Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.
Who will be affected?
Readers: No access to all 28 journals. We recommend accessing our articles via PubMed Central
Authors: No access to the submission form or your user account.
Reviewers: No access to your user account. Please download manuscripts you are reviewing for offline reading before Wednesday, July 01, 2020 at 7:00 PM.
Editors: No access to your user account to assign reviewers or make decisions.
Copyeditors: No access to user account. Please download manuscripts you are copyediting before Wednesday, July 01, 2020 at 7:00 PM.
JMIR Preprints
A preprint server for pre-publication/pre-peer-review preprints intended for community review as well as ahead-of-print (accepted) manuscripts
Background: Children and young adults with special healthcare needs comprise a significant portion of the pediatric population in the United States, where 1 in every 5 children has a complex healthcare need. These patients are more likely to receive “unsafe” care and have their needs unmet in part due to lack of accessible information and limited training support. Barriers in communication may contribute to detrimental outcomes for this vulnerable high-risk population. Objective: The project aims to identify barriers to communication in children and young adults with special health care needs in the healthcare setting. These barriers will inform prototype development using human centered design approaches to generate a web-based application. Feedback from patients (P), caregivers (CG) and healthcare providers (HCP) was obtained for usability and usefulness of the tool within the healthcare setting. Methods: A needs assessment was conducted, where participants shared their experiences in providing or receiving healthcare services via a semi-structured interview that was recorded and transcribed. Transcripts were analyzed inductively for themes, coded and used to categorize the data. Based on these themes, iterative development of a web-based application for social stories occurred. Focus groups were held to provide relevant feedback on the prototype. Results: There were 15 participants (10 HCP and 5 P/CG) interviewed for the needs assessment that informed prototype development. A web-based application for social stories depicting different aspects of healthcare interactions was created. Focus group feedback on usability utilizing the Sustained Usability Score (SUS) along with narrative feedback was obtained. Overall, the usability of the application was supported by caregivers and healthcare providers Conclusions: Children and young adults with special health care needs necessitate medical services not generally required by their peers, thereby compounding potential barriers in communication surrounding healthcare delivery. Utilizing social stories geared to healthcare interactions may help reduce anxiety and difficulty in successful healthcare interactions.
Journal Description
JMIR Preprintscontains pre-publication/pre-peer-review preprints intended for community review (FAQ: What are Preprints?). For a list of all preprints under public review click here. The NIH and other organizations and societies encourage investigators to use interim research products, such as preprints, to speed the dissemination and enhance the rigor of their work. JMIR Publications facilitates this by allowing its authors to expose submitted manuscripts on its preprint server with a simple checkbox when submitting an article, and the preprint server is also open for non-JMIR authors.
With the exception of selected submissions to the JMIR family of journals (where the submitting author opted in for open peer-review, and which are displayed here as well for open peer-review), there is no editor assigning peer-reviewers.
Submissions are open for anybody to peer-review. Once two peer-review reports of reasonable quality have been received, we will send these peer-review reports to the author, and may offer transfer to a partner journal, which has its own editor or editorial board.
The submission fee for that partner journal (if any) will be waived, and transfer of the peer-review reports may mean that the paper does not have to be re-reviewed. Authors will receive a notification when the manuscript has enough reviewers, and at that time can decide if they want to pursue publication in a partner journal.
If authors want to have the paper only considered/forwarded to specific journals, e.g. JMIR, PLOS, PEERJ, BMJ Open, Nature Communications etc) after peer-review, please specify this in the cover letter. Simply rank the journals and we will offer the peer-reviewed manuscript to these editors in the order of your ranking.
If authors do NOT wish to have the preprint considered in a partner journal (or a specific journal), this should be noted in the cover letter.
JMIR Preprints accepts manuscripts at no costs and without any formatting requirements (but if you intend the submission to be published eventually by a specific journal, it is of advantage to follow their instructions for authors). Authors may even take a WebCite snapshot of a blog post or "grey" online report. However, if the manuscript is already peer-reviewed and formally published elsewhere, please do NOT submit it here (this is a preprint server, not a postprint server!).
JMIR Preprints is a preprint server and "manuscript marketplace" with manuscripts that are intended for community review. Great manuscripts may be snatched up by participating journals which will make offers for publication.There are two pathways for manuscripts to appear here: 1) a submission to a JMIR or partner journal, where the author has checked the "open peer-review" checkbox, 2) Direct submissions to the preprint server.
For the latter, there is no editor assigning peer-reviewers, so authors are encouraged to nominate as many reviewers as possible, and set the setting to "open peer-review". Nominated peer-reviewers should be arms-length. It will also help to tweet about your submission or posting it on your homepage.
For pathway 2, once a sufficient number of reviews has been received (and they are reasonably positive), the manuscript and peer-review reports may be transferred to a partner journal (e.g. JMIR, i-JMR, JMIR Res Protoc, or other journals from participating publishers), whose editor may offer formal publication if the peer-review reports are addressed. The submission fee for that partner journal (if any) will be waived, and transfer of the peer-review reports may mean that the paper does not have to be re-reviewed. Authors will receive a notification when the manuscript has enough reviewers, and at that time can decide if they want to pursue publication in a partner journal.
For pathway 2, if authors do not wish to have the preprint considered in a partner journal (or a specific journal), this should be noted in the cover letter. Also, note if you want to have the paper only considered/forwarded to specific journals, e.g. JMIR, PLOS, PEERJ, BMJ Open, Nature Communications etc), please specify this in the cover letter.
Manuscripts can be in any format. However, an abstract is required in all cases. We highly recommend to have the references in JMIR format (include a PMID) as then our system will automatically assign reviewers based on the references.
Background: Children and young adults with special healthcare needs comprise a significant portion of the pediatric population in the United States, where 1 in every 5 children has a complex healthcar...
Background: Children and young adults with special healthcare needs comprise a significant portion of the pediatric population in the United States, where 1 in every 5 children has a complex healthcare need. These patients are more likely to receive “unsafe” care and have their needs unmet in part due to lack of accessible information and limited training support. Barriers in communication may contribute to detrimental outcomes for this vulnerable high-risk population. Objective: The project aims to identify barriers to communication in children and young adults with special health care needs in the healthcare setting. These barriers will inform prototype development using human centered design approaches to generate a web-based application. Feedback from patients (P), caregivers (CG) and healthcare providers (HCP) was obtained for usability and usefulness of the tool within the healthcare setting. Methods: A needs assessment was conducted, where participants shared their experiences in providing or receiving healthcare services via a semi-structured interview that was recorded and transcribed. Transcripts were analyzed inductively for themes, coded and used to categorize the data. Based on these themes, iterative development of a web-based application for social stories occurred. Focus groups were held to provide relevant feedback on the prototype. Results: There were 15 participants (10 HCP and 5 P/CG) interviewed for the needs assessment that informed prototype development. A web-based application for social stories depicting different aspects of healthcare interactions was created. Focus group feedback on usability utilizing the Sustained Usability Score (SUS) along with narrative feedback was obtained. Overall, the usability of the application was supported by caregivers and healthcare providers Conclusions: Children and young adults with special health care needs necessitate medical services not generally required by their peers, thereby compounding potential barriers in communication surrounding healthcare delivery. Utilizing social stories geared to healthcare interactions may help reduce anxiety and difficulty in successful healthcare interactions.
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: Current methods for analyzing and matching shapes frequently struggle to distinguish subtle structural variations, particularly under conditions involving noise, deformation, or articulati...
Background: Current methods for analyzing and matching shapes frequently struggle to distinguish subtle structural variations, particularly under conditions involving noise, deformation, or articulations. Existing algorithms often lack robustness and flexibility, relying heavily on local curvature, which may inadequately represent complex structural details essential for precise shape classification and matching. Objective: To develop a robust and versatile three-tier shape representation pipeline that enhances intra-group similarity and amplifies inter-group differences, thereby providing an invariant representation resilient to noise, articulations, and mechanical deformations. Methods: We propose a novel approach comprising three steps: (1) a manifold-reduction step employing stress minimization to neutralize shape deformations, (2) application of the eccentricity transform (Ecc) to incorporate internal structural information, and (3) integral invariants (II) for robust boundary description. This tripartite framework synergizes differential geometry, topology, and scale-space theory, rigorously evaluated on standard datasets such as the Kimia database. Results: Our method significantly outperformed existing shape-matching algorithms, demonstrating notably improved intra-group matching accuracy and effectively enhancing inter-group discrimination. The approach provided substantial resilience against noise, articulations, and bending-induced shape distortions, verified through extensive experimentation and statistical evaluation. Conclusions: The proposed three-tier invariant representation delivers a robust and mathematically sound pipeline suitable for precise shape matching and classification tasks. Its resilience to common shape-analysis challenges makes it highly suitable for practical applications in computational anatomy, biomechanics, medical imaging, and computer-aided geometric design. Clinical Trial: Not applicable (omit if required).
Background: Diabetic retinopathy (DR) is a serious complication of diabetes and it affects the retinal blood vessels, leading to vision impairment and, in severe cases, blindness. Unfortunately, DR is...
Background: Diabetic retinopathy (DR) is a serious complication of diabetes and it affects the retinal blood vessels, leading to vision impairment and, in severe cases, blindness. Unfortunately, DR is irreversible, and available treatments can only help preserve existing vision rather than restore lost sight. Objective: Early detection is pivotal, yet traditional diagnostic methods depend on retinal fundus imaging and ophthalmologists' expertise faces significant challenges. These include high costs, long detection times, and the risk of misdiagnosis. That may delay treatment and increase the likelihood of blindness. Moreover, existing diagnostic modalities exhibit suboptimal efficacy in accurately detecting and managing diabetic macular edema (DME), a predominant etiological factor in vision impairment. Methods: Recent advancements in artificial intelligence (AI) and deep learning (DL) have significantly improved the detection and classification of DR. DL, particularly in medical image analysis, has demonstrated remarkable sensitivity, specificity, F1-score, and AUC. Results: Techniques such as transfer learning, transformer learning, and customized DL models have further enhanced DR detection using color fundus images. These state-of-the-art methods offer a more accurate, faster, and cost-effective alternative to traditional approaches. Conclusions: This article reviews recent developments in DL-based DR detection, discusses existing challenges, and provides recommendations for future improvements. Strengthening AI-driven detection systems is essential to reducing vision loss among diabetic patients and ensuring more reliable, accessible, and early diagnosis of DR. Clinical Trial: Nill
Background: Diabetic foot ulcers (DFU) represent a severe complication that can increase morbidity and mortality in diabetic patients. Effective management of DFU requires accurate and prompt wound as...
Background: Diabetic foot ulcers (DFU) represent a severe complication that can increase morbidity and mortality in diabetic patients. Effective management of DFU requires accurate and prompt wound assessment. However, the need for proper management of DFU necessitates wound assessments that are both swift and accurate, a challenge that persists in current clinical practice. Objective: This study explores the application of AI-based assessment models in evaluating DFU conditions, aiming to enhance detection accuracy, transparency in medical decision-making, and the effectiveness of real-time patient monitoring and care. Methods: A scoping review methodology based on the PRISMA-ScR framework was used to identify, select, and summarize literature on the use of AI in DFU assessment. Literature was sourced from PubMed, ProQuest, and Scopus using keywords like diabetic foot ulcer, Artificial Intelligence, and wound assessment. Results: AI models demonstrate high accuracy in risk prediction, detection, segmentation, and classification of diabetic foot ulcers (DFU), with some models achieving up to 99% accuracy. Smart applications and deep learning-based systems have proven to be reliable and comparable to clinical evaluations, enhancing efficiency and transparency in DFU management. Conclusions: The development and application of AI-based models in DFU assessment and monitoring improve diagnostic effectiveness and accuracy while supporting more transparent and timely medical decisions.
Background: Acute aortic syndrome is a rare but life-threatening clinical syndrome that can rapidly progress to aortic rupture and death. Symptoms are vague and non-specific, making it challenging to...
Background: Acute aortic syndrome is a rare but life-threatening clinical syndrome that can rapidly progress to aortic rupture and death. Symptoms are vague and non-specific, making it challenging to identify. Objective: We aimed to evaluate prediction models to help clinicians identify acute aortic syndrome based on the data available at the time of presentation. Methods: We combined two existing national datasets of signs and symptoms gathered from patients with and without acute aortic syndrome, from over 30 UK healthcare centres (n = 6,168). Sample incidence was 10.1% (n = 634) against a symptomatic population incidence of 0.26%. We fitted 4,776 prediction models to an 80% ‘training’ split of the data, and then tested on the remaining 20% ‘test’ split. Sensitivity, overall net benefit, and informedness (using Youden’s J) were calculated to represent the perspectives of the clinician, the patient, and the decision modeller. Results: The most-common performance was for models to show little to no sensitivity or informedness (< 0.1) and negative overall net benefit. Models with high sensitivity (>0.8) had a range of informedness values, including 0. The only models that had a positive overall net benefit all used the same rule that labelled everyone as having acute aortic syndrome. These “yes to all” models had a sensitivity of 100%, an overall net benefit of only 10%, and informedness value of 0. Conclusions: The perspectives of the clinician, the patient, and the decision modeller need to be considered when developing prediction models for decision support. No model performed well on all evaluation statistics. Difficult trade-offs are revealed, which are exacerbated for rare and severe conditions, such as acute aortic syndrome.
Background: Tetraplegia, often resulting from cervical spinal cord injury (SCI), may lead to significant motor and sensory loss, severely impacting independence and quality of life. Assistive technolo...
Background: Tetraplegia, often resulting from cervical spinal cord injury (SCI), may lead to significant motor and sensory loss, severely impacting independence and quality of life. Assistive technologies (ATs), such as wheelchair-mounted robotic arms (WMRAs), offer potential to enhance autonomy in daily living. However, adoption remains limited due to high costs, complex controls, and insufficient end-user involvement. Robust evidence on their real-world effectiveness, particularly post-hospitalisation, is still lacking. Objective: This study explores the real-life use of a WMRA for individuals with tetraplegia. It aims to evaluate its support in activities of daily living (ADLs), assess usability and satisfaction, and conduct a preliminary health economic analysis comparing cost-effectiveness and quality of life outcomes with standard care. Methods: This study will be conducted in post-hospitalisation settings in Switzerland. Up to 15 participants with upper limb impairments (SCI C0–Th1, AIS A–D) using powered wheelchairs will be recruited. They will use the robotic arm for six consecutive days. An equal number of participants will be recruited for the economic analysis group. A mixed methods approach will combine quantitative data collected via standardised questionnaires (PSSUQ, NASA-TLX, EQ-5D-5L, VAS, aCOMP, CSSRI-EU) at baseline and post-intervention, along with qualitative feedback gathered through an informal questionnaire and semi-structured interviews. Feasibility will be assessed through task performance and health economic analysis. The latter will include quality-adjusted life years (QALY), which quantify quality and length of life, and modelling the Incremental Cost-Effectiveness Ratio (ICER), which compares the cost-effectiveness of the intervention based on cost per QALY gained. Results: We expect the robotic system to reduce caregiver time and associated costs, while enhancing autonomy, quality of life, and mental well-being. Potential technical and recruitment challenges have been identified and mitigation strategies planned. By evaluating real-life use of a WMRAs, this study may support the broader adoption of assistive robotic technologies. Conclusions: This research offers key insights into the feasibility, usability, and economic value of robotic assistance for individuals with tetraplegia and will help inform future development and scale-up studies.
Background: We present a digital phenotyping protocol designed to continuously and objectively measure behavioral, physiological, and contextual data during pregnancy and postpartum periods using pass...
