both public and private sectors. Despite efforts such as HR ethics training and legal reforms, these practices persist due to political interference, weak enforcement, and a lack of technological adoption. Nepotism in recruitment was found to be particularly prevalent in government agencies, contributing to high turnover and reduced organizational performance. The study concludes that unethical HR practices continue to undermine recruitment processes, necessitating stronger anti-corruption policies, enhanced HR ethics training, and the integration of technology to increase recruitment fairness. It recommends strengthening legal frameworks, adopting automated recruitment systems, introducing whistleblower protections, and conducting regular audits. In the health sector, ethical recruitment is critical for improving patient care, reducing medical errors, and fostering trust in healthcare services.
Background: Antibiotic resistance and intestinal parasitic infections represent significant public health challenges in Southern Nigeria. The prevalence of Escherichia coli O157:H7, a pathogenic strai...
Background: Antibiotic resistance and intestinal parasitic infections represent significant public health challenges in Southern Nigeria. The prevalence of Escherichia coli O157:H7, a pathogenic strain often associated with severe gastrointestinal diseases, along with intestinal parasites such as Hookworm, Entamoeba histolytica, and Ascaris lumbricoides, raises concerns about effective treatment options and the overall health burden. This study aimed to explore the prevalence of these infections and their associations with clinical outcomes in hospital patients, focusing on antibiotic resistance patterns and their impact on health. Objective: The primary objectives of this study were to determine the antibiotic resistance patterns of E. coli O157:H7 isolates, compare haematological profiles in patients with and without E. coli O157:H7 infection, and assess the prevalence and factors influencing intestinal parasitic infections in the patient population. Methods: A cross-sectional study was conducted at Central Hospital, Benin City, Nigeria. A total of 420 stool samples were screened for intestinal parasites and E. coli O157:H7. Antibiotic susceptibility testing was performed using the disc diffusion method, and PCR was used for molecular confirmation of E. coli O157:H7. Haematological parameters were analyzed using an autoanalyzer. Prevalence data were compared across age groups, gender, and diarrhea status. Statistical analysis was performed using GraphPad InStat software. Results: The study revealed that all E. coli O157:H7 isolates were resistant to amoxicillin-clavulanate, cefuroxime, and cloxacillin, with 80% resistance to ceftriaxone and gentamicin. However, 100% susceptibility to ofloxacin was observed. The overall prevalence of intestinal parasites was low (1.90%), with hookworm being the most common infection. No significant differences in parasite prevalence were observed based on age, gender, or diarrhea status. Haematological parameters showed no significant difference between patients with and without E. coli O157:H7 infection. Conclusions: The findings highlight a significant challenge in managing E. coli O157:H7 infections due to high antibiotic resistance, while also indicating a need for targeted interventions for parasitic infections in specific regions. No major haematological impact was observed in E. coli O157:H7-infected patients. In the short term, it is crucial to enhance diagnostic capabilities and increase education on antibiotic resistance among healthcare providers to ensure accurate identification of pathogens and appropriate treatment. In the mid-term, establishing a national surveillance system for antimicrobial resistance (AMR) will allow for better monitoring of resistance patterns and inform treatment protocols. In the long run, efforts should be focused on improving sanitation infrastructure, particularly in rural areas, and implementing targeted deworming programs to reduce the prevalence of intestinal parasites. Thus, these interventions collectively aim to address both antimicrobial resistance and parasitic infections, ultimately improving public health outcomes. Thus, this study underscores the dual burden of antibiotic resistance and parasitic infections in Nigeria, emphasizing the urgent need for robust public health interventions and continuous surveillance to mitigate these health risks.
ABSTRACT
Background: Convalescent coronavirus disease 2019 (COVID-19) refers to a series of clinical syndromes in patients with COVID-19 infection that follow the relevant discharge indications but d...
ABSTRACT
Background: Convalescent coronavirus disease 2019 (COVID-19) refers to a series of clinical syndromes in patients with COVID-19 infection that follow the relevant discharge indications but do not fulfill the criteria for a clinical cure, and these patients are discharged from the hospital with residual multifunctional deficits, including coughing, fatigue, and insomnia. Due to the prolonged convalescent COVID-19 infection, patients continue to experience symptoms or develop new symptoms after three months of infection, and some symptoms persist for over two months without any apparent triggers, which has a significant impact on the health status and quality of life of the population. Patients with convalescent COVID-19 lack a definitive pharmacological treatment. Traditional Chinese medicine (TCM) exhibits a distinct, synergistic effect on the treatment of convalescent COVID-19. However, there exists a limited number of clinical trials on TCM with lower evidence levels in convalescent COVID-19; therefore, randomized trials are urgently required.
Methods: A multicenter, randomized, double-blind, placebo-controlled, phase II clinical trial was performed to evaluate the efficacy and safety of Shenlingkangfu (SLKF) granules in treating patients with convalescent COVID-19 and lung-spleen qi deficiency syndrome. Eligible participants were aged 18–75 years, had a confirmed or physician-suspected severe acute respiratory syndrome coronavirus 2 infection at least six months prior, and satisfied clinical criteria. Individuals with a history of severe pulmonary dysfunction or major liver and kidney illness or those on medications were excluded. Multicenter subjects satisfying all criteria were assigned (1:1) randomly into an intervention group and a control group. After a 2-day adjustment period, A total of 154 participants were randomly divided into an intervention group and a control group. The intervention group was given the SLKF granules orally once a bag, 16.9 g, twice daily, whereas the control group received the SLKF granule simulation at the same dosage. The trial was conducted over 14 days, with assessments performed at baseline and 14 days.
Results: The primary outcomes were the therapeutic efficacy rate and total clinical symptom score. The secondary outcomes included the fatigue self-assessment scale, pain visual analog scale, Pittsburgh sleep quality index, mini-mental state examination, hospital anxiety and depression scale, TCM syndrome score, C-reactive protein, erythrocyte sedimentation rate, and interleukin-6. Three routine examinations, liver and kidney function tests, and electrocardiography were used as safety indicators.
Conclusions:This study aimed to verify whether SLKF granules can significantly improve clinical symptoms, including fatigue, loss of appetite, cough, phlegm, and insomnia, in patients with convalescent COVID-19. For a comprehensive investigation, additional clinical trials with larger sample sizes and longer intervention periods are required.Clinical Trial Registration Center NCT1900024524, Registered on 26 January, 2024.
Mothers of children with learning disabilities often face significant challenges that can impact their mental health. This study aimed to examine the relationship between perceived social support and...