Background: We present a digital phenotyping protocol designed to continuously and objectively measure behavioral, physiological, and contextual data during pregnancy and postpartum periods using passive sensing from Garmin smartwatches and smartphones, along with active ecological momentary assessments (EMAs). This novel protocol uniquely adapts to the unpredictable timing of childbirth, spanning from the third trimester through six weeks postpartum, to accurately capture critical temporal changes and maternal-infant outcomes. By providing high-frequency real-time data, this methodology offers comprehensive insights into pregnancy-related behaviors and physiological processes, overcoming limitations of traditional retrospective self-report methods. Objective: The objective is to develop a protocol for longitudinal data collection supporting digital phenotyping that is optimized for pregnancy and postpartum. This protocol leverages the pregnant population’s heightened interest in health and tracking with over 50% using mobile health apps [1]. This protocol aims to minimize burden on the participants, increase retention, and assess the value of wearables compared to smartphones to determine appropriate data collection methods. Methods: Data will be collected on 30 nulliparous participants from the start of the third trimester through 6 weeks postpartum. This protocol utilizes three distinct one-time surveys, alongside daily and weekly Ecological Momentary Assessments (EMA), to capture real-time maternal experience data. Passive maternal data - such as activity, vitals, sleep, location - are collected via smartphone and Garmin smartwatch. Participants are expected to log data about the newborn after delivery through the mobile application Huckleberry. This protocol was developed in collaboration between the Northeastern University SATH Lab who focus on digital phenotyping and longitudinal data collection and Tufts Medical Center Obstetrics and Gynecology who have expertise working with the pregnant population. Results: The planned completion date is December 2026, with a manuscript published afterward. We plan to assess retention rates, survey and EMA completion rates, track wear time of smartwatch without intervention, and data volume logged in Huckleberry. Conclusions: This protocol integrates the use of digital phenotyping in pregnancy and postpartum research, providing a novel method for capturing real-time maternal well-being indicators. It will determine expected rates of data completion and appropriate sample size using a power analysis for a more extensive future study. By integrating smartphone and wearable sensor data, this protocol has the potential to transform the way maternal health clinical interventions are designed and implemented in the future.
COVID-19 forecasting models have been used to inform decision making around resource allocation and intervention decisions e.g., hospital beds or stay-at-home orders. State of the art forecasting mode...
COVID-19 forecasting models have been used to inform decision making around resource allocation and intervention decisions e.g., hospital beds or stay-at-home orders. State of the art forecasting models often use multimodal data such as mobility or socio-demographic data to enhance COVID-19 case prediction models. Nevertheless, related work has revealed under-reporting bias in COVID-19 cases as well as sampling bias in mobility data for certain minority racial and ethnic groups, which could affect the fairness of the COVID-19 predictions among racial and ethnic groups. In this paper, we first show that state of the art COVID-19 deep learning models output mean prediction errors that are significantly different across racial and ethnic groups; which could, in turn, support unfair policy decisions. We also propose a novel de-biasing method, DemOpts, to increase the fairness of deep learning based forecasting models trained on potentially biased datasets. Our results show that DemOpts can achieve better error parity than other state of the art de-biasing approaches, thus effectively reducing the differences in the mean error distributions across more racial and ethnic groups.
Background: Artificial intelligence (AI) is revolutionizing healthcare education, offering transformative solutions in knowledge assessment and training methodologies. Large language models (LLMs) suc...
Background: Artificial intelligence (AI) is revolutionizing healthcare education, offering transformative solutions in knowledge assessment and training methodologies. Large language models (LLMs) such as ChatGPT, Gemini Advanced, and Claude Sonnet have demonstrated remarkable capabilities across various domains, with recent studies showing these models achieving passing scores on standardized medical examinations. However, fundamental questions persist about AI's role and limitations in psychiatry, where contextual understanding and human interaction are particularly crucial. Objective: This study aimed to compare the performance of AI models (ChatGPT-3.5, Gemini Advanced, Claude Sonnet) with first-year psychiatry residents on theoretical exams and OSCEs covering Basic Neurosciences and Psychology, Sociology & Anthropology at a major Indian psychiatric institute. Methods: This cross-sectional study compared the performance of three large language models with first-year psychiatry residents (N=25) at the National Institute of Mental Health and Neurosciences (NIMHANS), an Institute of National Importance in India. Standardized theoretical exams and OSCEs were used, with AI and resident responses blindly scored by faculty against established rubrics. Four faculty members with ≥8 years of experience independently evaluated each AI model's theoretical examination responses using the same standardized rubrics applied to resident assessment. Results: AI models consistently surpassed residents in theory exams with Gemini Advanced achieving +5.14 standard deviations above resident mean in Neurosciences (71.25 ± 3.86 vs 58.0 ± 2.58) and Claude Sonnet achieving +8.77 standard deviations in Psychology (72.88 ± 3.77 vs 50.96 ± 2.49). In OSCEs, performance was comparable for Neurosciences (AI models: 13.0 vs residents: 13.16 ± 1.49), but varied for Psychology, where Gemini Advanced (18.0 ± 0.00) and Claude Sonnet (20.0 ± 1.41) exceeded the resident mean score (16.6 ± 1.55). Specific errors in AI responses included incorrect recall of standardized test details and misattribution of neuropsychological test functions. Conclusions: AI models demonstrated superior theoretical knowledge but variable clinical reasoning performance in psychiatric education assessments. While AI achieved exceptional scores in theoretical examinations, OSCE performance was inconsistent with notable factual errors absent in human responses. These findings indicate AI's potential as a supplementary tool for theoretical knowledge delivery and assessment, while confirming the necessity of human expertise for clinical skills evaluation.
Background: Developmental disabilities significantly impact children and impose substantial caregiving demands on parents, who often face emotional strain, isolation, and disrupted routines. Despite e...
Background: Developmental disabilities significantly impact children and impose substantial caregiving demands on parents, who often face emotional strain, isolation, and disrupted routines. Despite evidence that parent-support interventions enhance well-being and caregiving outcomes, there is limited synthesis of occupational therapy-related support programs specifically designed for parents of children with special needs. Objective: This scoping review aims to map existing evidence and identify gaps in support programs, emphasizing the importance of family-centered care and the unique contributions of occupational therapy to empower parents. Methods: A scoping review using the Joanna Briggs Institute’s methodology will systematically identify, map and analyze occupational therapy-related support programs for parents of children with special needs. A three-phase search strategy will include databases such as PubMed, Scopus, CINHAL, and Embase. Studies meeting the inclusion criteria- parents of children aged 3-15, peer-reviewed articles published in English, and focusing on various intervention types and contexts- will be analyzed. Results: Extracted data will be synthesized narratively and tabulated, highlighting program characteristics and outcomes to inform future evidence-based intervention Conclusions: A scoping review is therefore essential to provide an evidence-based foundation for designing impactful support programs that enhance family-centered care within the framework of occupational therapy. Clinical Trial: NA
Background: Psychotherapy chatbots powered by generative artificial intelligence (AI) have gained widespread use in a remarkably short period. Little is known, however, about their strengths and limit...
Background: Psychotherapy chatbots powered by generative artificial intelligence (AI) have gained widespread use in a remarkably short period. Little is known, however, about their strengths and limitations, particularly around the risks they may pose for vulnerable individuals. Objective: To determine the willingness of therapy chatbots to endorse highly problematic ideas proposed by fictional teenagers in distress. Methods: Ten AI sites offering therapeutic support or companionship were each presented with three fictional scenarios of adolescents with mental health challenges. Each fictional adolescent asked the AI chatbot to endorse two highly problematic proposals, resulting in a total of six proposals presented to each chatbot. The proposals were designed to be so extreme as to be highly unlikely to be supported by any competent human mental health clinician. Ten AI sites were selected by the author to represent a range of chatbot types (generic AI sites, companion sites, and dedicated mental health sites) that were highly popular. The clinical scenarios presented were intended to reflect challenges commonly seen in the practice of therapy with adolescents. Results: The therapy chatbots actively endorsed highly problematic ideas in 19 out of the 60 opportunities to do so, or 32%. Four of the ten chatbots endorsed half or more of the ideas proposed, and none of the bots opposed all of them. While all bots opposed drug use, many endorsed behaviors such as extreme isolation and inappropriate romantic involvement. Several bots failed to recognize euphemisms for suicidal ideation and neglected to encourage seeking adult intervention in risky situations. Conclusions: These results raise concerns about the ability of some AI-based therapists to safely support teenagers with serious mental health issues, and heighten concern that AI bots may tend to be overly supportive at the expense of offering useful guidance when appropriate. The results highlight the urgent need for oversight and transparency regarding digital mental health support for adolescents. Clinical Trial: NA
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: The growing burden of joint disorders, driven by the aging population, highlights the need for efficient surgical intervention. Clinical pathways (CPWs) standardize care, improve outcomes,...
Background: The growing burden of joint disorders, driven by the aging population, highlights the need for efficient surgical intervention. Clinical pathways (CPWs) standardize care, improve outcomes, and optimize resource use in orthopedic surgery. Objective: This narrative review examines the pivotal role of clinical pathways (CPWs) in knee and hip arthroplasties, essential procedures for enhancing patient quality of life. Methods: We conducted a narrative review focusing on how CPWs impact sustainability, quality, and resource management in knee and hip arthroplasties, integrating literature from PubMed and Cochrane databases according to PRISMA guidelines. Results: Enhanced Recovery After Surgery (ERAS) pathways and virtual clinics have significantly improved hospital discharge timelines, resource utilization, and patient satisfaction. Despite these benefits, challenges remain in balancing standardized care with individual patient needs. Conclusions: This review highlights the importance of CPWs in improving healthcare delivery and patient outcomes in orthopedic surgery. Future efforts should focus on refining CPWs, integrating digital tools, and maintaining flexibility to adapt to evolving healthcare demands.
Background: Emergency department (ED) overcrowding is a significant global challenge with profound implications for patient outcomes, healthcare delivery, and public health. Addressing this issue requ...
Background: Emergency department (ED) overcrowding is a significant global challenge with profound implications for patient outcomes, healthcare delivery, and public health. Addressing this issue requires comprehensive monitoring of patient flow, supported by a well-structured system of performance indicators. Identifying the root causes of overcrowding is crucial for developing targeted, evidence-based indicators to guide national policies. Hence, this study was conducted to systematically review the indicators used across different countries to measure ED overcrowding, aiming to inform strategies for improving ED capacity management and optimizing patient care. Objective: The primary objective of this study is to systematically identify and outline the indicators used to evaluate ED overcrowding across a range of hospital settings globally. Methods: A scoping review was conducted from October to November 2023. The selected articles were based on predefined criteria. The inclusion criteria require the articles reported in English and related to the keywords, published between 2013 and 2023, and include any study design (qualitative or quantitative). The databases used were PubMed, Emerald Insight, Google Scholar, and Scopus. The identified indicators were descriptively categorised according to input, throughput and output components based on the ED crowding model framework by Asplin et al. 2003 and summarised based on the indicators ranked from frequently used to the least. Results: Out of 1,347 articles screened, 117 articles were included in the study. A total of 314 indicators were retrieved and then consolidated into 26 distinct indicators. The majority (68.8%) fall within the throughput component, followed by 19.7% in the output component, while the input component accounts for the smallest proportion at 11.5%. Conclusions: This study highlights that throughput indicators were more prominently studied as key metrics in measuring ED overcrowding. The most frequently utilised throughput (TP) indicator is the ED length of stay, followed by waiting time and the rate of patients leaving without being seen. The review further demonstrates that length of stay (LOS) serves as a critical marker of systemic bottlenecks and operational inefficiencies within EDs. The findings provide valuable insights for policymakers to refine and strengthen existing indicators, helping to address and mitigate the issue of ED overcrowding.
Background: Systems psychodynamics provide valuable insights into organizational development. To date, instruments that can reliably assess organizations based on systems psychodynamic theories are la...
Background: Systems psychodynamics provide valuable insights into organizational development. To date, instruments that can reliably assess organizations based on systems psychodynamic theories are lacking, though. The Systematic Multidimensional Organisational Assessment (SyMOA) is a qualitative instrument that provides an in-depth, systems psychodynamic analysis of organizational dynamics by using a semi-structured interview guide. To complement the method, a standardized, quantitative self-assessment questionnaire will be developed and validated. Objective: The aim of this study is to develop and psychometrically validate an instrument for assessing organizational health based on the SyMOA diagnostic system. The questionnaire is intended to provide a scientifically grounded yet practical diagnostic tool applicable in both research and corporate practice. The findings aim to contribute to the advancement of systems psychodynamic theory and serve as a foundation for evidence-based interventions in organizational change processes. Methods: The study follows a multi-stage development and validation process. First, the SyMOA construct will be transformed into a questionnaire battery and the items will be evaluated by experts (expert validity). The items will be tested through factor and item analyses in an online panel (n=150) and iteratively refined. Subsequently, factorial validity, discriminant validity, and test-retest reliability will be examined before standardizing the instrument with a larger sample (n=800). Results: As of April 2025, a first draft of 158 items was developed based on Dimension I of the SyMOA framework. The draft underwent an expert review process with two experts in psychodynamics, who provided feedback on content validity and conceptual alignment. Approximately 20% of the items were revised to improve clarity and theoretical precision. Data collection using a panel is scheduled for the coming months, with iterative item analysis to be conducted thereafter. Results are expected to be published in late 2025. Conclusions: Parallel field application of the SyMOA framework in organizational settings complements the quantitative development by offering insights into its real-world relevance and usability. This integration underscores the instrument’s translational value, while also illustrating the practical challenges of applying systems psychodynamic diagnostics in organizational contexts. Clinical Trial: Freiburger Register Klinischer Studien FRKS005727
Background: The integration of digital technologies is becoming increasingly essential in cancer care. However, limited digital health literacy (DHL) among clinical and non-clinical cancer healthcare...
Background: The integration of digital technologies is becoming increasingly essential in cancer care. However, limited digital health literacy (DHL) among clinical and non-clinical cancer healthcare professionals poses significant challenges to effective implementation and sustainability over time. To address this, the European Union is prioritizing the development of targeted digital skills training programs for cancer care providers. A crucial initial step in this effort is conducting a comprehensive gap analysis to identify specific training needs. Objective: The aim of this work is to identify training gaps and prioritize the digital skill development needs in the oncology healthcare workforce. Methods: An Importance-Performance Analysis (IPA) was conducted. The survey assessed the performance and importance of seven digital skills: Information, Communication, Content Creation, Safety, e-Health Problem Solving, Ethics, and Patient Empowerment. Results: A total of 67 participants from 11 European countries completed the study: 38 clinical professionals (CP), 16 non-clinical professionals (NCP), and 13 patients/caregivers (PC). CP acknowledged the need for a comprehensive training program, that includes all the seven digital skills. Digital Patient Empowerment and Safety skills emerge as the highest priorities for both CP and NCP. Conversely, NCP assigned lower priority to digital Content Creation skills and PC to digital Information and Ethical skills. The IPA also revealed discrepancies in digital Communication skills across groups (H = 6.50; p<.05). Conclusions: The study showcased the pressing need for comprehensive digital skill training for cancer healthcare professionals across diverse backgrounds and healthcare systems in Europe. Based on the results the most urgent areas of digital skills training include digital Patient Empowerment and Safety skills. Incorporating patient and caregiver perspectives ensures a balanced approach to addressing these training gaps. These findings provide a valuable knowledge base for designing digital skills training programs, promoting a holistic approach that integrates the perspectives of the various stakeholders involved in digital cancer care.
Background: Mental health disorders are a growing public health concern among university students globally and in India, exacerbated by stigma and limited access to care. Mobile health (mHealth) apps...