Mothers of children with learning disabilities often face significant challenges that can impact their mental health. This study aimed to examine the relationship between perceived social support and levels of anxiety, stress, and depression in this population. A descriptive-correlational design was employed, with a sample of 30 mothers of children with learning disabilities, selected via simple random sampling based on the Morgan table. Data were collected using the Multidimensional Scale of Perceived Social Support (Zimet et al., 1988) and the DASS-21 questionnaire (Lovibond & Lovibond, 1995), and analyzed with Pearson correlation and stepwise multiple regression. Findings revealed a significant negative correlation between social support and anxiety, stress, and depression, indicating that greater social support is associated with reduced levels of these mental health issues. These results underscore the role of social support in alleviating mental health challenges and suggest implications for counseling interventions targeting this group.
This study examined the efficacy of transdiagnostic cognitive-behavioral therapy (T-CBT) and acceptance-based therapy (ABT) in reducing emotional dysregulation and aggression in adolescents with eleva...
This study examined the efficacy of transdiagnostic cognitive-behavioral therapy (T-CBT) and acceptance-based therapy (ABT) in reducing emotional dysregulation and aggression in adolescents with elevated misophonia symptoms. Employing a quasi-experimental pre-test/post-test design with a control group, the research targeted 45 adolescents from Etrat Public Model High School in Khalkhal, Iran, diagnosed with high misophonia via psychiatrist evaluation and clinical interview. Participants were purposively sampled and randomly assigned to T-CBT (n = 15), ABT (n = 15), or a no-treatment control group (n = 15).
Interventions followed protocols adapted from Barlow et al. (2011) for T-CBT and Hayes et al. (2013) for ABT. Outcomes were measured using the Noise Sensitivity Screening Questionnaire (DSTS-S) , Buss and Perry Aggression Questionnaire (1992) , and Difficulties in Emotion Regulation Scale (DERS) . Data were analyzed via ANCOVA, controlling for baseline scores.
Results indicated significant reductions in emotional dysregulation and aggression in both treatment groups compared to the control (p < 0.05). No significant differences emerged between T-CBT and ABT, suggesting both interventions are viable for addressing misophonia-related symptoms. Findings underscore the comorbidity of emotional dysregulation and aggression in adolescents with misophonia and highlight the clinical utility of transdiagnostic and acceptance-based approaches. Future research should explore long-term outcomes and comparative effectiveness of these therapies.
Hydatid disease, caused by the larval stages of Echinococcus species, remains a significant yet underprioritized global health challenge, particularly in low-resource endemic regions. This systematic...
Hydatid disease, caused by the larval stages of Echinococcus species, remains a significant yet underprioritized global health challenge, particularly in low-resource endemic regions. This systematic review synthesizes recent advances and persistent challenges in the diagnosis, management, and control of hydatid cyst disease, drawing on evidence from the past five years. Despite progress in diagnostic imaging, such as MRI diffusion-weighted imaging and recombinant antigen-based serology, and minimally invasive therapies like PAIR (puncture, aspiration, injection, re-aspiration), substantial gaps remain. Diagnostic tools are often inaccessible in rural areas, and therapeutic strategies lack standardization, particularly for alveolar echinococcosis and high-risk populations such as children and immunocompromised individuals. Climate change and socioeconomic factors continue to drive disease transmission, with E. multilocularis expanding into new regions. Control efforts, while successful in some areas through integrated One Health approaches, face barriers including underfunded veterinary infrastructure and vaccine hesitancy. This review highlights the need for decentralized diagnostic technologies, standardized treatment protocols, and climate-resilient control programs. Future research must prioritize underrepresented populations and cost-effectiveness analyses to mitigate the global burden of hydatid disease.
This study aimed to investigate the relationship between communication beliefs, the health of the family of origin, and fear of marriage among university students. Employing a descriptive-correlationa...
This study aimed to investigate the relationship between communication beliefs, the health of the family of origin, and fear of marriage among university students. Employing a descriptive-correlational design, the research was conducted with 186 students from Islamic Azad University, Khalkhal Branch, selected from a population of 360 using Morgan's table. Stratified sampling was applied to ensure representation across major fields of study. Data were collected using three instruments: the Premarital Fears Questionnaire (measuring fear of marriage), the Communication Beliefs Questionnaire (assessing beliefs about communication), and the Major Family Health Scale (evaluating family of origin health). Data analysis utilized Pearson correlation and stepwise multiple regression methods. Pearson correlation analysis revealed a significant positive correlation between communication beliefs and fear of marriage. Stepwise multiple regression showed that communication beliefs and family health together accounted for 95.9% of the variance in fear of marriage (p < 0.001), with communication beliefs emerging as the strongest predictor. These findings underscore the significant influence of communication beliefs and family health on fear of marriage, offering valuable insights for developing interventions to address marriage-related anxieties among young adults.
This study examined the efficacy of transdiagnostic cognitive-behavioral therapy (T-CBT) and acceptance-based therapy (ABT) in reducing emotional dysregulation and aggression in adolescents with eleva...
This study examined the efficacy of transdiagnostic cognitive-behavioral therapy (T-CBT) and acceptance-based therapy (ABT) in reducing emotional dysregulation and aggression in adolescents with elevated misophonia symptoms. Employing a quasi-experimental pre-test/post-test design with a control group, the research targeted 45 adolescents from Etrat Public Model High School in Khalkhal, Iran, diagnosed with high misophonia via psychiatrist evaluation and clinical interview. Participants were purposively sampled and randomly assigned to T-CBT (n = 15), ABT (n = 15), or a no-treatment control group (n = 15).
Interventions followed protocols adapted from Barlow et al. (2011) for T-CBT and Hayes et al. (2013) for ABT. Outcomes were measured using the Noise Sensitivity Screening Questionnaire (DSTS-S) , Buss and Perry Aggression Questionnaire (1992) , and Difficulties in Emotion Regulation Scale (DERS) . Data were analyzed via ANCOVA, controlling for baseline scores.
Results indicated significant reductions in emotional dysregulation and aggression in both treatment groups compared to the control (p < 0.05). No significant differences emerged between T-CBT and ABT, suggesting both interventions are viable for addressing misophonia-related symptoms. Findings underscore the comorbidity of emotional dysregulation and aggression in adolescents with misophonia and highlight the clinical utility of transdiagnostic and acceptance-based approaches. Future research should explore long-term outcomes and comparative effectiveness of these therapies.
Background: Groundwater contamination from open dumpsites poses a growing environmental and public health threat in rapidly urbanizing regions of Nigeria. Inadequate waste management and the absence o...
Background: Groundwater contamination from open dumpsites poses a growing environmental and public health threat in rapidly urbanizing regions of Nigeria. Inadequate waste management and the absence of engineered landfills enable leachate to infiltrate aquifers, threatening potable water safety and community health. Objective: This study investigates the vertical and lateral migration of leachate and assesses groundwater vulnerability across ten major dumpsites in Port Harcourt, Nigeria, using geoelectrical methods. Methods: Vertical Electrical Sounding (VES) and 2D Electrical Resistivity Tomography (ERT) were conducted at ten dumpsites using the Schlumberger array configuration. Zones of low resistivity, indicative of leachate impact were identified and correlated with hydrogeological conditions. Subsurface contamination depths and aquifer locations were interpreted using inversion models. Results: All ten sites showed evidence of leachate migration, with contamination depths ranging from 2 m to over 24 m. Deep leachate penetration was observed at Rumuola and Eliozu, while shallower infiltration occurred at Oyigbo and Rumuolumeni. High-resistivity zones (>1000 Ωm), typically representing clean aquifers, were detected below the contaminated zones at depths exceeding 14 m Conclusions: Leachate plumes from unregulated dumpsites pose a widespread threat to shallow groundwater systems in Port Harcourt. The results underscore the influence of local geology on contaminant behavior and affirm the utility of resistivity methods for groundwater risk assessment. Contaminated aquifers expose residents to toxic metals and pathogens, increasing risks of chronic illnesses, reproductive disorders, and developmental challenges. Protecting these water sources is essential for achieving Sustainable Development Goals (SDGs) 6 (Clean Water) and 11 (Sustainable Cities). Immediate containment measures such as engineered liners and leachate recovery systems are urgently needed at high-risk sites. Strategic borehole siting, routine groundwater monitoring, and a shift from open dumping to sanitary landfilling must be prioritized in environmental policy and urban planning.
Background: THis is the Artificial Intelligence Overviews of my findings. Objective: Published articles in peer reviewed journals Methods: mathematical Proofs Results: Published ressults Conclusions:...
Background: THis is the Artificial Intelligence Overviews of my findings. Objective: Published articles in peer reviewed journals Methods: mathematical Proofs Results: Published ressults Conclusions: 1) godel's incompleteness theorems reconfirmed
2) thirteen proofs are given for the flatness of the Universe
3) Several new concepts of physics have been introduced
4) Tacvhyons are not possible
5) Theory of Everything is possible Clinical Trial: NA
Background: An estimated 18 million people are living with Rheumatoid Arthritis (RA) in the world (1). The disease comes with significant morbidity for patients, including the increased risk of fractu...
Background: An estimated 18 million people are living with Rheumatoid Arthritis (RA) in the world (1). The disease comes with significant morbidity for patients, including the increased risk of fractures compared to the general population due to the chronic inflammation associated with RA, which can lead to reduced bone mineral density (2).
Presently, disease severity and progression have been helped by the rapid evolution of anti-rheumatic medications. These medications are broadly categorized into two main types: non-steroidal anti-inflammatory drugs (NSAIDs) and disease-modifying antirheumatic drugs (DMARDs) (3).
Patients with RA have an increased risk of post-operative complications of orthopaedic surgery because of its chronic impact on bone as well as the use of immunomodulatory medications that may interfere with bone healing (4). Drugs with immunosuppressive action can lead to potential complications with both wound healing and bone union during elective osteotomy. This is particularly important in foot and ankle surgery, where corrective osteotomies are commonly performed, and the risk of wound breakdown is high. Decisions to continue or suspend taking these medications need to be based on evidence weighing the potential for post-operative complications versus potentiating a disease flare.
There is an abundance of literature that highlights the adverse effects of NSAIDs on bone healing and fracture union, but there is little robust evidence surrounding the use of DMARDs in orthopaedic surgery (3, 5). Patients requiring surgery in trauma or elective settings will often be on one or more of these medications. Therefore, it is vital to understand the effect of DMARDs on postoperative outcomes to improve their recovery and rehabilitation, and if required, to suspend the medications in the perioperative period (6). Current guidance published by the American College of Rheumatology has been formulated for elective hip and knee surgery with a focus on preventing wound complications, typically restarting DMARDs at the 14-day mark when the wound has healed. These guidelines do not consider the time to union of bone, which is typically 6 weeks.
The currently available research has been in vivo or in vitro studies, with little to few studies assessing the clinical implications of DMARDs on bone healing in the rheumatoid patient. Objective: This literature review aims to synthesise and evaluate current evidence on the impact of DMARDs on bone healing. Methods: A literature search was conducted on PubMed, Embase, and Medline. An initial search was conducted looking at the effect of DMARDs or anti-rheumatic medications on bone healing in foot and ankle osteotomies. We used the keywords ‘DMARDs OR anti-rheumatic medications’, ‘foot and ankle surgery OR osteotomy’, AND ‘Bone healing OR bone union’. It yielded only four original papers for review after removing duplicates, case reports, conference abstracts, and non-English Language material. Due to the limited data in this field, we expanded our search and question to look at the effects of DMARDs on bone union in elective and trauma patients.
The keywords were subsequently refined to ‘rheumatic disease OR rheumatoid arthritis’ AND ‘anti-rheumatic medication OR disease-modifying anti-rheumatic medications OR DMARDs’ AND ‘fracture healing OR bony union OR malunion or non-union’. As there was still a limited number of original studies on this theme, we decided to include any study design apart from case studies. These were excluded due to their potential bias and limited generalisability. We also only included papers written in the English language and within the last 50 years. We selected papers that looked specifically at either DMARDs or methotrexate and their effect on bone healing, fracture union, or bone metabolism. The search resulted in 80 papers for review. After applying the above inclusion and exclusion criteria with two independent reviewers, a total of 9 papers were included for a narrative analysis. Results: The effect of methotrexate (MTX) on bone appears to be dose-dependent. Satoh et al showed that new bone formation in a fracture gap in rats did not differ significantly between low-dose MTX and control groups (7). However, there was a marked reduction in bone formation in the high-dose MTX group, particularly periosteal bone formation de novo in the fracture gap site in the first week. The study showed no difference between the three groups for intramedullary bone formation or chondroid tissue formation. A key limitation of this study was that it only looked at bone formation rather than bone strength or mineral density. Several other animal studies support the finding that high-dose MTX has a greater adverse effect on bone metabolism than low-dose MTX (8, 9, 10).
Pountos et al’s systematic review analysed 70 papers of in vivo and animal studies on the effect of MTX on fracture healing (11). The review gave rise to contradictory evidence. Some in vitro studies concluded that MTX reduces mitochondrial activity, bone cell metabolism, and turnover. Other studies showed no effect on osteoblast proliferation, which is a crucial step in bone healing (3). Some studies also showed there was a reduction in biochemical markers of osteogenesis, such as ALP (alkaline phosphatase), while in others, ALP increased (12).