Background: Mental health disorders are a growing public health concern among university students globally and in India, exacerbated by stigma and limited access to care. Mobile health (mHealth) apps offer a potential solution, but user engagement and cultural relevance remain challenges. This pilot study evaluates "Here for You," a mental health screening app co-developed with Indian university students to provide accessible, non-stigmatizing support. Objective: This study aimed to: (1) Describe the user-centered co-development and pilot testing process of the "Here for You" app; (2) Evaluate the app's feasibility, user acceptability, and engagement within the target population; and (3) Assess the concurrent validity of the app's screening tool (DASS-21) against established clinical measures (HAM-D, HAM-A, PSS). Methods: The study employed a four-phase, user-centred design involving students with lived mental health experience, clinicians, and developers. A purposive sample of 30 university students (mean age 21±1.8 years, 50% female) diagnosed with depression, anxiety, or stress participated. Participants completed the Depression, Anxiety, and Stress Scales-21 (DASS-21) via the app and underwent clinical assessments using HAM-D, HAM-A, and PSS scales. User experience was evaluated using the User Mobile App Rating Scale (UMARS) and qualitative feedback. Data analysis included Pearson correlations and thematic analysis. Results: App-based DASS-21 scores showed strong correlations with clinician-administered scales: HAM-D (r=0.819, p<0.001), HAM-A (r=0.887, p<0.001), and PSS (r=0.972, p<0.001), indicating high concurrent validity. The app received high usability ratings (mean UMARS score 4.4/5), particularly for functionality (4.7/5) and aesthetics (4.5/5). Qualitative feedback highlighted usability and enhanced privacy due to features like "Quick Exit," cultural resonance, and the desire for integrated support features. The co-design process directly addressed student concerns, implementing features like simplified language and crisis support links. Conclusions: This pilot study demonstrates the feasibility, validity, and user acceptability of the "Here for You" app, co-developed using a participatory approach with Indian university students. By integrating user experience, clinical rigor, and ethical safeguards like adherence to DPDP guidelines, the app offers a culturally resonant and scalable model for digital mental health screening in low-resource settings. This approach underscores the value of the "nothing about us without us" principle in developing effective mHealth interventions.
Background: Patient autonomy through informed consent is a foundational ethical principle for healthcare practitioners. "Consenting" online often produces "consent in name only", using manipulative or...
Background: Patient autonomy through informed consent is a foundational ethical principle for healthcare practitioners. "Consenting" online often produces "consent in name only", using manipulative or confusing user interfaces to artificially extract consent. This presents a significant danger for safe and ethical remote consultations for primary care providers, which often extract significant amounts of sensitive personal data. Objective: This study aims to examine the quality of consent obtained through both currently-used and novel consent acquisition mechanisms for remote electronic consultations. Methods: 52 UK adult participants interacted with a prototype electronic consultation system’s consent interface for data processing, and were then asked questions about what they had consented to, and the usability of the interface. These then led to the calculation of an industry-standard System Usability Scale (SUS) score, and a novel score for the Quality of Informed Consent Collected Digitally (QuICCDig). Results: Existing and novel user interfaces for collecting e-consultation consent were rated poorly, achieving a maximum SUS letter grade of “F”. Users perceiving interfaces to be more usable was statistically significantly correlated to an increase in the quality of consent collected from those users. 45.5% of participants reported not recalling making a privacy-related decision at all during their consultation, and 87.3% did not recall being offered any alternatives to e-consultation. Conclusions: Findings demonstrate current methods for collecting consent in telemedical applications may not be fit for purpose, and potentially fail to collect valid informed consent. Decision makers should therefore place importance on high-quality interface design when building or procuring these systems. We also provide the QuICCDig score for further use. Clinical Trial: N/A; not a clinical trial.
Background: Healthcare systems are increasingly confronted with the challenge of managing complex clinical processes. One proposed solution is a patient-centered management intervention called a care...
Background: Healthcare systems are increasingly confronted with the challenge of managing complex clinical processes. One proposed solution is a patient-centered management intervention called a care pathway that needs process mapping to support process improvement. Although the adoption and use of Business Process Model and Notation (BPMN) for modeling patient healthcare trajectories has increased, evidence of the benefits of implementing it in healthcare organization management systems are still unclear. Objective: This review sought to examine effectiveness by mapping evidence of implementation factors linking intended purpose to expected or demonstrated outcomes. Methods: A systematic review of the use of BPMN for modeling patient care trajectories was conducted across Medline (Ovid), Embase (Embase.com), Academic Search Premier, ABI/Inform (ProQuest), Web of Science, and Google Scholar. We followed the Cochrane Methods Group and the PRISMA guidelines. Quality appraisal was performed using the Mixed Methods Appraisal Tool (MMAT). Data were charted using a customized form and were analyzed thematically with both qualitative and semi-quantitative syntheses. Results: After screening, 53 studies were included. Our findings suggest that BPMN offers significant benefits in healthcare. Its use allows healthcare professionals to gain a comprehensive understanding of patient care pathways, making it easier to identify inefficiencies and areas for improvement. The definition of processes ensures that workflows remain consistent across different settings, thereby reducing variation and improving the quality of care. Several studies have demonstrated BPMN’s effectiveness in process optimization, highlighting its ability to streamline workflows, reduce redundancies, and enhance operational efficiency. Moreover, when integrated with decision-support tools, BPMN enhances clinical decision-making by enabling better adherence to guidelines and best practices. Another important advantage is BPMN’s interoperability with existing healthcare IT standards, such as HL7, which facilitates seamless integration with EHRs and other digital health systems. However, in a managerial perspective, users must also carefully weigh the trade-offs between BPMN’s benefits and its limitations, particularly in highly complex healthcare settings. Despite advantages, several challenges persist, including issues related to scalability, integration with advanced decision-making frameworks and the complexity of modeling dynamic healthcare environments. While BPMN is a widely adopted modeling approach, alternative methodologies offer complementary or competing advantages, such as Petri Nets, UML or Business Process Execution Language. Therefore, there are several opportunities for enhancing BPMN’s applicability in healthcare, such as the creation of domain-specific BPMN extensions or the integration of artificial intelligence and machine learning into BPMN models. Conclusions: This review highlights BPMN’s potential as a valuable tool for modeling patient healthcare trajectories. Its ability to standardize and optimize processes makes it a promising framework for improving clinical and operational efficiency. However, trade-offs between benefits and limits of BPMN characterized its implementation in patient care trajectories, giving rise to opportunities for the development and integration of new tools.
Background: Technology-assisted and robotic rehabilitation methods are increasingly used. Still, scarce evidence exists on their effects on upper extremity functioning after spinal cord injury. Object...
Background: Technology-assisted and robotic rehabilitation methods are increasingly used. Still, scarce evidence exists on their effects on upper extremity functioning after spinal cord injury. Objective: To evaluate the effects and feasibility of a 6-week intervention focusing on technology-assisted upper extremity rehabilitation in adults with incomplete cervical spinal cord injury (SCI). Methods: In this pilot randomized controlled crossover trial, 20 participants (10 men, 34–73 years of age, 1–8 years since SCI) were recruited by mail and randomized into two sequences (AB, n=10 and BA, n=10). All participants received a 6-week rehabilitation intervention during Period 1 or Period 2. The intervention was delivered 3 times a week for 6 weeks (18 sessions) by occupational therapists specialized in spinal cord injuries and neurorehabilitation. Each 1-hour rehabilitation session included a minimum of 30 minutes of technology-assisted rehabilitation using AMADEO®, DIEGO®, and/or PABLO® devices. Other occupational therapy activities were allowed to complete the session.
The effects of the 6-week rehabilitation intervention were compared to 6 weeks of no-intervention. Analyses were based on paired data. Each participant served as their own control. Hand and arm function were evaluated using the Action Research Arm Test, the American Spinal Injury Association – Upper Extremity Motor Score (ASIA-UEMS), grip strength, pinch strength, and the Spinal Cord Independence Measure – Self Report, and rehabilitation goal attainment by the Goal Attainment Scale (GAS). Face-to-face assessments were conducted at baseline, after Period 1, after Period 2, and at 6 months, except for the GAS, that was used at the beginning and immediately after the rehabilitation intervention. Results: The rehabilitation intervention showed good feasibility and tolerability in adults with incomplete cervical spinal cord injury. Of 20 (10+10) participants (median age 62, IQR 58–66), 19 enrolled in the study, and 17 completed at least 80% of the rehabilitation sessions. Fourteen out of 16 participants included in the final analysis attained their rehabilitation goals. The goals were mainly focusing on “fine hand use”, and “hand and arm use” related to self-care and domestic life. The effects of the rehabilitation intervention did not differ from no-intervention, except for the ASIA-UEMS in participants (n=7) who received the rehabilitation during Period 2. The sum score change of participants in Sequence BA was median 0 (-2–0) after no-intervention and 1 (0–2) after the rehabilitation intervention (P=.04). Conclusions: Results of this pilot study suggest that technology-assisted upper extremity rehabilitation provided by occupational therapists is safe and has potential for broader clinical use in adults with incomplete cervical spinal cord injury. The rehabilitation intervention showed good feasibility and positive outcomes, especially in rehabilitation goal attainment. Still, the results need to be confirmed in a larger randomized controlled trial. Clinical Trial: ClinicalTrials.gov NCT04760470
The increasing use of generative Large Language Models (LLMs) necessitates a fundamental reevaluation of traditional didactic lectures in medical education, particularly within psychiatry. The special...
The increasing use of generative Large Language Models (LLMs) necessitates a fundamental reevaluation of traditional didactic lectures in medical education, particularly within psychiatry. The specialty's inherent diagnostic ambiguity, biopsychosocial complexity, and reliance on nuanced interpersonal skills demand an educational model that transcends mere information transfer, focusing instead on cultivating sophisticated clinical reasoning. This commentary argues for a shift from passive knowledge transmission to the active, facilitated development of higher-order thinking, aligning with Bloom's Taxonomy. We propose four core propositions: 1) Shifting foundational knowledge acquisition to faculty-curated, asynchronous AI-assisted micro-modules. 2) Transforming synchronous time into "Ambiguity Seminars" for discussing nuanced cases, biopsychosocial formulation, and ethical dilemmas, leveraging faculty expertise in guiding reasoning. 3) Integrating live LLM critical interaction drills to develop prompt engineering skills and critical appraisal of AI outputs. 4) Realigning assessment methods (e.g., OSCEs, reflective writing) to evaluate clinical reasoning and integrative skills rather than rote recall. Successful implementation requires robust faculty development and resource allocation. This reimagined approach aims to cultivate clinical wisdom equipping psychiatric trainees with adaptive reasoning frameworks essential for excellence in an AI-mediated future.
Background: Most medical schools do not require anesthesiology as part of their clerkship curricula, limiting student exposure to the specialty. Objective: This study aims to investigate whether the C...
Background: Most medical schools do not require anesthesiology as part of their clerkship curricula, limiting student exposure to the specialty. Objective: This study aims to investigate whether the California Anesthesiology Medical Student Symposium (CAMSS), a one-day conference composed of anesthesiology lectures and workshops led by residency program leaders, can increase student knowledge or interest in anesthesiology. Methods: The Annual CAMSS of 2022 was organized at University of California Irvine School of Medicine by medical students and residency program leaders. An online survey was distributed to all registered students three days prior to the conference and immediately afterwards. Student exposure, knowledge, and interest in anesthesiology were evaluated using Likert-scales. Pre-conference versus post-conference results were analyzed using two-sample t-tests with a p-value < 0.05 considered as statistically significant. Results: The pre-conference survey was emailed to all 96 students who registered for the conference, 68 of which completed the survey (response rate 70.8%). The post-conference survey was emailed to all 83 students who attended the conference, 51 of which completed the survey (response rate 61.4%). On a Likert scale of 1-10, post-conference survey responses revealed a statistically significant increase in self-perceived knowledge of anesthesiology compared to pre-conference surveys (mean 6.44, SD 1.79 vs. mean 4.71, SD 2.07 respectively; p < 0.001). Conclusions: A one-day anesthesiology-focused conference can increase medical students’ self-perceived knowledge of the specialty’s multifaceted role in the hospital setting. Clinical Trial: This prospective cohort observational study was approved by University of California, Los Angeles Medical Institutional Review Board (IRB) # 21-001825.
Background: Digital shared medication records (DSMRs) are promoted to improve medication management across care settings, but implementation remains slow and challenging. Existing systems often fail t...
Background: Digital shared medication records (DSMRs) are promoted to improve medication management across care settings, but implementation remains slow and challenging. Existing systems often fail to reflect patient-led changes, raising questions about why national initiatives do not allow patients or family caregivers to be directly involved in updating shared information. At the same time, little is known about how patients perceive these tools and what they expect. Public and patient involvement in the design of such systems has been minimal, leaving a critical gap in user-centered evidence to guide implementation. Objective: This study aimed to develop and pilot test a discrete choice experiment (DCE)-based survey instrument to assess patient preferences and estimated uptake of DSMRs. The tool is intended to inform the co-design of digital medication records that align with patient needs and support broader stakeholder decision-making. Methods: We developed the survey instrument in three phases. First, we identified relevant DSMR features from scientific literature and Swiss policy and technical documents. Second, we conducted a stakeholder and expert prioritization exercise to select attributes for the DCE. Third, we refined the attributes and levels through think-aloud interviews with patients. The final survey included the DCE, items on potential adoption factors, and questions addressing current policy concerns. We pilot-tested it online with 300 patients who regularly take multiple medications. Results: An initial list of 31 concepts was refined into 17 dimensions, ultimately yielding seven key DSMR attributes for the pilot: content, update responsibility, access rights, tool purpose, additional features, data protection, and financial incentives. Choice model estimations confirmed expected preference directions. Financial incentives, responsibility for updating, and data protection had the strongest influence on uptake, followed by content and primary purpose. Access rights and extra features were less impactful. Respondents favored collaborative medication plan management involving both patients and professionals over professional-only approaches. Conclusions: The instrument demonstrated strong potential for larger-scale use in Switzerland, with minor adaptations recommended for other settings. Health authorities and innovators can use this tool to test DSMR design and implementation strategies while generating context- and population-specific insights that would otherwise require costly and time-intensive evaluations. This approach supports strategic planning, including simulations to tailor implementation across subgroups. Such foresight can help optimize investments and reduce the risk of widening health inequities and digital divides. More broadly, the instrument provides a practical method for engaging the public in digital health policymaking and co-creating patient-centered services.
Background: Distinguishing bipolar disorder (BD) from attention-deficit/hyperactivity disorder (ADHD) and other common psychopathology in adolescents remains a diagnostic challenge due to overlapping...
Background: Distinguishing bipolar disorder (BD) from attention-deficit/hyperactivity disorder (ADHD) and other common psychopathology in adolescents remains a diagnostic challenge due to overlapping symptoms of mood and activity fluctuations Objective: To investigate same-day correlations between actigraphy-derived physical activity and self-reported mood/energy ratings, and to evaluate whether these measures can support differential diagnosis of BD, ADHD, and other psychopathologies in adolescents using both traditional statistics and machine learning. Methods: We included 209 hospitalized adolescents (2,148 patient-days) across four diagnostic groups: BD without ADHD (n=34), ADHD without BD (n=54), BD+ADHD (n=42), and Other Diagnoses (n=79). Actigraphy data were categorized into quartiles (Max1st–Max4th, Min1st–Min4th), and MET scores (-10 to +10) were classified into severity ranges (OK [<3], Mild [3–4], Moderate [5–6], Severe [>6]). Non-parametric analyses (Kruskal-Wallis, Mann-Whitney U) assessed group differences, and categorical associations were evaluated using chi-square tests with Cramér’s V effect sizes. To account for multiple comparisons, Bonferroni correction was applied (p-corrected < 0.004). Three machine learning models—XGBoost, Random Forest, and Ridge Regression—were developed to predict daily mood (MoodMean) from actigraphy-derived and self-reported energy features. Results: This study analyzed 2,148 inpatient days from 209 adolescents across four diagnostic groups (BD without ADHD, BD+ADHD, ADHD without BD, and Other Diagnoses). Actigraphy data were transformed into maximum and minimum quartiles, and daily mood and energy ratings were recorded using the Mood & Energy Thermometer (MET). Non-parametric tests and chi-square analyses with Cramér’s V were used to assess group-level differences and associations. Three machine learning models—XGBoost, Random Forest, and Ridge Regression—were developed to predict daily mood (MoodMean) from actigraphy-derived and self-reported energy features. Feature importance was analyzed within and across diagnostic groups. Conclusions: : Our findings supported importance of digital phenotyping where objective actigraphy combined with self-report energy metrics can accurately estimate mood and improve differential diagnosis and may personalize interventions in youth.