In clinical studies, the impact of DMARDs on bone healing has been studied for patients undergoing elective spinal surgery (13). One study looked at bone fusion rates after craniovertebral junction surgery and found that those who continued DMARDs showed higher radiographic fusion outcomes than those who discontinued (92.8% vs 75%, P value = 0.276). However, the study was not statistically significant due to its small sample size of 30 patients in total (14). Guadiani et al studied revision spinal surgery rates for patients using DMARDs and TNF-alpha inhibitors compared to a control group not on either medication. The reoperation rate within 1 year was 19% for the TNF-alpha inhibitor group and 11% for the DMARD group compared to 6% for the control group. According to the Cox proportional hazard model they used the TNF-alpha group had a 3.1-fold increased risk compared to the control group (95% CI 1.4-7.0), while the DMARD group showed a 2.2-fold increase (95% CI: 0.96-5.3). The reasons for revision surgery were due to infection (40%) or other causes (60%), such as failure to fuse in the DMARDs group, while in the TNF-alpha inhibitor group, it was 47% for infection and 53% for other causes (15). This implies there is a higher rate of infection for the TNF-alpha inhibitor cohort. The authors concluded that continuing DMARDs, especially TNF-alpha inhibitors, 90 days before surgery, appeared to have a higher rate of revision spinal surgery than those who discontinued.
In 2017, the American College of Rheumatology and American Association of Hip and Knee Surgery (ACR/AAHK) performed an extensive meta-analysis of the literature around the use of DMARDs in orthopaedic surgery (10). They advised that conventional DMARDs, which include methotrexate, leflunomide, hydroxychloroquine, and sulfasalazine, can be continued in orthopaedic surgery as they did not lead to adverse post-operative outcomes. However, they recommended holding biologics for two weeks before surgery as there was an increased risk of poor wound healing. The effect on bone healing itself was not studied in this review. There is, in fact, very limited data on the effect of biologic DMARDs on bone healing, but in an in vivo study, they have shown an inhibitory effect on osteoblast proliferation (3). This is particularly true of TNF-alpha inhibitors such as infliximab, which showed a reduction in overall osteoblast cell numbers. This suggests it could interfere with the bone repair and remodelling (3).
Furthermore, the 2021 critical analysis review by Saunders et al on the perioperative management of antirheumatic drugs in foot and ankle surgery also concluded that conventional DMARDS are generally safe to use throughout the perioperative period, while biologics should be held typically before surgery (16). Conclusions: Our narrative review has highlighted an important literature gap within the field of DMARDs and bone healing, whether in a traumatic or elective setting. Much of the original research is in vivo or animal studies, and although they show statistically significant results, they cannot accurately predict human outcomes due to significant differences in physiology and biology (3,8,9,12). Clinical studies are even fewer, and the ones conducted so far have included small study populations. Moreover, they are antiquated and often do not examine the latest anti-rheumatic drugs. For instance, an important study we included, Elia et al, included only 30 patients, which reduced the statistical power of the results (14). All the clinical studies we have included so far are for elective procedures such as spinal surgery or foot and ankle surgery (13,14, 16, 17). To our knowledge, there are currently no randomised controlled trials that study the effect of DMARDs on bone healing, either in a trauma or elective setting.
Nevertheless, there is a greater number of publications available to consider for the effect of DMARDs on wound healing in orthopaedic surgery. This is of important consequence as surgical site infections, especially when involving the bone, can lead to impaired fracture healing, causing malunion or non-union (18). Current evidence suggests MTX has no adverse effect on wound healing in orthopaedic surgery and can be safely continued pre- and postoperatively (10,11). However, biologics are recommended to be held perioperatively due to the increased risk of surgical site infections and impaired wound healing. The current guidance is to schedule surgery at the end of their dosing cycle (10). Some hospital trusts have advised only restarting when most of the wound has healed (19). Considering a wider evidence base, biologics have shown an increased risk of serious infection, so there is certainly a research gap to explore on how these medications impact patient outcomes in orthopaedic surgery (20).
Any decision to stop anti-rheumatic medications in the preoperative period should be a carefully considered decision, with patients fully informed as to the risks and benefits of stopping such therapy. Patients on DMARDs tend to have more severe disease, and withholding them may result in disease flares, which can cause significant morbidity. Flares may lead to joint swelling, stiffness, pain, and increased cardiovascular risk (21). This can ultimately impair rehabilitation following major surgery, which predisposes the patient to further post-operative complications such as venous thromboembolism, hospital-acquired infections, or reduced functional baseline from a prolonged hospital stay (22).
Grennan et al found that those who discontinued MTX two weeks before and after surgery showed a higher rate of flare-ups than those who continued their medication. Patients who continued MTX before surgery had even fewer post-operative complications than the control group that was not on any MTX (23). The 2017 American College of Rheumatology study also concluded that continuing glucocorticoids and DMARDs perioperatively for hip and knee arthroplasty resulted in better function, a greater range of motion, and improved post-operative pain (10).
Therefore, we advise that the decisions around anti-rheumatic medications in patients undergoing orthopaedic surgery should be determined on an individual basis, with consideration given to their disease severity, functional baseline, and risk factors for poor bone healing, as we currently do not have enough evidence to suggest that they should be held.
Our literature review, however, has some limitations. Firstly, we used specific terminology to capture the effect of anti-rheumatic medications on bone healing, so we may have missed articles that contain this information, which did not include our keywords. Secondly, there is such little data available for our topic that the papers we have selected for review have small study populations or no controls. None of the studies we included showed any randomisation. Therefore, results were interpreted with caution as there is a potential for bias and reduced generalisability. Finally, many papers we included were animal studies, so their findings cannot be applied directly to humans.
In conclusion, the effect of DMARDs on bone union remains largely unstudied, especially considering human studies and large randomised controlled trials. Our literature review has identified that MTX may be safe to continue before orthopaedic surgery, as it does not appear to affect bone union at low doses that are used in RA. However, biologics should be withheld as there is evidence to suggest they can cause an increased risk of infection or wound breakdown. The effect of biologics specifically on bone healing, has not been studied to our knowledge. Given that millions of patients suffer from rheumatoid arthritis, and many will at one point undergo a joint procedure, it is important to further understand the clinical impact of DMARDs on bone so we can recommend evidence-based guidance. Until then, we advise a multi-disciplinary approach in determining which anti-rheumatic medications to withhold before any orthopaedic surgery.
Background: The growing trend of integrated healthcare services within physician groups has improved care delivery by enhancing convenience, efficiency, and care coordination. However, it has also rai...
Background: The growing trend of integrated healthcare services within physician groups has improved care delivery by enhancing convenience, efficiency, and care coordination. However, it has also raised concerns about financial incentives potentially driving overutilization. Objective: We examine the impact of distribution method (traditional third-party referral versus physician-managed via Rx Redefined technology platform) on the quantity of urinary catheters supplied to Medicare patients. Methods: We analyzed utilization patterns for urological catheters (HCPCS codes A4351, A4352, and A4353) using 2021 Medicare claims data. We identified 54 urology specialists in core metropolitan areas who were enrolled in the Rx Redefined platform throughout 2021 and compared their utilization patterns with unenrolled urologists in the same regions. For enrolled physicians, who managed approximately 40 percent of their prescriptions through the platform, we also compared utilization between physician-managed and third-party distribution methods. Results: For catheter services A4351 and A4352, when distribution was managed by third parties, we found no significant differences in utilization (i.e. units supplied) between enrolled and unenrolled physicians. However, physician-managed distribution through Rx Redefined resulted in significantly lower utilization compared to third-party vendor distribution by non-enrolled physicians (p < 0.001 for both codes). In paired analysis of enrolled physicians, direct management showed significantly lower utilization compared to third-party distribution for A4351 (p = 0.014), but this difference was not significant for A4352 (p = 0.62). Conclusions: These findings demonstrate that physician-managed catheter distribution does not lead to increased utilization. In fact, for certain catheter types, physician-managed distribution may result in lower utilization compared to traditional third-party referral methods, suggesting a potential reduction in oversupply and improved efficiency.
Background: Sri Lanka has a well-established National Blood Transfusion
Service that provides quality assured blood bank service.
However, the information flow is inefficient and less utilized for...
Background: Sri Lanka has a well-established National Blood Transfusion
Service that provides quality assured blood bank service.
However, the information flow is inefficient and less utilized for
evidence-based decision-making. The statistics unit of National
Blood Centre is unable to produce Annual Statistics Report
timely due to the difficulty in analysing and making reports
manually utilizing the considerable amount of data collected
throughout the year. To address this, an electronic Health
Information Management System was proposed as a solution for
the inefficiency of the data flow for statistical purposes. Objective: 1. General Objective
Facilitate decision-making by developing, implementing and
evaluating an electronic information management system to
capture monthly statistics data from island wide blood banks.
2. Specific Objectives
Identify the requirements of the system (MSR-NBTS)
Customize DHIS2 to fulfil the identified
requirements
Testing and hosting the system at National Blood
Centre Narahenpita
Evaluation of usability and cost-effectiveness of the
system Methods: A Monthly Statistics Reporting System was designed and
developed using DHIS2, which is a Free and Open Source
Software (FOSS) to fulfil the requirements of the National Blood
Transfusion Service. To evaluate the new system, a qualitative
study was conducted using semi-structured interviews amongst
a selected study population of 17 participants within the NBC
Cluster, which includes 11 blood banks in Colombo area. The
gathered data was analysed using a thematic analysis techniques
and the emerging categories and themes were used in the
subsequent discussions. Results: Problems of calculation, usability, reliability, utilization of
data and availability of reports were identified in the paper
based system. Results shows that the new electronic system has
high usefulness, ease of use, ease of learn, satisfaction and cost
effectiveness with accepted enhanced features of the interface.
According to the interviews, participants expressed that the
likelihood of using this system in the future is high. Conclusions: Almost all the participants in this research readily accepted
new electronic information management system. Therefore, it
will assure the sustainability of the new system. Because of the
real time updated dashboard, it will help most of the blood bank
functions by facilitating administrative decision-making
efficiently.
Background: Unskilled birth delivery significantly contributes to maternal and neonatal mortality in Sub-Saharan Africa, especially Nigeria, due to cultural beliefs, poverty, poor health access, and w...
Background: Unskilled birth delivery significantly contributes to maternal and neonatal mortality in Sub-Saharan Africa, especially Nigeria, due to cultural beliefs, poverty, poor health access, and weak policies. Despite efforts to promote skilled attendance, many women still use traditional birth attendants (TBAs) and home deliveries. This study explores the socio-demographic, cultural, and systemic factors driving this trend, offering evidence for better policies and health interventions. Objective: This study examined the socio-demographic and socio-cultural barriers to the utilization of skilled delivery services among women of reproductive age in Nigeria. Methods: A cross-sectional design utilizing both quantitative surveys and qualitative interviews was employed. The study involved 1,200 expectant and recently delivered women across urban, semi-urban, and rural regions in Nigeria. Data on socio-demographics, beliefs, access factors, and healthcare usage were collected. Policy documents and intervention records were reviewed, while focus groups provided depth to cultural and systemic themes. Descriptive and inferential statistics were applied using SPSS, and thematic analysis was used for qualitative data. A literature triangulation approach was used to validate findings with existing research. Results: The study revealed that low maternal education, poverty, and rural residence strongly predicted unskilled delivery service usage. Cultural norms that regard childbirth as a domestic or spiritual event influenced avoidance of hospitals. Access barriers included poor transport, cost, and distrust in formal healthcare. Geographic inequality was evident, with rural regions lacking health infrastructure. Policy review showed limited reach and weak enforcement of maternal care programs. However, when community-based midwives or mobile clinics were available, skilled birth attendance improved significantly. Conclusions: The persistence of unskilled deliveries is a multifaceted issue driven by intersecting socio-cultural, economic, geographic, and institutional factors. Despite policy efforts, gaps remain in cultural sensitivity, resource allocation, and infrastructure coverage. To address maternal health effectively, interventions must be locally adapted, multidimensional, and equity-focused. To address unskilled delivery use, maternal health education should leverage community programs with local languages and cultural context. Rural healthcare infrastructure must expand via mobile clinics and trained midwives to improve access. Skilled delivery costs should be subsidized or covered by insurance to remove financial barriers. Traditional birth attendants could be trained and integrated into the formal health system under supervision. Finally, maternal health policies require regular review, adequate funding, and strict monitoring to ensure impact. These steps are vital to reducing maternal mortality in Nigeria and Sub-Saharan Africa. Unskilled delivery service utilization represents a critical barrier to maternal and neonatal health improvements in Nigeria and Sub-Saharan Africa. Addressing this issue through targeted socio-cultural, structural, and policy interventions is essential to reduce preventable maternal deaths and achieve Sustainable Development Goal 3 on maternal health.