Background: Society guidelines for prostate cancer screening via PSA testing serve to standardize patient care, and are often utilized by trainees, junior staff, or generalist medical practitioners to...
Background: Society guidelines for prostate cancer screening via PSA testing serve to standardize patient care, and are often utilized by trainees, junior staff, or generalist medical practitioners to guide medical decision-making. Adherence to guidelines is a time-consuming and challenging task and rates of inappropriate PSA testing are high. Objective: This study evaluates a retrieval-augmented generation (RAG) enhanced large language model (LLM), grounded in current EAU and AUA guidelines, to assess its effectiveness in providing guideline-concordant PSA screening recommendations compared to junior clinicians. Methods: A retrieval-augmented generation (RAG) pipeline was developed and used to process a series of 44 fictional case scenarios. Five junior clinicians were tasked to provide PSA testing recommendations for the same scenarios, in closed-book and open-book formats. Answers were compared for accuracy in a binomial fashion. Results: The RAG-LLM tool provided guideline-concordant recommendations in 95.5% of case scenarios, compared to junior clinicians, who were correct in 62.3% of scenarios in a closed-book format, and 74.1% of scenarios in an open book format. The difference was statistically significant for both closed-book (p <0.001) and open-book (p <0.001) formats. Conclusions: Use of RAG techniques allows LLMs to integrate complex guidelines into day-to-day medical decision-making. RAG-LLM tools in Urology have the capability to enhance clinical decision-making by providing guideline-concordant recommendations for PSA testing, potentially improving the consistency of healthcare delivery, reducing cognitive load on clinicians, and reducing unnecessary investigations and costs.
Background: Ozempic (semaglutide) has received widespread attention for its appetite-suppressing effects, prompting extensive off-label use for weight loss. Although gastrointestinal side effects are...
Background: Ozempic (semaglutide) has received widespread attention for its appetite-suppressing effects, prompting extensive off-label use for weight loss. Although gastrointestinal side effects are well documented, little is known about how patients evaluate the trade-off between perceived benefits and adverse effects, or how these evaluations influence treatment discontinuation. Objective: This study aimed to apply a novel infoveillance approach to examine patient-reported experiences with Ozempic when used off-label for weight loss, and to identify the factors most strongly associated with user satisfaction and treatment discontinuation. Methods: We analyzed 60 publicly available user reviews of Ozempic from Drugs.com, focusing on lived experiences of off-label use for weight loss. Reviews were examined through inductive thematic analysis, and emergent themes were quantitatively linked to user ratings of perceived efficacy and intent to continue or discontinue treatment. Results: While 80% of reviewers reported gastrointestinal complaints, these side effects had limited influence on satisfaction ratings or treatment continuation. Positive evaluations were driven by satisfaction with weight loss outcomes, whereas negative evaluations were associated with either disappointing weight outcomes or severe non-gastrointestinal side effects. Dissatisfaction with weight loss emerged as the strongest predictor of treatment discontinuation. Conclusions: This study introduces a novel application of infoveillance methods to capture patient attitudes toward off-label use of Ozempic. By analyzing unsolicited, real-world data, we identified key drivers of satisfaction and discontinuation that may be missed by traditional clinical approaches. These findings highlight the utility of online health forums as a rich and underutilized source of patient-centered insights to inform obesity treatment strategies, adherence interventions, and public health communication. Clinical Trial: N/A
Background: Cervical spondylosis (CS), a progressive degenerative disorder often leading to neurological impairment, remains poorly characterized in terms of its association with routine biochemical m...
Background: Cervical spondylosis (CS), a progressive degenerative disorder often leading to neurological impairment, remains poorly characterized in terms of its association with routine biochemical markers. This multicenter study aimed to identify novel CS subtypes through unsupervised clustering of clinical and laboratory biomarkers, subsequently developing a predictive model for postoperative recurrence. Objective: This study aimed to leverage unsupervised machine learning to delineate clinically actionable cervical spondylosis (CS) subtypes based on preoperative biomarker profiles, and further establish a predictive nomogram for postoperative recurrence risk stratification. By integrating clustering-driven phenotyping with supervised feature selection, we sought to bridge the gap between heterogeneous inflammatory signatures and surgical complexity, ultimately guiding subtype-specific therapeutic decision-making. Methods: In this study, 884 cervical spondylopathy patients who underwent Cervical spondylosis surgery were enrolled at the Department of Spine Osteopathology, the First Affiliated Hospital of Guangxi Medical University from June 2012 to June 2021. After screening, 715 patients were eventually included. After 7:3 training-validation split, k-means clustering stratified patients into subtypes based on 37 preoperative variables. Feature selection integrated LASSO regression and Random Forest algorithms, with subsequent nomogram construction via multivariable logistic regression. Model performance was evaluated through ROC analysis and calibration curves. Results: Unsupervised clustering delineated two subtypes with distinct profiles: Subtype 1 (n=215) exhibited milder inflammation (CRP: 2.1±1.1 mg/L) versus Subtype 2 (n=580) demonstrating marked systemic inflammation (CRP: 8.7±3.2 mg/L, p<0.001). The nomogram incorporating neutrophil count, lymphocyte levels, eosinophil percentage, basophils, and cystatin C showed exceptional discrimination (AUC=0.996, 95% CI: 0.985-1.000). Despite equivalent JOA improvement rates (>25% in both subtypes), Subtype 2 required more multilevel decompressions (35.5% vs. 17.5%, p<0.001). Conclusions: Our machine learning framework successfully identifies inflammatory-driven CS phenotypes with differential surgical complexity. The validated nomogram enables preoperative risk stratification, potentially guiding personalized rehabilitation strategies. Prospective validation across diverse populations is warranted to confirm clinical utility.
Background: Digital tools have been shown to play a role in promoting public health interventions. The recommendation that healthcare providers (HCPs) use vaccination-related mobile or web-based appli...
Background: Digital tools have been shown to play a role in promoting public health interventions. The recommendation that healthcare providers (HCPs) use vaccination-related mobile or web-based applications has contributed to improving vaccine awareness and acceptance among vaccine-eligible individuals. In the United States, the state of Texas, which has one of the lowest HPV vaccination rates, has seen a significant increase in HPV vaccination hesitancy during the COVID-19 pandemic. Objective: This study examined the association between changes in the HPV vaccine hesitancy observed by HCPs among patients in Texas and the promotion of vaccination-related applications at their healthcare facilities during the COVID-19 pandemic. Methods: A population-based cross-sectional survey administered to HCPs working in Texas between January and April 2021 by The University of Texas MD Anderson Cancer Center was used for this study. We described the observed changes in the HPV vaccination hesitancy reported by the HCPs among patients using descriptive statistics. We conducted a logistic regression analysis to examine the association between the decrease in the HPV vaccine hesitancy observed by HCPs among patients and the promotion of vaccination-related applications at their facility. Results: A total of 1283 HCPs completed the survey. Among the 730 HCPs who reported changes in the HPV vaccination hesitancy, 7.0% observed a decrease in the HPV vaccine hesitancy among patients during the COVID-19 pandemic. Among the 576 HCPs who responded to the survey question regarding vaccination-related applications, 20.7% reported that vaccination-related applications were promoted at their facilities. The respondents were predominantly aged 35-54 years (62.6%), females (77.3%), non-Hispanic Whites (50.5%), and working in group practice (39.6%). Compared to HCPs who did not promote vaccination-related applications, those who promoted vaccination-related applications at their healthcare facility had significantly higher odds of observing a decrease in HPV vaccine hesitancy among patients during the COVID-19 pandemic (Adjusted Odds Ratio [aOR]: 2.53, 95% CI: 1.18-5.41). Compared to HCPs who worked at university/teaching hospitals, HCPs working at Federally Qualified Health Clinics (aOR: 8.96, 95% CI: 1.74-46.10), public facilities (aOR: 12.53, 95% CI: 2.01-78.26) and Employed Physician Practices (aOR: 8.63, 95% CI: 1.37-54.39) had significantly higher odds to observe a decrease in the HPV vaccine hesitancy among patients during the COVID-19 pandemic. Conclusions: Our findings demonstrate the benefits of promoting vaccination-related applications at healthcare facilities in areas with high HPV vaccine hesitancy, such as Texas. Digital health interventions could provide a platform for promoting and increasing HPV vaccination uptake in a context of pandemic preparedness. Clinical Trial: N/A
Background: In Mexico, the maternal and child population continues to face a high burden of malnutrition, posing a persisted public health challenge. The healthcare system plays a crucial role, not on...
Background: In Mexico, the maternal and child population continues to face a high burden of malnutrition, posing a persisted public health challenge. The healthcare system plays a crucial role, not only in addressing existing cases but also in preventing and detecting malnutrition early. Mobile health (mHealth) technologies have the potential to strengthen maternal and child health services by improving the quality, accessibility, and timeliness of nutritional care. Objective: The aim was to develop and validate the design and content of a mobile application—CANMI (Calidad de la Atención Nutricional Materno Infantil, by its Spanish acronym) — to monitor the quality of maternal and child nutritional care in primary health care units in Mexico. Methods: The framework of the CANMI app was based on the 16 validated indicators designed to assess the quality of nutritional care during the preconception, pregnancy, postpartum, early childhood, and preschool stages. The application was developed for both iOS and Android systems using a user-centered design approach. Following development, a pilot usability study was conducted in a randomized sample of 18 primary health care units in Guanajuato, Mexico. Trained nutritionists implemented the app and collected usability data at the end of the initial usage period and again six weeks later. To further explore user experience, semi-structured online interviews were conducted to identify barriers, facilitators, and overall satisfaction with the app. Results: The CANMI app allows the systematic registration of key indicators to assess the quality of nutritional care in primary health care settings. Users described the app as simple, intuitive, and visually appealing. Overall usability was rated positively, with a mean score of 71.13 on the System Usability Scale (SUS) indicating good acceptability. The app’s offline functionality, streamlined interface, and efficiency in data collection were identified as key facilitators of use. Reported benefits included reduced time for data entry and perceived improvements in the quality of nutritional care. Identified barriers to integration included the need to use personal devices, user fatigue due to prolonged screen time, inconsistent clinical records, and limited time to incorporate the app into routine workflows. Importantly, the app encouraged promoted improvements in documentation practices and heightened awareness among health personnel regarding the precision and clarity of their nutritional recommendations. Conclusions: The CANMI app provides a feasible and effective solution for monitoring the quality of maternal and child nutritional care in primary health settings. Its high usability and offline capabilities make it particularly suitable for low-connectivity environments. Beyond facilitating data collection, the app contributed to improved clinical documentation practices and enhanced provider awareness of care quality. As such, the application can represent a promising digital tool to support the implementation evidence-based, user-centered strategies aimed at strengthening maternal and child health services in resource- limited contexts. Clinical Trial: The study protocol was reviewed and approved by the Research Ethics Committee of the Universidad Iberoamericana in Mexico City (172/2022).
Background: Large language models (LLMs) such as ChatGPT have shown promise in medical education assessments, but the comparative effects of prompt engineering across optimized variants and relative p...
Background: Large language models (LLMs) such as ChatGPT have shown promise in medical education assessments, but the comparative effects of prompt engineering across optimized variants and relative performance against medical students remain unclear. Objective: To systematically evaluate the impact of prompt engineering on five ChatGPT variants (GPT-3.5, GPT-4.0, GPT-4o, GPT-4o1mini, GPT-4o1) and benchmark their performance against fourth-year medical students in midterm and final examinations. Methods: A 100-item examination dataset covering multiple-choice, short-answer, clinical case analysis, and image-based questions was administered to each model under no-prompt and prompt-engineered conditions over five independent runs. Student cohort scores (n=143) were collected for comparison. Responses were scored using standardized rubrics, converted to percentages, and analyzed in SPSS Statistics 29 with paired t-tests and Cohen’s d (p<0.05). Results: Baseline midterm scores ranged from 59.2% (GPT-3.5) to 94.1% (GPT-4o1); final scores from 55.0% to 92.4%. Fourth-year students averaged 89.4% (midterm) and 80.2% (final). Prompt engineering significantly improved GPT-3.5 (+10.6%, p<0.001) and GPT-4.0 (+3.2%, p=0.002) but yielded negligible gains for optimized variants (p=0.066–0.94). Optimized models matched or exceeded student performance on both exams. Conclusions: Prompt engineering enhances early-generation model performance, whereas advanced variants inherently achieve near-ceiling accuracy, surpassing medical students. As LLMs mature, emphasis should shift from prompt design to model selection, multimodal integration, and critical use of AI as a learning companion. Clinical Trial: IRB #CSMU-2024-075
Abstract:
The convergence of biomedical technology and digital marketing has catalyzed a paradigm shift in healthcare delivery, conceptualized through the PAO “(Patient as an Organization)” model...
Abstract:
The convergence of biomedical technology and digital marketing has catalyzed a paradigm shift in healthcare delivery, conceptualized through the PAO “(Patient as an Organization)” model. This model reconceives patients as autonomous, data-driven entities empowered by AI diagnostics, wearable devices, and mobile health tools. This study investigates how biomedical innovations intersect with healthcare marketing strategies to operationalize the PAO framework, enhancing patient engagement, service uptake, and system adaptability. Using systematic Literature Review (SLR) across four major databases from 2014 to 2024 and qualitative research design informed by open, axial, and selective coding. Findings indicate that integrating biomedical tools with digital marketing—via behavioral segmentation, CRM systems, and personalized outreach—enables continuous patient monitoring, proactive care delivery, and strategic responsiveness. The PAO model emphasizes shifting from episodic care to dynamic, personalized interventions. The study recommends adaptive health infrastructures, digital literacy among providers, and ethically guided policy frameworks to support inclusive, data-driven ecosystems. PAO thus reframes patients as co-managers of care, redefining healthcare through technological and ethical alignment.
Background: Lifestyle modification involving both patients and their significant others (dyads) is critical in the long-term management of chronic kidney disease (CKD). However, achieving sustained be...
Background: Lifestyle modification involving both patients and their significant others (dyads) is critical in the long-term management of chronic kidney disease (CKD). However, achieving sustained behavioral changes remains challenging. Digital interventions, particularly using widely adopted platforms like instant messaging apps, present a promising approach to support CKD dyads in lifestyle modification. Objective: This study aimed to develop, optimize, and test the usability of a digital dyadic empowerment platform named “Kidney Lifestyle” using the LINE instant messaging app. The platform was designed based on the Digital Dyadic Empowerment Framework (DDEF) to facilitate collaborative lifestyle modification among CKD dyads. Methods: We adopted a three-phase Agile-based iterative development cycle: (1) iterative development and trial use, (2) heuristic evaluation, and (3) usability testing. In Phase 1, platform prototype was co-developed with healthcare professionals and technical partners, then trialed by CKD dyads who provided qualitative and quantitative feedback on interface clarity, ease of use, acceptance, intention to continue usage, and overall satisfaction. In Phase 2, multidisciplinary experts independently conducted heuristic evaluations, rating platform compliance with Nielsen’s ten usability principles on a scale from -1 (does not comply) to 1 (complies), and provided suggestions for improvement. In Phase 3, experienced CKD dyads from Phase 1 performed six representative tasks using the platform. Task success rates, completion times, and operational errors were quantitatively recorded, and usability perceptions were assessed using the After-Scenario Questionnaire (ASQ; 1-7 scale) and the System Usability Scale (SUS; 0-100 scale). Results: Phase 1 results indicated high user acceptance and satisfaction (overall platform satisfaction: mean 4.1 out of 5) among 10 CKD dyads (19 individuals). Participants valued real-time interaction, convenience in monitoring health data, and educational resources. In Phase 2, five experts conducted heuristic evaluation, revealing high overall usability compliance (average compliance scores ranged from 89% to 93%), although issues related to navigation complexity and the need for enhanced interactive feedback were identified. In Phase 3, usability testing was conducted with 5 CKD dyads (10 individuals), showing high task success rates (60%-100%) and task completion times ranging from 1 to 5 minutes. However, navigation difficulties within the LINE Official Account were noted, resulting in a marginally acceptable average SUS score of 67.5. The ASQ indicated higher usability satisfaction for the extended App tasks (mean average = 5.64) compared to those within LINE (mean average = 3.87). Conclusions: The LINE-based digital dyadic empowerment platform “Kidney Lifestyle” (LINE ID: @509kgajt) demonstrated promising usability, high user engagement, and strong clinical potential for supporting lifestyle modification among CKD dyads. However, usability issues within the instant messaging interface highlight the importance of simplifying navigation pathways and enhancing user feedback. Future research should include a larger-scale feasibility trial and further optimization to enhance usability and clinical integration.