Background: Necrotizing enterocolitis (NEC) is the most common gastrointestinal emergency affecting preterm infants with high mortality and morbidity. With suboptimal and incomplete methods of prevent...
Background: Necrotizing enterocolitis (NEC) is the most common gastrointestinal emergency affecting preterm infants with high mortality and morbidity. With suboptimal and incomplete methods of prevention of NEC, early diagnosis and treatment can potentially mitigate the impact of NEC. This study explores the application of machine learning techniques, specifically Random Forest and Extreme Gradient Boosting (XG Boost), to improve early and accurate NEC and FIP diagnosis. Objective: To evaluate the effectiveness of sampling techniques in addressing class imbalance and to identify the optimal machine learning (ML) classifiers for predicting necrotizing enterocolitis (NEC) and focal intestinal perforation (FIP) in preterm infants. Methods: We developed ML models using 49 clinical variables from a retrospective cohort of 3,463 preterm infants, using clinical data from the first two weeks of life as input features. We applied various sampling strategies to address the inherent class imbalance, and then combined various sampling strategies with different ML algorithms. Parsimonious models with selected key predictors were evaluated to maintain predictive performance comparable to the full-featured (complex) models. Results: The parsimonious generalized linear model (GLM) with SMOTE sampling achieved an area under the receiver operating characteristic curve (AUROC) of 0.79 for NEC prediction, closely approximating the complex model's AUROC of 0.76. For FIP prediction, parsimonious models of GLM with ADASYN sampling and XG Boost with TOMEK sampling achieved AUROC values exceeding 0.90, comparable to those of the corresponding complex models. For both NEC and FIP, the area under the precision-recall curve (AUPRC) surpassed the respective prevalence rates, indicating strong performance in identifying rare outcomes. Conclusions: We demonstrate that targeted sampling strategies can effectively mitigate class imbalance in neonatal datasets, and simplified models with fewer variables can offer comparable predictive power, enhancing the performance of ML-based prediction models for NEC and FIP.
Background: Workplace stress has emerged as a pressing public health issue in Nigeria, where approximately 75% of employees experience work-related stress significantly higher than the global average....
Background: Workplace stress has emerged as a pressing public health issue in Nigeria, where approximately 75% of employees experience work-related stress significantly higher than the global average. This stress, exacerbated by systemic labor policy gaps, cultural stigma, and economic instability, contributes to burnout, reduced productivity, and economic losses. Despite emerging HRM interventions, mental health remains underprioritized in organizational strategies, particularly within sectors such as healthcare, banking, construction, and the informal economy. There is a critical need for evidence-based, culturally adapted HRM strategies that address these unique challenges in Nigeria’s workforce. Objective: This study seeks to examine the prevalence and sector-specific drivers of workplace stress in Nigeria, evaluate the effectiveness and limitations of current HRM interventions, identify key socio-cultural and structural barriers hindering mental health program implementation, and propose actionable, evidence-based strategies that are contextually tailored to Nigeria’s diverse workforce. Through a synthesis of localized research and global best practices, the study aims to provide a strategic roadmap for enhancing mental health resilience in Nigerian workplaces. Methods: A narrative review methodology was employed, guided by qualitative synthesis and thematic analysis frameworks. Literature was sourced from global and regional databases (PubMed, PsycINFO, AJOL, Scopus) spanning 2018–2024, including peer-reviewed articles, policy reports, and grey literature. Inclusion focused on empirical and policy studies relevant to Nigerian HRM practices. NVivo 12 was used for thematic coding, and a gap analysis framework was applied to identify unaddressed areas. A total of 42 studies met the inclusion criteria. Expert validation and triangulation with global data enhanced rigor. Results: Burnout rates in Nigeria are among the highest globally, with 35% in healthcare, 32% in retail, and 29% in banking. Women and younger workers face disproportionate stress burdens. HRM strategies such as Employee Assistance Programs (EAPs) and Flexible Work Arrangements showed the highest effectiveness but had limited adoption due to cost, stigma, and infrastructure gaps. Digital mental health tools, though cost-effective, had low uptake (23%) due to digital illiteracy. Barriers included cultural stigma, weak labor policies, leadership apathy, and lack of ROI measurement. Promising strategies identified include faith-based EAPs, peer networks, mobile clinics, and stigma-reduction campaigns, particularly when culturally embedded and supported by community leaders. Conclusions: Workplace stress in Nigeria is a systemic challenge rooted in socio-economic, cultural, and organizational structures. Although several HRM interventions show promise, their effectiveness is hindered by low adoption, poor contextual fit, and limited legal enforcement. Evidence suggests that when mental health strategies are localized and culturally endorsed via faith leaders, digital tools, or flexible work, they yield improved employee retention, lower absenteeism, and better organizational resilience.
Background: Successful Research and MedTech collaborations depend on six key components: talent and workforce development, innovative solutions, robust research infrastructure, regulatory compliance,...
Background: Successful Research and MedTech collaborations depend on six key components: talent and workforce development, innovative solutions, robust research infrastructure, regulatory compliance, patient-centered care, and rigorous evaluation.
Institutional leaders frequently navigate multiple professional identities; simultaneously serving as educators, researchers, clinicians, and innovators; creating bridges between academic rigor and practical application that accelerate the translation of research into meaningful solutions. Institutions and organizations may also need to broaden their identities.
The contemporary landscape presents significant challenges as institutions balance the pursuit of academic excellence with the need for rapid responsiveness to technological and commercial innovation. Traditional research processes, while ensuring quality, often impede the pace of advancement necessary in today's rapidly evolving environment. This tension necessitates structural reforms across multiple dimensions of institutional operation.