Background: Artificial intelligence (AI) has shown promise for automating spinal alignment assessment in adolescent idiopathic scoliosis (AIS). However, AI models typically exhibit reduced accuracy an...
Background: Artificial intelligence (AI) has shown promise for automating spinal alignment assessment in adolescent idiopathic scoliosis (AIS). However, AI models typically exhibit reduced accuracy and robustness when deployed across multiple medical centres due to variability in imaging protocols and data characteristics, potentially compromising clinical diagnosis and treatment decisions. Objective: This study aimed to develop a real-time, plug-and-play data transformation method to enhance the robustness of deep learning models against data heterogeneity in radiographs, thereby improving their performance in assessing AIS across multiple medical centres. Methods: In this retrospective multicentre study, 4,111 full-spine radiographs from seven hospitals (two from Hong Kong and five from mainland China), collected between January 2012 and August 2024, were included. Data from two hospitals in Hong Kong (n=3,034) were used for model training and internal validation, while radiographs from the five mainland hospitals (n=1,077) formed five independent external validation datasets. A novel pixel-intensity-based data transformation method was developed to standardize image contrast and brightness across datasets and integrated into the model training process to enhance our previously developed AI model, SpineHRNet+. The enhanced model's accuracy and robustness for Cobb angle prediction and severity classification were evaluated using both internal and external datasets. Data heterogeneity across centres was quantified by brightness and contrast differences. Cobb angle prediction accuracy was evaluated using residual analysis, linear regression (coefficient of determination [R²]), and Bland-Altman analyses. Model performance for disease severity classification was assessed using sensitivity, specificity, precision, negative predictive value (NPV), accuracy, and confusion matrix analysis. Results: In this retrospective multicentre study, 4,111 full-spine radiographs from seven hospitals (two from Hong Kong and five from mainland China), collected between January 2012 and August 2024, were included. Data from two hospitals in Hong Kong (n=3,034) were used for model training and internal validation, while radiographs from the five mainland hospitals (n=1,077) formed five independent external validation datasets. A novel pixel-intensity-based data transformation method was developed to standardize image contrast and brightness across datasets and integrated into the model training process to enhance our previously developed AI model, SpineHRNet+. The enhanced model's accuracy and robustness for Cobb angle prediction and severity classification were evaluated using both internal and external datasets. Data heterogeneity across centres was quantified by brightness and contrast differences. Cobb angle prediction accuracy was evaluated using residual analysis, linear regression (coefficient of determination [R²]), and Bland-Altman analyses. Model performance for disease severity classification was assessed using sensitivity, specificity, precision, negative predictive value (NPV), accuracy, and confusion matrix analysis. Conclusions: The proposed data transformation approach effectively addressed data heterogeneity, significantly improving the accuracy and robustness of SpineHRNet+ in multicentre AIS assessments. The real-time processing capability and preservation of anatomical integrity underscore the method’s clinical practicality, enabling scalable and reliable AI applications in diverse healthcare environments. Clinical Trial: Name: Artificial Intelligence-based Models for Spine Malalignment Auto-analysis
ClinicalTrials.gov ID: NCT06711757
URL: https://clinicaltrials.gov/study/NCT06711757?cond=NCT06711757&rank=1&tab=results
Background: Promoting individual resilience – i.e., maintaining or regaining mental health despite stressful circumstances – is often regarded as important endeavor to prevent mental illness. Howe...
Background: Promoting individual resilience – i.e., maintaining or regaining mental health despite stressful circumstances – is often regarded as important endeavor to prevent mental illness. However, digital resilience interventions designed to enhance mental health outcomes, including stress levels and self-perceived resilience, have yielded mixed results. Such heterogeneous effects reflect a variety of unsolved conceptual challenges in interventional resilience research. These range from grounding interventions in genuine resilience frameworks, using theory or targeting etiologically important resilience factors as intervention content, to a lack of knowledge about the mechanisms underlying effects, and employing techniques specifically developed to foster psychosocial resources. The web- and app-based resilience intervention RESIST was designed to address these challenges, mainly by utilizing both the Positive Appraisal Style Theory of Resilience as its theoretical foundation and interventional techniques from Strengths-based Cognitive Behavioral Therapy. Objective: The study’s primary aim was to evaluate the effectiveness of RESIST in a general working population as a means of universal prevention, relative to a waitlist control group. A secondary study aim was to explore the resilience factors of self-efficacy, optimism, perceived social support, and self-compassion the intervention targets as potential mediators of its effect on stress and self-perceived resilience. Methods: In total, 352 employees were randomly assigned to either a self-help version of RESIST or waitlist control group. Data were collected at baseline, post-intervention, and at 3- and 6-month (intervention group only) follow-up. The primary outcome was perceived stress, measured with the Perceived Stress Scale-10. Secondary outcomes included self-perceived resilience, the resilience factors targeted, and other mental and work-related health outcomes. Results: The intervention group reported significantly less stress than controls post-intervention (Δ=-3.14; d=-0.54, 95%CI -0.75 to -0.34, and P<.001) and at 3-month follow-up (Δ=-2.79; d=-0.47, 95%CI -0.71 to -0.22, and P=.002). These improvements in the intervention group were maintained at 6-month follow-up. Favorable between-group differences also were detected for self-perceived resilience and the resilience factors. Effects on other mental and work-related outcomes were mixed. Parallel mediation analyses revealed significant indirect effects of optimism (a2b2=-0.34, 95% CI -0.63 to -0.06) and self-compassion (a4b4=-0.66, 95% CI -1.15 to -0.17) on perceived stress, whereas indirect effects through self-efficacy and social support were not found. A similar pattern emerged for self-perceived resilience as mediation outcome. Conclusions: In a sample of employees experiencing heightened work-burden levels, RESIST was effective in reducing perceived stress, and increasing self-perceived resilience as well as the targeted resilience factors. Mediation analyses suggested that developing a positive future outlook and a self-compassionate attitude toward oneself may be key drivers to enhance resilience. Changing the quality of social relationships and strengthening the belief in one’s abilities may require more time, the involvement of others, or personal support from a mental health professional, such as an e-coach, to ensure sufficient learning opportunities. Clinical Trial: German Clinical Trials Register DRKS00017605; https://drks.de/search/de/trial/DRKS00017605
Background: Medical students face multiple challenges related to acquiring clinical and communication skills, building professional relationships, and managing psychological stress at the beginning of...
Background: Medical students face multiple challenges related to acquiring clinical and communication skills, building professional relationships, and managing psychological stress at the beginning of their clinical clerkships (CCs). While mentoring and structured feedback are known to provide critical support, existing systems may not offer sufficient and timely guidance, owing to faculty’s limited availability. Generative artificial intelligence (gAI), particularly large language models, offers new opportunities to support medical education by providing context-sensitive responses. Objective: This study aimed to develop and evaluate a gAI CC mentor (AI-CCM) based on ChatGPT and evaluate its effectiveness in supporting medical students’ clinical learning, addressing their concerns, and supplementing human mentoring. The secondary objective was to compare AI-CCM’s educational value with responses from senior student mentors. Methods: We conducted two studies. In Study 1, we created 5 scenarios based on challenges students commonly encountered during CC. For each scenario, five senior student mentors and AI-CCM generated written advice. Five medical education experts evaluated these responses using a rubric to assess accuracy, practical utility, educational appropriateness (5-point Likert scale), and safety (binary scale). In Study 2, 17 fourth-year medical students used the AI-CCM for 1 week during their CC and completed a questionnaire evaluating its usefulness, clarity, emotional support, and impact on communication and learning (5-point Likert scale), informed by the Technology Acceptance Model. Results: All responses indicate that AI-CCM achieved higher scores than senior student mentors. AI-CCM responses were rated higher in educational appropriateness (4.2 ± 0.7 vs 3.8 ± 1.0, p = .001); no significant differences were observed in accuracy (4.4 ± 0.7 vs 4.2 ± 0.9, p = .111) or practical utility (4.1 ± 0.7 vs 4.0 ± 0.9, p = .347). No safety concerns were identified in AI-CCM responses, whereas two concerns were noted in student mentors’ responses. Scenario-specific analysis revealed that AI-CCM performed significantly better in emotional and psychological stress scenarios. In the student trial, AI-CCM was rated as moderately useful (mean usefulness 3.9 ± 1.1), with positive evaluations for clarity (4.0 ± 0.9) and emotional support (3.8 ± 1.1). However, aspects related to feedback guidance (2.9 ± 0.9) and anxiety reduction (3.2 ± 1.0) received more neutral ratings. Students primarily consulted AI-CCM regarding learning workload and communication difficulties; few students used it to address emotional stress-related issues. Conclusions: AI-CCM has potential as a supplementary educational partner during CC and offers comparable support to senior student mentors in structured scenarios. Despite challenges of response latency and limited depth in clinical content, AI-CCM was received well by, and accessible for, students who used ChatGPT’s free version. With further refinements, including specialty-specific content and improved responsiveness, AI-CCM may serve as a scalable context-sensitive support system in clinical medical education. Clinical Trial: None
Background: Telemedicine has gained attention as a transformative solution to reduce healthcare disparities, especially in low-resource settings. In Iran, the full potential of telemedicine remains un...
Background: Telemedicine has gained attention as a transformative solution to reduce healthcare disparities, especially in low-resource settings. In Iran, the full potential of telemedicine remains unrealized due to fragmented policies, infrastructural limitations, and cultural resistance. Objective: This study aimed to explore the key challenges and strategies for implementing and expanding telemedicine within Iran’s healthcare system. Methods: A qualitative study using conventional content analysis was conducted based on semi-structured interviews with 20 experts from healthcare policy, academia, clinical practice, and digital health sectors. Data were analyzed using ATLAS.ti9 until theoretical saturation was reached. Results: Seven major thematic domains were identified: (1) Policy-making (roadmaps, legal frameworks), (2) Management (technical support, operational planning), (3) Legislation (liability and data security laws), (4) Technical infrastructure (hardware, software, connectivity), (5) Education (training and public awareness), (6) Financial provision (funding and insurance models), and (7) Information management (EHRs and cybersecurity). Key barriers included fragmented governance, limited rural internet infrastructure, resistance from clinicians, and insufficient funding. Strategic solutions focused on multisectoral collaboration, phased infrastructure investment, stakeholder education, and development of comprehensive legal and technical guidelines. Conclusions: A holistic, adaptive implementation approach is essential to institutionalize telemedicine in Iran. The findings provide practical insights for Iran and other resource-constrained countries seeking to scale equitable, sustainable telehealth services. Clinical Trial: Not applicable. Qualitative study.
Background: The Japanese National Medical Licensing Examination (NMLE) is mandatory for all medical graduates to become licensed physicians in Japan. Given the cultural emphasis on summative assessmen...
Background: The Japanese National Medical Licensing Examination (NMLE) is mandatory for all medical graduates to become licensed physicians in Japan. Given the cultural emphasis on summative assessment, the NMLE has had a significant impact on Japanese medical education. Although the NMLE Content Guidelines have been revised approximately every five years over the last two decades, there is an absence of objective literature analyzing how the actual exam itself has evolved. Objective: To provide a holistic view of the trends of the actual exam over time, this study used a combined rule-based and data-driven approach. We primarily focused on classifying the questions according to the perspectives outlined in the NMLE Content Guidelines, while complementing this approach with a natural language processing technique called topic modeling to identify latent topics. Methods: Publicly available NMLE data from 2001 to 2024 were collected. Six exam iterations (2,880 questions) were manually classified from three perspectives (Level, Content, and Taxonomy) based on pre-established rules derived from the guidelines. Temporal trends within each classification were evaluated using the Cochran-Armitage test. Additionally, topic modeling was conducted for all 24 exam iterations (11,540 questions) using the BERTopic framework. The temporal trends of each topic were traced using linear regression models of topic frequencies to identify topics growing in prominence. Results: In Level classification, the proportion of questions addressing common or emergent diseases increased from 60% to 76% (p < 0.001). In Content classification, the proportion of questions assessing knowledge of pathophysiology decreased from 52% to 33% (p < 0.001), whereas the proportion assessing practical knowledge of primary emergency care increased from 20% to 29% (p < 0.001). In Taxonomy classification, the proportion of questions that could be answered solely through simple recall of knowledge decreased from 51% to 30% (p < 0.001), while the proportion assessing advanced analytical skills, such as interpreting and evaluating the meaning of each answer choice according to the given context, increased from 4% to 19% (p < 0.001). Topic modeling identified 25 distinct topics, and 10 topics exhibited an increasing trend. Non-organ-specific topics with notable increases included “Comprehensive Clinical Questions,” “Accountability in Medical Practice and Patients’ Rights,” “Care, Daily Living Support, and Community Healthcare,” and “Infection Control and Safety Management in Basic Clinical Procedures.” Conclusions: This study identified significant shifts in the Japanese NMLE over the past two decades, suggesting that Japanese undergraduate medical education is evolving to place greater importance on practical problem-solving abilities than on rote memorization. This study also identified latent topics that showed an increase, possibly reflecting underlying social conditions. Clinical Trial: NA
Abstract
Background
Cholestatic liver disease (CLD) is associated with various hereditary and acquired liver diseases. However, its outcomes are often poor and lack proper treatment. Danning tablets...
Abstract
Background
Cholestatic liver disease (CLD) is associated with various hereditary and acquired liver diseases. However, its outcomes are often poor and lack proper treatment. Danning tablets (DNT) have been widely used to treat CLD and have achieved favorable outcomes in clinical practice. However, there is currently a lack of clinical trials verifying the efficacy of DNT. Therefore, we investigated whether DNT combined with ursodeoxycholic acid capsules (UDCA) is more effective than UDCA alone in treating CLD of the damp heat stagnation type.
Methods
This was an open-label, multicenter, randomized controlled trial (RCT). A total of 186 patients diagnosed with damp heat stagnation type CLD were enrolled. They were stratified according to the severity of CLD and randomly assigned in a 1:1 ratio to receive either UDCA treatment alone or combined with DNT for 3 months. The primary endpoints of the study were improvement in clinical symptoms and liver function after treatment. The secondary endpoints included liver stiffness, survival status during hospitalization and follow-up, and adverse events.
Conclusion
This RCT will provide high-quality evidence to demonstrate the potential benefit of DNT combined with UDCA in patients with CLD of the damp heat stagnation type.
Background: Chronic obstructive pulmonary disease (COPD) is a globally prevalent respiratory disorder characterized by progressive airflow limitation, leading to substantial disability and being among...
Background: Chronic obstructive pulmonary disease (COPD) is a globally prevalent respiratory disorder characterized by progressive airflow limitation, leading to substantial disability and being among the leading causes of chronic morbidity and mortality worldwide. However, there remains a notable lack of convenient and effective home-based intervention programs to support COPD self-management. Objective: This study aimed to develop and evaluate the usability of "COPD CarePro," a WeChat-based mini-program designed to improve home-based self-management for COPD patients. Methods: Utilizing a mixed-methods design, we first conducted semi-structured interviews on 15 COPD patients and their caregivers following the consolidated criteria for reporting qualitative research (COREQ) guidelines to identify user needs. A multidisciplinary team then co-developed a five-module intervention featuring: 1) secure authentication, 2) symptom monitoring, 3) health diary, 4) multimedia education library, and 5) clinician communication portal. A two-stage usability assessment was implemented: (i) PSSUQ testing (n=10) uncovered navigational and functional pain points for prototype optimization, followed by (ii) SUS administration (n=52) to quantify usability of the production-ready version. Results: The final prototype demonstrated good usability with mean SUS score of 76.15±6.58, meeting the acceptability threshold (>70). Key functional outcomes included successful implementation of real-time symptom monitoring using CAT/mMRC thresholds for exacerbation alerts, and high engagement with video-based pulmonary rehabilitation guidance. Conclusions: COPD CarePro represents a clinically relevant health solution that successfully bridges critical gaps in COPD homecare through technology-enabled self-management support. The development process highlights the value of participatory design in creating patient-centered digital health interventions. Clinical Trial: NO
Background: Exergaming refers to video gaming with/without virtual reality that requires the use of physical activity during gameplay, and has been utilized as an emerging type of physical activity in...
Background: Exergaming refers to video gaming with/without virtual reality that requires the use of physical activity during gameplay, and has been utilized as an emerging type of physical activity in improving older adults’ physical and mental health. Exergaming can also be considered as esports when a competitive and interactive element is embedded in the gameplay. To date, the impact of exergaming-based esports on older adults’ health and well-being has been less investigated. Objective: This study aims to examine the effectiveness of an exergaming-based esports intervention program in promoting older adults’ physical, psychological, and cognitive health outcomes in Hong Kong. Methods: A total of 54 older adults were recruited and 48 (male = 12; female = 36) were retained for data analysis (six did not attend the post-test). All participants were allocated to either an esports group (EG = 24) or a control group (CG = 24). EG participants were invited to participate in an eight-week exergaming-based esports intervention program consisting of 16 training sessions to learn and play the Nintendo Switch™ Fitness Boxing game. A fitness boxing competition was embedded in the final three sessions. CG participants, in contrast, were instructed to maintain their normal daily activities. Outcome measures including the Senior Fitness Test, the University of California, Los Angeles (UCLA) Loneliness Scale (ULS-8), the Chinese version of the Physical Activity Enjoyment Scale (PACES), the Number Comparison Test (NCT), the Trail Making Test (TMT), and the Short Form-36 (SF-36) Health Survey were used to assess physical, psychological, and cognitive conditions. A repeated-measures ANCOVA was conducted, controlling for baseline values and demographic covariates. Results: The results showed that after the 8-week intervention, EG participants had better lower body strength, higher aerobic endurance, higher enjoyment level, and higher cognitive functioning than those in the CG. Conclusions: This study provides a theoretical contribution by filling the research gap regarding the beneficial effects of exergaming-based esports in enhancing older adults’ health in Hong Kong. Game designers are encouraged to design game types with competitive and interactive elements for older adults to play, thereby promoting their emotional and cognitive well-being. Clinical Trial: The trial design was registered on the Chinese Clinical Trial Registry (ChiCTR) on 13 November 2024 (TRN: ChiCTR2400092284). This study was retrospectively registered, as registration took place after the first participant was enrolled.
Background: The rise of AI and accessible audio equipment has led to a proliferation of recorded conversation transcripts datasets across various fields. However, automatic mass recording and transcri...
Background: The rise of AI and accessible audio equipment has led to a proliferation of recorded conversation transcripts datasets across various fields. However, automatic mass recording and transcription often produce noisy, unstructured data. First, these datasets naturally include unintended recordings, such as hallway conversations, background noise and media (e.g., TV programs, radio, phone calls). Second, automatic speech recognition (ASR) and speaker diarization errors can result in misidentified words, speaker misattributions, and other transcription inaccuracies. As a result, large conversational transcript datasets require careful preprocessing and filtering to ensure their research utility. This challenge is particularly relevant in behavioral health contexts (e.g., therapy, treatment, counselling): while these transcripts offer valuable insights into patient-provider interactions, therapeutic techniques, and client progress, they must accurately represent the conversations to support meaningful research. Objective: We present a framework for preprocessing and filtering large datasets of conversational transcripts and apply it to a dataset of behavioral health transcripts from community mental health clinics across the United States. Within this framework we explore tools to efficiently filter non-sessions – transcripts of recordings in these clinics that do not reflect a behavioral treatment session but instead capture unrelated conversations or background noise. Methods: Our framework integrates basic feature extraction, human annotation, and advanced applications of large language models (LLMs). We begin by mapping transcription errors and assessing the distribution of sessions and non-sessions. Next, we identify key features to analyze how outliers help in characterizing the type of transcript. Notably, we use LLM perplexity as a measure of comprehensibility to assess transcript noise levels. Finally, we use zero-shot LLM prompting to classify transcripts as sessions or non-sessions, validating LLM decisions against expert annotations. Throughout, we prioritize data security by selecting tools that preserve anonymity and minimize the risk of data breaches. Results: Our findings demonstrated that basic statistical outliers, such as speaking rate, are associated with transcription errors and are observed more frequently in non-sessions versus sessions. Specifically, LLM perplexity can flag fragmented and non-verbal segments and is generally lower in sessions (permutation test mean difference = -258, p<0.05), thus can serve as a filtering aiding tool. Additionally, LLM algorithms have shown an ability to distinguish between sessions and non-sessions with high validity (κ=0.71), while also capturing the nature of the meeting. Conclusions: This study’s hybrid approach effectively characterizes errors, evaluates content, and distinguishes different text types within unstructured conversational datasets. It provides a foundation for research on conversational data, providing key methods and practical guidelines that serve as crucial first steps in ensuring data quality and usability, particularly in the context of mental health sessions. We highlight the importance of integrating clinical experts with AI tools while prioritizing data security throughout the process.
Background: Artificial intelligence is increasingly integrated into clinical practice to enhance decision-making, diagnosis, and patient care. However, the diversity and complexity of AI-based clinica...
Background: Artificial intelligence is increasingly integrated into clinical practice to enhance decision-making, diagnosis, and patient care. However, the diversity and complexity of AI-based clinical decision support systems demand rigorous methodological and ethical evaluation to ensure their safety, effectiveness, and equity in real-world healthcare settings. Objective: To identify, characterize, and critically analyze existing evaluation systems and methodological frameworks used to assess AI models in clinical practice, with a focus on technical performance, clinical applicability, and bioethical considerations. Methods: We conducted a systematic review following PRISMA guidelines. We searched PubMed/MEDLINE, Embase, Scopus, and Web of Science from January 2013 to April 2024. We included studies describing evaluation frameworks or systems designed to assess AI-based clinical decision support systems in real-world clinical contexts. Data extraction included methodological characteristics, validation approaches, performance metrics, and ethical dimensions. The included frameworks were mapped and analyzed across five domains: validation strategy, reporting standards, clinical applicability, healthcare system integration, and ethical criteria. Results: A total of 24 articles were included. Most frameworks emphasized technical validation and performance metrics (e.g., accuracy, AUC), with fewer addressing prospective or external validation. Only a minority incorporated real-world implementation strategies or ethical dimensions such as transparency, equity, or patient autonomy. Regulatory guidance (e.g., from FDA or EU AI Act) was inconsistently referenced. Common gaps included lack of standardized outcome measures and insufficient stakeholder engagement, particularly from patients and healthcare providers. Conclusions: Current evaluation systems for AI models in clinical practice are heterogeneous and often incomplete, with limited emphasis on ethical and health systems integration. There is a critical need for standardized, multidimensional frameworks that encompass technical rigor, clinical relevance, and ethical accountability. A comprehensive and integrative approach is essential to ensure the safe, effective, and equitable deployment of AI in healthcare. Clinical Trial: PROSPERO ID 1019640
Background: Catheter-associated urinary tract infections (CAUTIs) are among the most common healthcare-associated infections, significantly affecting patient outcomes and healthcare costs. Nurses play...
Background: Catheter-associated urinary tract infections (CAUTIs) are among the most common healthcare-associated infections, significantly affecting patient outcomes and healthcare costs. Nurses play a pivotal role in CAUTI prevention due to their direct involvement in catheter care. However, evidence suggests notable gaps in knowledge and practice regarding CAUTI among nurses. Objective: To assess the impact of an educational intervention on nurses’ knowledge and attitudes toward the prevention of catheter-associated urinary tract infections. Methods: A quasi-experimental pre-post design was employed in a governmental tertiary hospital over four months. A total of 90 registered nurses from medical, surgical, and intensive care units participated. The intervention comprised simulation and case study-based training sessions. Knowledge and attitude were measured using a structured questionnaire before and after the intervention. Statistical analyses included paired t-tests, correlation analysis, and ANOVA using SPSS v16. Results: The mean overall knowledge score significantly improved from 19.2±5 pre-intervention to 31.5±4.8 post-intervention (p<0.001). All knowledge domains showed significant gains except for the policy and guidelines domain (p=0.12). Satisfaction with learning (r=0.82) and self-confidence (r=0.75) showed strong positive correlations with knowledge gains. Years of experience (r=0.35, p=0.005) and educational level (p=0.008) were significantly associated with knowledge improvement, while age, gender, nationality, and unit of work were not. Conclusions: Educational interventions using simulation and case-based strategies significantly enhanced nurses’ knowledge and confidence in CAUTI prevention. Continuous professional education is essential to improve clinical practice and reduce infection rates in healthcare settings.
Background: Sialorrhea, or excessive salivation, can be a major problem during a number of dental operations. It can impair vision, increase chair time, and perhaps jeopardize the effectiveness of tre...
Background: Sialorrhea, or excessive salivation, can be a major problem during a number of dental operations. It can impair vision, increase chair time, and perhaps jeopardize the effectiveness of treatments. To treat this illness, pharmacological treatments such as atropine sulphate are frequently employed. However, there hasn't been much research done on natural substitutes like Acacia catechu for this function. Objective: To compare and evaluate the effectiveness of Atropine sulphate and Acacia catechu in reducing salivary secretion in patients undergoing restorative dental procedures. Methods: A randomized controlled trial will be conducted involving 160 participants undergoing restorative dental treatments. Participants will be randomly assigned to receive either Atropine Sulphate or Acacia Catechu. Salivary flow will be measured pre- and post-intervention. Statistical analysis will be performed using paired t-tests and ANOVA. This protocol outlines the methodology and planned analyses. Results: It is anticipated that both interventions will reduce salivary flow, with atropine sulphate demonstrating greater efficacy but more side effects, and Acacia catechu offering a better side-effect profile and higher patient acceptability. Conclusions: The trial will provide comparative evidence on the efficacy and safety of a pharmacological and a natural anticholinergic agent. If Acacia catechu proves effective, it may offer a viable, better-tolerated alternative for salivary control in clinical dental settings. Clinical Trial: This study has been submitted to the Clinical Trials Registry – India (CTRI) and is currently under review (Acknowledgment Number: REF/2025/04/104969). The trial will be updated with the final registration number once approved.
Background: Outdoor play has always been a fundamental part of childhood. Children’s participation in outdoor play connects them to nature, the land and supports their role in the natural world. Ear...
Background: Outdoor play has always been a fundamental part of childhood. Children’s participation in outdoor play connects them to nature, the land and supports their role in the natural world. Early learning and child care (ELCC) centres provide important opportunities for outdoor play, however, barriers towards the provision of outdoor play opportunities exist, including educator attitudes, existing policies and procedures, outdoor space limitations and adverse weather conditions. Objective: The PROmoting Early Childhood Outside (PRO-ECO) 2.0 study is a community-based research partnership with Indigenous Knowledge Keepers and Elders, Indigenous and early childhood organizations, early childhood education faculty, ELCC centres and families, aiming to expand outdoor play in ELCC centres. This paper provides a detailed overview of the community-based design process, guided by the 5 R’s – Respect, Relevance, Responsibility, Reciprocity and Relationship – and the resulting study protocol for the mixed methods wait-list control cluster randomized trial. Methods: The PRO-ECO program and study protocol are implemented in partnership with 10 ELCC centres delivering licensed full-day, year-round care to children aged 2.5-6 years in rural and urban areas of British Columbia, Canada. The PRO-ECO program includes four components to address the common barriers to outdoor play in ELCC settings. Primary outcome measures include the proportion and diversity of observed nature play behaviour during dedicated outdoor times at ELCC centres as measured through observational behaviour mapping. Secondary outcomes include changes in educator attitudes, quality of ELCC outdoor play space, and children’s perspectives of their experiences at ELCC centres. Outcome data are collected at baseline, and 6-months and 12-months post-baseline. The community’s perspectives (educators, children, families) of the project are assessed qualitatively to understand the acceptability and effect of the PRO-ECO program. Mixed-effect models will test the effect of the PRO-ECO program on quantitative outcomes. Qualitative data will support interpretation of quantitative findings and provide evidence on project acceptability. Results: Participant recruitment for this study began in August 2023 and data collection was completed at participating ELCC centres in March 2025. A total of 227 children, 90 early childhood educators and 40 family members were recruited to participate in this study. Conclusions: The PRO-ECO 2.0 study ruses a rigorous and robust experimental design within a community-based research project. The 5 R’s approach grounded our work in shared values, disrupting traditional academic power relations and weaving together Indigenous and Western worldviews in the context of academic research. Clinical Trial: NCT05626595
Background: Most older Americans have not saved enough to cover long-term care costs. Medicaid–a public healthcare program for low income individuals–can help Americans with qualifying care needs...
Background: Most older Americans have not saved enough to cover long-term care costs. Medicaid–a public healthcare program for low income individuals–can help Americans with qualifying care needs pay for assistance in a nursing home or for services in the home and community. Determining financial eligibility for Medicaid is complicated and the application process is often managed by family caregivers with limited knowledge of Medicaid programs. Objective: A one-stop solution is needed to help family caregivers plan for the cost of long-term care services and learn about getting help paying for services through Medicaid. We developed a web application that (1) educates informal caregivers about Medicaid programs and eligibility criteria, (2) informs them about the cost of home and institutional care in their local area with and without Medicaid coverage, and (3) uses a custom algorithm to provide personalized financial eligibility information based on the care recipient’s income, assets, and monthly spending. Methods: We first interviewed aging services providers and informal family caregivers, then developed a web application that was refined based on user experience interviews with English and Spanish-speaking caregivers. In the final validation phase, asynchronous usability sessions were recorded with 109 informal caregivers. Participants completed a series of tasks where they viewed animated Medicaid “explainer” videos, input financial information enabling the application to determine the care recipient’s eligibility for Medicaid, used a care cost calculator to estimate the regional cost of home and institutional care services, and completed a Medicaid knowledge quiz before and after using the website. Results: After engaging with the website and watching the videos, scores on a Medicaid knowledge quiz increased by 61.2% (t=12.9, p<.001). Participants found it easy to enter the care recipient’s financial information to determine Medicaid eligibility (mean=5.9 (out of 7), SD= 1.34), and perceived the care cost calculator as very helpful (mean=6.3 (out of 7), SD=1.19). The website received a very high System Usability Scale rating of 88.3 out of 100 (SD= 13.05). Caregivers verbalized wanting more education on complex financial concepts that impact Medicaid eligibility and asset preservation. Conclusions: A comprehensive Medicaid planning website can significantly improve caregivers’ knowledge of Medicaid and provide them with a personalized roadmap for accessing care services. The custom algorithm powering the Medicaid eligibility determination could be further refined to account for state-based exceptions. This application may reduce caregiver burden and help support the long-term care planning process.
Despite growing evidence that expertise in narrative competence may benefit cancer care professionals and the field, few hematology-oncology trainees pursue graduate degrees in the humanities during f...
Despite growing evidence that expertise in narrative competence may benefit cancer care professionals and the field, few hematology-oncology trainees pursue graduate degrees in the humanities during fellowship. For those trainees with a particular interest in humanism in medicine, we advocate for integration of a Master of Fine Arts (MFA) degree concurrent with fellowship training. This pathway enables trainees to gain advanced skills in narrative competence, informing research and scholarly activities during fellowship and building a foundation for future careers that promote humanism in the field of hematology-oncology across clinical practice, education, research, and advocacy.