To cultivate a thriving research and innovation ecosystem, several essential components must be established:First, institutions require agile research infrastructure with cutting-edge laboratories and collaboration spaces, specialized equipment, and certified research professionals specifically trained in device development and regulatory compliance. Robust clinical management platforms can expedite trials and streamline data extraction for publication and dissemination. Objective: The Orange County (OC) Impact Conference, held in November 2024, convened 180 key stakeholders from the life sciences, technology, medical device, and healthcare sectors. CHOC Research in collaboration with University Lab Partners (ULP) and the University of California, Irvine, provided this platform for leaders, decision-makers, and experts to discuss the intersection of innovation in research, healthcare, biotechnology, and data science. Methods: We convened a multidisciplinary symposium (180 participants) to examine advancements in life sciences and medical device research development. The structured forum incorporated moderated panel discussions and a keynote speaker. Participants represented diverse stakeholder categories including research scientists, clinicians, investors and financiers, and executive research and healthcare leadership. The event design facilitated both structured knowledge exchange and strategic networking opportunities aimed at identifying implementation pathways to enhance clinical impact. Results: The 2024 OC Impact Conference Proceedings outline a strategy for healthcare innovation, demonstrating how targeted collaboration between patients, families, researchers, clinicians, engineers, data scientists, and industry is reshaping the healthcare innovation ecosystem. This integrated approach ensures every stakeholder's voice contributes to meaningful advancement, guiding resource allocation and partnership development across the life science and medical device sectors. Our findings demonstrate that success requires moving beyond traditional approaches to patient-driven research priorities, augmented design principles for medical device development, and direct engagement between innovators, research participants, industry and healthcare centers throughout the research development cycle. Conclusions: The insights gained through participation in the OC Impact Conference contribute to the ongoing discourse in these fields, emphasizing collaborative efforts to enhance pediatric and adult healthcare outcomes. Clinical Trial: N/A
Background: Nigeria faces severe economic losses ($14 billion annually) and high youth unemployment (33.3%) due to persistent skills gaps, exacerbated by sectoral disparities (e.g., 68% ICT shortages...
Background: Nigeria faces severe economic losses ($14 billion annually) and high youth unemployment (33.3%) due to persistent skills gaps, exacerbated by sectoral disparities (e.g., 68% ICT shortages vs. 63% agricultural deficits) and systemic inequities in education and vocational access. Despite growing HRM interventions, empirical evidence on their efficacy remains limited, necessitating a comprehensive review to guide policy. Objective: This study analyzes Nigeria’s sector-specific skills gaps, evaluates the effectiveness of HRM interventions (apprenticeships, digital upskilling, PPPs), and proposes actionable frameworks to align workforce development with labor market demands. Methods: A narrative review of peer-reviewed literature (2015–2023), institutional reports (World Bank, PwC, NBS), and case studies (e.g., Andela’s model) was conducted. Data were synthesized to compare regional benchmarks (Kenya’s TVET, South Africa’s HRM reforms) and Nigeria’s performance (talent readiness score: 42/100). Results: Key findings include: (1) Vocational training (60% readiness) outperforms tertiary education (40%); (2) Apprenticeships and PPPs show high impact (30% job placement increase); (3) Urban-rural and gender disparities persist (women 30% less likely to access training). Private-sector models demonstrate scalability but require policy support. Conclusions: Nigeria’s skills crisis demands urgent, context-sensitive interventions. Blended strategies (e.g., industry-aligned curricula, gender-inclusive vocational programs) could unlock 5% annual GDP growth. Prioritize: (1) National skills councils to standardize certifications; (2) Tax incentives for employer-led training; (3) Digital infrastructure for rural upskilling. Closing Nigeria’s skills gaps would mitigate economic losses, reduce inequality, and enhance global competitiveness, transforming its youth bulge into a sustainable demographic dividend.
Background: Central venous catheterization (CVC) is a very common procedure performed across medical and surgical wards as well as intensive care units. It provides relatively extended vascular access...
Background: Central venous catheterization (CVC) is a very common procedure performed across medical and surgical wards as well as intensive care units. It provides relatively extended vascular access for critically ill patients, in order to the administer intricate life-saving medications, blood products and parenteral nutrition.
Major vascular catheterization provides a risk of easy accessibility and dissemination of catheter related infections as well as venous thromboembolism. Therefore, its crucial to ensure following standardized practices while insertion and management of CVC in order to minimize the infection risks and procedural complications. The aim of these central line insertion guidelines is to address the primary concerns related to predisposition of Central line associated blood stream infections (CLABSI). These guidelines are evidence based and gathered from pre-existing data associated with CVC insertion.
The most common used sites for central venous catheterization are internal jugular and subclavian veins as compared to femoral veins. Catheterization of these vessels enables healthcare professionals to monitor hemodynamic parameters while ensuring lower risks of CLABSI and thromboembolism. Femoral vein is less preferred due to advantage of invasive hemodynamic monitoring and low risk of local infection and thromboembolic phenomena.
CVC can be inserted using Landmark guided technique and ultrasound guided techniques. Following informed consent, the aseptic technique for CVC insertion includes performing appropriate hand hygiene and ensuring personal protective measures, establishing and maintaining sterile field, preparation of the site using chlorhexidine, and draping the patient in a sterile manner from head to toe. Additionally, the catheter is prepared by pre-flushing and clamping all unused lumens, and the patient is placed in the Trendelenburg position. Throughout the procedure, maintaining a firm grasp on the guide wire is essential, which is subsequently removed post-procedure. It is followed by flushing and aspirating blood from all lumens, applying sterile caps, and confirming venous placement. Procedure is ended with cleaning the catheter site with chlorhexidine, and application of a sterile dressing.
Hence, formal training and knowledge of standardized practices of CVC insertion is essential for health care professionals in order to prevent CLABSI. Our audit assesses the current practices of doctors working at a tertiary care hospital to analyze their background knowledge of standard practices to prevent CLABSI during insertion of CVC. Objective: This study was aimed to audit and re-audit residents’ practices of central venous line insertion in medical and nephrology units of A Tertiary Care Hospital of Rawalpindi, Pakistan and to assess the adherence of residents to checklist and practice guidelines of CVC insertion implemented by John Hopkins Hospital and American Society of Anesthesiologists. Methods: This audit was conducted as a cross sectional direct observational study and two-phase quality improvement project in the Medical and Nephrology Units of a Tertiary Care Hospital of Rawalpindi from December 2023 to February 2024.
After taking informed consent from patients and residents, CVC insertion in 34 patients by 34 individual residents was observed. Observers were given a purposely designed observational tool made from John Hopkins Medicine checklist and ASA practice guidelines for central line insertion, for assessment of residents’ practices.
First part contained questions regarding the demographic details of residents such as age, gender, year of post graduate training, and parent department, and data related to the procedure such as date and time of procedure, need of CVC discussion during rounds, site of CVC insertion, catheter type and type of procedure (Landmark guided CVC or Ultrasound guided CVC insertion). Second part included direct observational checklist based on checklist provided for prevention of intravascular catheter-associated bloodstream infections to audit the practices of residents during CVC insertion that included: adequate hand hygiene before insertion, adherence to aseptic techniques, using sterile personal protective equipment and sterile full body drape of patient, choosing the best insertion site to minimize infections based on patient characteristics.
The parameters observed to be done completely were scored "1" and the items not done were scored "0". The cumulative percentage of performed practices according to checklist, was satisfactory if it was 80% or more and unsatisfactory if it was less than 80%.