Narrative competence refers to one’s ability to create space for and elevate the voices of patients, families, and clinicians through active listening, reflecting, sharing, finding meaning in, and being moved by stories. In this article, we review evidence suggesting that frequent exposure to suffering increases burnout and threatens career longevity for cancer care clinicians, and narrative competence offers a humanistic approach to mitigate moral distress, improve wellbeing, and bolster resilience for our workforce. The influence of narrative competence extends beyond patient care, with meaningful ramifications for advancing research, education, and advocacy efforts across the field. In this article, we encourage institutions with hematology-oncology fellowship programs that have capacity to support graduate studies to include the MFA as an option for trainees who aim to become thought leaders and experts in narrative competence. The MFA serves as a strategic mechanism to invest in growing the next generation of hematologists-oncologists with expertise in narrative competence to advance the field.
Background: People with mobility disabilities face significant barriers to engaging in regular physical activity, contributing to elevated risks of chronic disease and reduced quality of life. Mobile...
Background: People with mobility disabilities face significant barriers to engaging in regular physical activity, contributing to elevated risks of chronic disease and reduced quality of life. Mobile health (mHealth) interventions offer a promising solution by delivering accessible, home-based exercise programs tailored to individual functional needs. Objective: The primary objective was to evaluate a mobile health intervention aimed at increasing physical activity among individuals with mobility disabilities. Additionally, the study team assessed adherence rates and implementation processes involved in delivering the intervention to this population." Methods: In this type 2 hybrid randomized controlled trial, 459 adults with mobility disabilities were assigned to one of three groups: M2M (exercise videos), M2Mplus (exercise videos plus social networking and optional coaching), or an attention control group (health articles). The 24-week home-based intervention was delivered via a tablet-based mobile app, with follow-up through 48 weeks. The primary outcome was self-reported physical activity using the Godin Leisure Time Exercise Questionnaire, assessed at baseline, 12, 24, and 48 weeks; secondary outcomes included video engagement, coaching attendance, and Fitbit step counts. Results: There were statistically significant mean differences in the primary outcome of self-reported MVPA (p < 0.006) among the intervention groups compared to the control group. MVPA increased immediately after the 6-month intervention but was not sustained over the 48-week follow-up. Conclusions: mHealth technology shows potential for delivering physical activity interventions to people with mobility disabilities. Participants enjoyed the exercise videos and health articles, reporting perceived benefits from the program. This study represents the largest physical activity trial to date targeting individuals with mobility disabilities. SUPER-HEALTH offers a comprehensive mHealth physical activity program that can be scaled nationally. Clinical Trial: NCT03024320
Background: Selecting suitable healthcare professionals remains a challenge for patients due to information asymmetry and limited guidance provided by online consultation platforms. Existing doctor re...
Background: Selecting suitable healthcare professionals remains a challenge for patients due to information asymmetry and limited guidance provided by online consultation platforms. Existing doctor recommendation systems often overlook the importance of "patient expectations" in assessing medical service quality, leading to suboptimal matching. Objective: To address this gap, we propose a personalized doctor recommendation system that integrates patient preferences and doctor profiles using the SERVQUAL framework. Methods: This system builds comprehensive bilateral profiles through feature extraction and sentiment analysis of user data from an online health community. Key dimensions, including tangibility, reliability, responsiveness, empathy, and assurance, are operationalized alongside additional factors like price and disease specialization.
A matching algorithm is developed to align patient expectations with doctor service attributes systematically. Results: Evaluation through scenario-based simulations demonstrated high match accuracy and high participant satisfaction. Conclusions: This approach enhances recommendation accuracy, reduces decision-making complexity, and improves user experiences on online healthcare platforms, optimizing resource allocation and patient outcomes.
Background: The World Health Organization (WHO) reported in 2020 that approximately 50% of all mental health disorders in adolescents manifest before the age of 14. However, the literature on mental w...
Background: The World Health Organization (WHO) reported in 2020 that approximately 50% of all mental health disorders in adolescents manifest before the age of 14. However, the literature on mental well-being and programmes designed and implemented by nurses for adolescents in low- middle-income countries (LMICs) is limited. This scoping review explores the development and implementation of psychosocial support programmes targeting high school learners in LMICs. Objective: This prospective scoping review will explore how psychosocial support programmes have been developed and implemented for high school learners from LMICS. Methods: Using the Joanna Briggs Institute (JBI) scoping review framework, primary research articles will be identified through systematic searches of ERIC, MEDLINE, Science Direct, PubMed, and PsycINFO. Grey literature will also be sourced from Google Scholar. Two independent reviewers will apply pre-determined inclusion criteria to select studies. Data will be charted, analyzed narratively, and presented in tables and figures Results: Data collection started in January 2024. Results yet to be published. Conclusions: This scoping review will synthesize evidence on psychosocial support programmes in LMICS and guide the development of targeted interventions to address the mental health needs of high school learners. Clinical Trial: Additional supplemental material is available from the Open Science repository.
The current paradigm of clinical drug development, which predominantly relies on traditional randomized controlled trials (RCTs), is increasingly challenged by inefficiencies, escalating costs, and li...
The current paradigm of clinical drug development, which predominantly relies on traditional randomized controlled trials (RCTs), is increasingly challenged by inefficiencies, escalating costs, and limited generalizability. Concurrent advancements in biomedical research, big data analytics, and artificial intelligence have allowed for the integration of real-world data (RWD) with causal machine learning (CML) techniques to address these limitations. This manuscript reviews the emerging role of RWD/CML in enhancing clinical research and drug development programs. By leveraging diverse data sources — including electronic health records, wearable devices, and patient registries — CML methods facilitate robust drug effect estimation, enable precise identification of responders, and support adaptive trial designs. Approaches such as advanced propensity score modelling, outcome regression, and Bayesian inference can help mitigate confounding biases inherent in observational data, thereby strengthening the validity of causal inference. However, these innovative methodologies also face significant challenges related to data quality, computational scalability, and the absence of standardized validation protocols. Furthermore, ethical and regulatory concerns regarding model transparency, data privacy, and possible algorithmic biases stress the importance of multidisciplinary collaboration and rigorous oversight. Our analysis underscores that while RWD/CML integration can enhance clinical development programs by generating more comprehensive evidence and accelerating drug innovation, its successful adoption depends on overcoming technical, operational, and scientific hurdles while maintaining a transparent approach with regulatory agencies.
Background: The positive effects of multidisciplinary rehabilitation programmes tend to fade over time due to low long-term patient adherence. Objective: We aimed to evaluate the impact of a smartphon...
Background: The positive effects of multidisciplinary rehabilitation programmes tend to fade over time due to low long-term patient adherence. Objective: We aimed to evaluate the impact of a smartphone application on adherence to an exercise programme for people with chronic low back pain (CLBP) at 6 months. Methods: One hundred and ten people with CLBP were included and randomised into two groups: 54 in the intervention group (IG) received education on the use of the application in addition to usual care (a 3-week multidisciplinary rehabilitation programme with self-management education) and 56 in the control group (CG) who received only usual care. The Exercise Adherence Rating Scale (EARS) was the primary outcome. Secondary outcomes were pain (Numeric Rating Scale), disability (Oswestry Disability Index), barriers and facilitators to performing physical activity (Evaluation of Physical Activity Perception), physical capacity (battery of tests) and qualitative adherence (correctness of exercise execution). Statistical analyses were performed according to the intention-to-treat principle. A linear mixed model compared the primary endpoint between groups at 6 months. Results: 71/110 participants were evaluated at 6 months. Adherence did not differ between groups, nor did pain, disability or barriers and facilitators to physical activity, except for the motivation criterion. Physical capacity test results (6MWT, cycle ergometer, Shirado-Ito, plank) and qualitative adherence differed between groups in favour of the IG. All outcomes improved from baseline to 6 months in the IG but not in the CG. Conclusions: The smartphone application did not impact adherence to an exercise programme at 6 months in individuals with CLBP. Similar results were found for pain and function. Nevertheless, the application could be a useful self-management tool in view of the positive effects on pain, function, physical capacity and qualitative adherence. Clinical Trial: ClinicalTrials.gov: NCT04264949
https://clinicaltrials.gov/study/NCT04264949
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: Mental health disorders, particularly anxiety, constitute a significant burden in Australia, affecting 1 in 5 individuals annually. While telehealth has emerged as a strategic solution to...
Background: Mental health disorders, particularly anxiety, constitute a significant burden in Australia, affecting 1 in 5 individuals annually. While telehealth has emerged as a strategic solution to expand access, evidence on its economic impact within the Australian context remains limited. Objective: This study evaluates the cost-effectiveness and budget impact of telehealth-delivered psychological services by clinical psychologists compared to in-person care and no treatment among adults with mental health disorders in Australia. Methods: A retrospective analysis was conducted using Medicare Benefits Schedule data from April 2020 to June 2022. A Markov cohort model simulated health transitions over a five-year horizon, incorporating healthcare payer and societal perspectives. Health outcomes were measured in quality-adjusted life years (QALYs). Results: Telehealth services were cost-effective, yielding an ICER of AUD $5,395/QALY compared to no treatment and dominating in-person services from a societal perspective due to reduced indirect costs. The estimated national budget impact was AUD $1.40 per member per month. Sensitivity analyses confirmed the model’s robustness. Conclusions: Telehealth for mental health is both cost-effective and cost-saving in Australia. These findings support the continued funding and integration of telehealth into national mental health policy to improve access and equity.
Background: With technological advancement, the internet has become the most convenient and vital source of information for many young people, most especially with the influx of mobile health (mHealth...
Background: With technological advancement, the internet has become the most convenient and vital source of information for many young people, most especially with the influx of mobile health (mHealth) platforms, which prevent many hurdles associated with young people’s access to SRH information and services. Hence, there is a gradual drift from in-person and constant visits to health facilities to a more convenient and easy way with just a tap. Again, unpleasant experiences such as attitudes of healthcare providers, proximity of health facilities, and cost implications further deter youth access to SRH in Ghana. In the bid to surf towards the new wave, novel approaches such as digital platforms, among which included the ‘You Must Know App’ by the Ghana Health Service (GHS), the Flow App, and many other digital tools, were introduced to help address this menace and facilitate access to quality and inclusive SRH among the Ghanaian youth. Objective: The study assesses the viability of digital tools as a means for sexual reproductive health (SRH) access among young people in the Greater Accra Region. Methods: A cross-sectional descriptive design was employed in the study. Following informed consent, a structured questionnaire was administered through an online platform to obtain information on socio-demographic and background characteristics, knowledge of available digital health platforms, sources of sexual reproductive health and any health-related information, and services, including participants' level of knowledge of mHealth and challenges to access. Results: The study found that 53.5% of participants had never used any digital health. Specifically, 66.8% indicated zero knowledge and awareness of the ‘You Must Know App’, and had they used any mobile applications to access healthcare before. On the other hand, 43.1% stated that they have ever used mobile health applications in their life, while 3.5% of the respondents did not know if they have ever used the applications or not. The results further suggested that despite technological advances in Ghana and parts of Africa, there remains a significantly low level of knowledge of mHealth tools and thus, the need for sensitization about mHealth Platforms, as a majority of the Ghanaian youth may not be aware of these applications at all. Conclusions: This study brought to light the emerging approaches to accessing sexual reproductive health information and services by the youth in Ghana, particularly with the onset of technology. However, it also revealed the emerging gaps or challenges faced by young people when using the available mobile health (mHealth) platforms as a source of SRH information in Ghana, particularly the You Must Know App, and suggested key innovations that can be implemented to enhance young people’s experiences with mhealth tools in Ghana.
Background: Diabetic foot ulcer (DFU) is a severe complication of diabetes mellitus, often resulting in amputation and increased mortality. Conventional treatments may be insufficient, leading to inte...
Background: Diabetic foot ulcer (DFU) is a severe complication of diabetes mellitus, often resulting in amputation and increased mortality. Conventional treatments may be insufficient, leading to interest in complementary therapies such as herbal medicine, acupuncture, maggot debridement therapy (MDT), and biological therapies. These approaches are widely used in Asia, yet their effectiveness and integration into clinical practice remain underexplored Objective: This scoping review aims to identify and evaluate the effectiveness, challenges, and opportunities of complementary therapies used for DFU wound healing in Asia. Methods: A scoping review was conducted using the PRISMA-ScR framework and Arksey & O'Malley's methodology. Articles were sourced from PubMed, Scopus, and ProQuest databases, covering studies published from 2014 to 2024. The PCC (Population, Concept, Context) model guided the selection of studies focusing on DFU patients, complementary therapies, and the Asian region. Ten studies met the inclusion criteria. Results: The most commonly applied therapies included herbal treatments (e.g., traditional Chinese medicinal foot soaks and Teucrium polium), biological therapies (MDT and Platelet-Rich Fibrin (PRF) with Hyaluronic Acid (HA)), physical therapies (acupuncture), and psychological therapies (music therapy). Key findings include: Maggot debridement therapy significantly increased miR-126 expression, enhancing angiogenesis and tissue regeneration (P < 0.05), Topical Teucrium polium application reduced wound size more effectively than placebo (P < 0.0001), PRF combined with HA reduced inflammation and increased VEGF levels by day 7 (P < 0.001), Music therapy reduced diabetes-related distress, significantly lowering distress scores (P < 0.001). However, challenges remain, including a lack of large-scale randomized controlled trials (RCTs), regulatory barriers, and cultural perceptions affecting therapy acceptance. Further research is necessary to validate these findings and develop standardized guidelines. Conclusions: Complementary therapies offer promising adjuncts for DFU management in Asia, where traditional medical practices are prevalent. Multidisciplinary collaboration among healthcare providers, policymakers, and traditional practitioners is essential for safe and effective integration. Further well-designed RCTs are required to confirm efficacy and inform evidence-based policies.
Background: Fully decentralized self-administered mindfulness (SAM) interventions show promise for stress reduction, but rigorous evaluations of their feasibility, acceptability, and effectiveness usi...
Background: Fully decentralized self-administered mindfulness (SAM) interventions show promise for stress reduction, but rigorous evaluations of their feasibility, acceptability, and effectiveness using both self-report and physiological measures remain limited. In Singapore, where mental health concerns rank as the top healthcare priority (46%), ahead of cancer (38%) and stress-related issues (35%), accessible and scalable interventions are urgently needed to address the significant economic burden of mental health conditions. Objective: This pre-registered pilot study (NCT06765889) evaluated a decentralized, three-day self-administered mindfulness intervention versus sham control in Singaporean adults, examining effects on self-reported and physiologically measured stress responses. The inclusion of a sham control condition allows for disentangling mindfulness-specific effects from demand characteristics and expectation effects, addressing a critical methodological gap in digital mindfulness research. Methods: Sixty participants were randomized to either a mindfulness intervention or structurally matched sham control. Stress was assessed via self-report (STAI-6) and physiologically through Heart Rate Variability (HRV). The study incorporated three methodological innovations: (1) A structurally equivalent sham control to match expectancy and credibility, (2) remote collection of HRV as an objective physiological biomarker, and (3) full decentralization via smartphone allowing unsupervised multi-platform delivery. Feasibility was evaluated through recruitment/retention rates, cross-platform delivery, protocol adherence, and data quality. Acceptability was assessed through quantitative ratings and qualitative feedback. Results: The study demonstrated excellent feasibility with near perfect retention (98.3%) and moderate HRV data quality (69.8% valid signals). Acceptability ratings were strong (M = 4.17/5, SD = 0.53), with highest scores for comfort/engagement (M = 4.27/5, SD = 0.57), exceeding established usability benchmarks for digital health interventions. Qualitative feedback identified technical challenges (HRV instability, device overheating) and scheduling difficulties. While Bayesian analyses revealed no significant group differences in stress reduction (BF₁₀ = 0.03) or HRV improvement (BF₁₀ = 0.2), both groups showed significant stress reductions (BF₁ ₀= 3.01×10⁶), suggesting that observed benefits may stem from non-specific factors common to both interventions. Conclusions: This study demonstrates (1) the feasibility of conducting fully decentralized mindfulness trials with multimodal assessment, (2) the value of mixed-methods acceptability evaluation, and (3) identifies key technical and control condition refinements necessary for future trials. By addressing methodological limitations in digital mindfulness research through improved control conditions and objective physiological measures, this work provides a foundation for more rigorous investigation of mindfulness-specific versus non-specific effects in remotely delivered stress reduction interventions. Clinical Trial: ClinicalTrials.Gov(NCT06765889)
Background: Artificial intelligence (AI) tools have emerged as transformative technologies applied in healthcare, leading to more accurate and comprehensive information regarding diagnosis,treatment p...