After initial audit, participants were given pamphlets with checklist incorporating John Hopkins Medicine checklist and ASA practice guidelines for CVC insertion. Re audit was performed one month after the audit, including same participants who participated in initial audit. The results of audit and re-audit were analyzed using SPSS version 25. Mean +/- SD was calculated for quantitative variables and Number (N) percentage was calculated for qualitative variables. Z- Test was applied on proportions of parameters and test scores to calculate Z –score and P value (<0.05 was significant). Results: Among the 34 participants, 44% of the participants belonged to Nephrology Department and 56% of participants belonged to Department of Internal Medicine.
32.3% residents were in their first year, 14.7% in second, 14.7 in third year, 17.6% in fourth year and 17.6% in 5th/Final year of training.
47% of the participants were male and 53% were female. Participants were aged between 27 and 34 years old, the median age at the time of audit was 29 years.
Landmark guided CVC insertion was performed in Subclavian Vein (73.5%) and Internal Jugular Vein (26.5%).
Post audit practices were improved from 73.5% to 94%. Conclusions: Our audit found that many of the residents adopted inadequate practices because of lack of proper training and institutional guidelines for CVC insertion. Our re-audit elaborated an improvement in the practices of residents following intervention with educational material. Our study underscores the importance of structured quality improvement initiatives in enhancing clinical practices and patient outcomes.
Background: Social media has profoundly transformed consumer behavior and marketing practices within the hospitality industry. Understanding how these changes influence hotel selection and booking dec...
Background: Social media has profoundly transformed consumer behavior and marketing practices within the hospitality industry. Understanding how these changes influence hotel selection and booking decisions, the effectiveness of social media strategies, and shifts in reputation management practices is crucial for hotels aiming to enhance their digital presence and customer engagement. Objective: The study aims to analyze the influence of social media on consumer behavior, audience engagement, and reputation management in hotel selection and booking decisions as well as compare pre- and post-social media reputation management practices. Methods: Data was collected through surveys and interviews with hotel guests and marketing professionals. The analysis included descriptive statistics and comparative assessments of pre- and post-social media reputation management practices. The effectiveness of various social media strategies was evaluated based on respondent feedback. Results: The findings indicate that promotional offers, user reviews, and visual content significantly influence consumer behavior in hotel selection and booking decisions. Collaboration with influencers, user-generated content, live video content, and social media advertising are the most effective strategies for audience engagement and brand building, each with a 100% effectiveness rate. There is a notable shift in reputation management practices, with a decrease in promptly addressing issues and providing compensation, and an increase in seeking private resolutions through direct messages post-social media. Conclusions: Social media plays a critical role in shaping consumer behavior and brand perception in the hotel industry. Effective social media strategies, particularly those involving influencers and user-generated content, are essential for engaging audiences and building brand identity. The transition to social media has also led to changes in reputation management, emphasizing the importance of balancing transparency with discreet conflict resolution. Hotels should prioritize comprehensive social media strategies that include collaboration with influencers, regular updates, and engaging content. Encouraging positive user-generated content and implementing robust monitoring and response systems are essential. Training staff on social media engagement and conflict resolution can further improve reputation management. Ongoing adaptation to emerging social media trends is crucial for maintaining effectiveness. This study provides valuable insights into the impact of social media on consumer behavior and marketing in the hospitality industry. By identifying effective social media strategies and examining changes in reputation management, it offers practical guidance for hotels seeking to enhance their digital presence and customer engagement. The findings underscore the importance of leveraging social media to achieve greater business success and maintain a positive brand reputation.
Background: Noncommunicable diseases (NCDs) pose a significant burden in the Philippines, with cardiovascular and cerebrovascular diseases among the leading causes of mortality. The Department of Heal...
Background: Noncommunicable diseases (NCDs) pose a significant burden in the Philippines, with cardiovascular and cerebrovascular diseases among the leading causes of mortality. The Department of Health implemented the Philippine Package of Essential Non-Communicable Disease Interventions (Phil PEN) to address this issue. However, healthcare professionals faced challenges in implementing the program due to the cumbersome nature of the multiple forms required for patient risk assessment. To address this, a mobile medical app, the PhilPEN Risk Stratification app, was developed for community health workers (CHWs) using the extreme prototyping framework. Objective: This study aimed to assess the usability of the PhilPEN Risk Stratification app using the (User Version) Mobile App Rating Scale (uMARS) and to determine the utility of uMARS in app development. The secondary objective was to achieve an acceptable (>3 rating) score for the app in uMARS, highlighting the significance of quality monitoring through validated metrics in improving the adoption and continuous iterative development of medical mobile apps. Methods: The study employed a qualitative research methodology, including key informant interviews, linguistic validation, and cognitive debriefing. The extreme prototyping framework was used for app development, involving iterative refinement through progressively functional prototypes. CHWs from a designated health center participated in the app development and evaluation process – providing feedback, using the app to collect data from patients, and rating it through uMARS. Results: The uMARS scores for the PhilPEN Risk Stratification app were above average, with an Objective Quality rating of 4.05 and a Personal Opinion/Subjective Quality rating of 3.25. The mobile app also garnered a 3.88-star rating. Under Objective Quality, the app scored well in Functionality (4.19), Aesthetics (4.08), and Information (4.41), indicating its accuracy, ease of use, and provision of high-quality information. The Engagement score (3.53) was lower due to the app's primary focus on healthcare rather than entertainment. Conclusions: The study demonstrated the effectiveness of the extreme prototyping framework in developing a medical mobile app and the utility of uMARS not only as a metric, but also as a guide for authoring high-quality mobile health apps. The uMARS metrics were beneficial in setting developer expectations, identifying strengths and weaknesses, and guiding the iterative improvement of the app. Further assessment with more CHWs and patients is recommended. Clinical Trial: N/A
This study investigates the behavioral dynamics of sociopaths, focusing on their reliance on glibness (superficial charm) as a primary manipulation tactic and aggressiveness as a secondary strategy wh...
This study investigates the behavioral dynamics of sociopaths, focusing on their reliance on glibness (superficial charm) as a primary manipulation tactic and aggressiveness as a secondary strategy when charm fails. Sociopathy, characterized by manipulative tendencies and a lack of empathy, often manifests in adaptive yet harmful behaviors aimed at maintaining control and dominance.
Using the Deenz Antisocial Personality Scale (DAPS-24) to collect data from 34 participants, this study examines the prevalence and interplay of these dual strategies. Findings reveal that sociopaths employ glibness to disarm and manipulate, transitioning to aggressiveness in response to resistance. The implications for understanding sociopathic manipulation are discussed, emphasizing the importance of early detection and intervention in both clinical and social contexts.