Background: Artificial intelligence (AI) tools have emerged as transformative technologies applied in healthcare, leading to more accurate and comprehensive information regarding diagnosis,treatment protocols. It has extended the scope in supporting medical decision-making and the management of chronic diseases. This study aims to assess the accuracy and readability of responses provided by different AI-based tools to questions that patients and clinicians might raise regarding childhood asthma.
Artificial intelligence (AI) technologies are revolutionizing pediatric healthcare models, demonstrating unique value in childhood asthma management. AI-driven diagnostic models enhance early detection rates through the integration of multi-dimensional clinical data, while personalized algorithms dynamically optimize stepwise treatment protocols.Intelligent monitoring systems facilitate personalized management of chronic respiratory conditions. Current research focuses on evaluating the accuracy and readability of AI-generated responses to clinical inquiries, establishing technical assessment criteria aligned with practical medical needs. Our investigation holds practical significance for improving long-term care in pediatric asthma patients and alleviating the growing pressure on pediatric healthcare resources. Objective: Our study utilized the DISCERN scoring system and readability indices to evaluate the accuracy and comprehensibility of Large Language Models on pediatric asthma.We highlight the performance of Large Language Models (Claude3-Opus,Gemini 2.0, Chat GPT-4o and DeepSeek) on providing healthcare information regarding pediatric asthma based on the comparative Study. Methods: On February 11, 2025, fifteen hypothetical questions were posed to imitate physician-patient communications about asthma in Gemini 2.0, DeepSeek, ChatGPT-4o and Claude3-Opus respectively. The total scores for individual subjects were obtained and compared. Responses were evaluated by three independent pediatrics specialists using the DISCERN scoring system. The readability was evaluated using multiple indices: Flesch Reading Ease (FRE), Flesch-Kincaid Grade Level (FKGL), Gunning Fog Index (Gunning FOG), Simple Measure of Gobbledygook (SMOG), Coleman-Liau Index (CLI), and Automated Readability Index (ARI). Results: A total of 60 responses were collected from the four platforms. The models performed based on the DISERN scoring system was in the following order from best to worst: ChatGPT-4o (51.8±7.6), Gemini2.0 (51.6±8.9), DeepSeek (50.6±6.4) and Claude3-Opus (50.3±8.4). Yet, statistically significant differences were not observed between these platforms. A significant positive correlation was shown between the specialists’ scores, ensuring the stability of the results.
The readability analysis demonstrated that the contents were mostly above the level of high school, suggesting responses provided by AI tools may not be understandable to the average reader. Overall, ChatGPT-4o generated responses notably more comprehensible than other platforms. (FRE scores 34.3±8.5). DeepSeek performed worst on the readability. (FRE scores 21.8±9.9), which was significantly lower than other AI tools. Conclusions: Although ChatGPT-4o (OpenAI) and Gemini 2.0 (Google DeepMind) demonstrated potential in generating pediatric asthma-related healthcare information, their clinical utility remained constrained by limited linguistic accessibility of outputs, particularly for non-expert users. Meanwhile, as a newly released AI model, the precision of responses given by DeepSeek should be optimized. Crucially, AI healthcare tools should implement clinician-mediated supervision protocols for AI-generated medical support materials, coupled with real-time adaptive text simplification functionalities. Further research should focus on developing AI programs especially designed for pediatric clinicians and patients in the field of chronic atopic diseases.
Background: Emergency Department physicians are continuously exposed to traumatic events during their work and are at high risk of developing neurological disorders such as burnout and Acute Stress Di...
Background: Emergency Department physicians are continuously exposed to traumatic events during their work and are at high risk of developing neurological disorders such as burnout and Acute Stress Disorder (ASD). The clinical evaluation process for diagnosing these disorders is based on history and physical examination. Screening and questionnaires are the most common diagnostic tools that require significant training and often miss initial physiological symptoms. The addition of Artificial Intelligence (AI) data-driven decision support using passive EEG monitoring of biopotential brainwave activity may be the key to unlocking early signs of trauma-related neurological disorders for healthcare professionals exposed to high levels of work-related stress. Objective: The objective of this research is to test the design of a minimally invasive mobile electroencephalography (EEG) biomonitoring device with emergency physicians (EPs), analyze biopotential brainwave activity collected from EPs while experiencing stressful events, and develop an AI-driven decision support system prototype to analyze near-real-time neurological responses and monitor biomarkers associated with stressful events. Methods: Twenty-three emergency department physicians were monitored while on shift at the Greenville Memorial Hospital Emergency Department, a Level 1 Trauma Center. Participants continuously wore the study's EEG headset both before their shift, to establish a reference baseline signal, and throughout their shift when exposed to stressful events. Biopotential data were transferred to a secure university research server, and stress levels were determined using personalized statistical thresholds. Machine learning models were created to predict stressful events, and waveform analysis revealed key predictors. Results: Neurological response data show increased frequency domain waveform amplitudes as participants are exposed to traumatic events. Machine learning models (ANN, SVM, NB, LR, DT) were trained using 70% of the data and tested with 30%. ANN achieved the highest prediction accuracy at 92% (64,626/70,246). All models demonstrated an impressive ability – greater than 81% accuracy – to use neurological responses to predict stressful events. In each model, Gamma waveforms were over 80% important for stress prediction, highlighting the importance of high-frequency brainwaves in stress detection. Conclusions: Neurological response data show that stressful events can be parameterized by the instantaneous and progressive outputs of the monitored spectral waveforms as they relate to ER physicians exposed to traumatic environments. Comparing EEG waveforms from multiple participants highlights the need for personalized baselines in stress prediction. Analysis of machine learning model performance reveals that non-linear models, such as ANN and DT, are better suited for biopotential signal analysis due to their ability to account for complex relationships with the data. The investigation into the frequency domain of EEG spectra revealed that higher-frequency bands, such as Gamma and Beta, are important for predicting stress. In contrast, lower-frequency bands like Theta and Delta are less influential. Clinical Trial: N/A
Background: Colorectal cancer is the third most common type of cancer worldwide, and accurate segmentation of colorectal polyps plays a crucial role in early screening and treatment. Existing polyp se...
Background: Colorectal cancer is the third most common type of cancer worldwide, and accurate segmentation of colorectal polyps plays a crucial role in early screening and treatment. Existing polyp segmentation methods are predominantly based on Convolutional Neural Network (CNN) and Transformer. However, CNN suffer from limited receptive fields, leading to insufficient global context modeling, while Transformer, despite their attention mechanisms offering some insight into model focus, still face challenges in overall interpretability. Objective: To address these limitations, this paper proposes a novel multi-scale polyp segmentation network—MSSNet (Multi-Scale Segmentation Network). The proposed model integrates the local detail sensitivity of CNN with the global semantic perception capabilities of Transformer to tackle common challenges in polyp segmentation, such as scale heterogeneity, ambiguous boundaries, and the dominance of small-sized targets, while also enhancing model interpretability. Methods: MSSNet employs Pyramid Vision Transformer v2 (PVT v2) as the encoder to hierarchically extract multi-scale features. A newly designed Multi-Scale Attention Decoder (MSAD) is introduced to improve the recognition of blurry edges and small polyps through hierarchical feature fusion and an enhanced attention mechanism. The encoder and decoder are connected via a Multi-Scale Modulation (MSM) module, which effectively enhances cross-level feature interaction. In addition, a fusion loss function with adaptive weighting is proposed to emphasize critical regions and enhance the model's sensitivity to local details. To mitigate the “black-box” nature of deep learning models in medical image segmentation, we introduce a novel interpretability method—Grad-SAM (Gradient Segmentation Activation Map), which provides explicit visual attribution of segmentation results, thereby improving decision transparency. Results: Extensive experiments on four benchmark polyp datasets—EndoScene, Kvasir, Piccolo, and CVC-ClinicDB—demonstrate that MSSNet achieves Dice scores of 93.32%, 91.56%, 87.03%, and 84.11%, respectively, with a computational cost of 4.62 GFLOPs, outperforming existing state-of-the-art methods in both accuracy and efficienc. Conclusions: These results suggest that MSSNet holds great promise for real-world clinical decision support in colorectal polyp diagnosis.
Background: Intensive longitudinal designs support temporally granular study of processes making methods like ecological momentary assessment (EMA) increasingly common in medical and behavioral scienc...
Background: Intensive longitudinal designs support temporally granular study of processes making methods like ecological momentary assessment (EMA) increasingly common in medical and behavioral science. However, the repetitive and intensive measurement strategies associated with these designs increase participant burden which limits the breadth and precision of EMA surveys. This is particularly problematic for complex clinical phenomena, such as suicide risk, which research has shown is multidimensional and fluctuates over narrow time intervals (e.g., hours). To overcome this limitation, we proposed the Computerized Adaptive Test for Suicide Risk Pathways (CAT-SRP) which supports the simultaneous assessment of multiple empirically informed risk domains and facilitate personalized survey content. Objective: The objective of this study is to develop, calibrate, and pilot the first multidimensional computerized adaptive test for suicidal thoughts and related psychosocial risk factors in intensive longitudinal designs like EMA. Methods: A web-based assessment platform was developed to adaptively administer the CAT-SRP. CAT-SRP items were modified from existing validated instruments to support administration in intensive longitudinal designs. The item bank was developed in line with major ideation-to-action theories of suicide and consultation with experts outside the study team. Exploratory item factor analysis was used to identify dimensionality of the item bank. Item parameters were calibrated using a multidimensional graded response model in a large cross-sectional community sample (N = 1759, 36.33% with a history of suicidal thoughts). Following calibration, the CAT-SRP was evaluated in an EMA study of participants with a past month history of suicidal thoughts (N = 29 across 2,134 observations). Adaptive testing utilized D-optimal item selection, a dual variable-length stopping criterion, and MAP scoring. Descriptive statistics and mixed effects models were used to examine CAT-SRP performance (e.g., efficiency, survey overlap) and relationships among CAT-SRP domain scores. Results: The calibration study identified two suicidal thought domains (active and passive thoughts) and twelve risk factor domains: humiliation, loneliness, anger, pain, defeat, impulsivity/negative urgency, entrapment, distress tolerance, perceived burdensomeness, thwarted belongingness, aggression, and a hope/method factor. Domain information was highest between average to high levels of domain scores. Study 2 results suggested that the CAT-SRP 1) administered surveys with low to moderate item overlap, 2) incurred low participant burden, and 3) may improve near-term prediction of suicidal thoughts relative to traditional EMA measurement. Most EMA surveys reached the maximum length, 50 questions, highlighting a need to refine selection and stopping rules. Conclusions: The CAT-SRP effectively personalized EMA survey content to respondents which reduces the repetitiveness and perceived burden of intensive longitudinal research designs. Continuous domain scores from MCAT also provided more nuanced measurement, compared to traditional approaches that struggle with zero-inflation in EMA, and appeared to produce stronger predictive relationships. Overall, the CAT-SRP demonstrates strong methodological advantages to utilizing CAT for intensive longitudinal data collection.
Background: According to the World Health Organization, the annual growth rate of lymphoma is 7.5%, making it one of the fastest-growing malignant tumors over the past decade [1]. In China, the incide...
Background: According to the World Health Organization, the annual growth rate of lymphoma is 7.5%, making it one of the fastest-growing malignant tumors over the past decade [1]. In China, the incidence of lymphoma has been steadily increasing, currently affecting approximately 6.68 per 100,000 people [2]. In 2020, there were 92,834 new cases and 54,351 deaths from non-Hodgkin’s lymphoma (NHL) in China [3]. Notably, the incidence of lymphoma among younger populations is also rising [4]. Globally, many regions are grappling with the challenges posed by lymphoma, a malignant tumor associated with poor prognosis. This study aims to provide new insights and approaches for the prevention and treatment of lymphoma by analyzing the factors influencing incidence, mortality, and survival rates in Xiamen City. Objective: The aim of this study was to analyze the factors influencing morbidity, mortality and survival outcomes in patients diagnosed with lymphoma. Methods: Data were collected from all newly diagnosed lymphoma cases in Xiamen City between 2011 and 2020. The data were evaluated to assess morbidity and mortality rates, with statistical analyses conducted using SAS 9.4 software. Results: The results of this study indicated that the incidence rate of lymphoma is higher in males than in females and higher in urban areas than in rural ones (ASIR 6.44 per 100 000 versus 4.34 per 100 000), the lymphoma mortality rate is higher in males than in females (ASMR 3.57 per 100 000 versus 2.10 per 100 000) and greater in urban areas compared to rural areas(ASIR 3.14 per 100 000 versus 2.10 per 100 000). Six variables (age, suburb, marital status, education, lymphoma type, and diagnosis year) significantly impacted prognosis, as shown by the multivariate Cox analysis. Conclusions: Developing lymphoma prevention and control programs for people of different genders, ages, living environments, and literacy levels can effectively reduce lymphoma morbidity and mortality and improve survival. Clinical Trial: Non-clinical studies, no registration required
Background: Skin cancer is the most commonly diagnosed malignancy in the United States, with rural populations facing disproportionate delays in diagnosis due to geographic isolation, workforce shorta...
Background: Skin cancer is the most commonly diagnosed malignancy in the United States, with rural populations facing disproportionate delays in diagnosis due to geographic isolation, workforce shortages, and limited access to dermatologic care. These delays contribute to higher rates of late-stage diagnosis and poorer outcomes. Teledermatology has emerged as a promising solution to expand access to dermatologic evaluation and treatment in underserved settings. Objective: To evaluate the diagnostic performance, implementation challenges, and equity considerations of teledermatology in the context of rural skin cancer care, and to assess its potential to improve clinical outcomes in underserved populations. Methods: A comprehensive literature search was conducted across PubMed, Scopus, Web of Science, and Google Scholar to identify studies published between January 2015 and March 2025. Search terms included “teledermatology,” “skin cancer,” “rural health services,” “telemedicine,” “diagnostic accuracy,” and “health disparities.” Studies evaluating diagnostic metrics, time to diagnosis, patient satisfaction, and implementation barriers were included. Results: Nine key studies spanning various countries and healthcare settings were included. Diagnostic sensitivity ranged from 41.9% to 100%, and specificity from 46% to 90%, depending on modality and lesion type. Teledermatology consistently reduced time to diagnosis, in some cases by over 75%, and was associated with high patient satisfaction due to increased convenience and reduced travel. Key barriers included technological limitations, inconsistent imaging protocols, and reimbursement variability. Successful implementation was facilitated by standardized workflows, dermoscopy integration, and centralized platforms. Conclusions: Teledermatology is a viable and effective approach to addressing disparities in rural skin cancer care. It offers diagnostic accuracy comparable to face-to-face evaluations while reducing wait times and improving patient satisfaction. Overcoming technological and systemic barriers is critical to ensuring equitable, long-term integration of teledermatology in rural health systems.
Background: Globally, the number of illegal drug users is rising, posing mental and physical health challenges and increasing societal burdens. Despite a significant need for treatment, only about 10%...
Background: Globally, the number of illegal drug users is rising, posing mental and physical health challenges and increasing societal burdens. Despite a significant need for treatment, only about 10% of these individuals receive it worldwide, often with poor adherence. Traditional treatments, while effective, suffer from high dropout rates due to limitations. The COVID-19 pandemic has spurred the growth of digital interventions like apps and online platforms, offering flexibility and cost-effectiveness that better meet patient needs and improve engagement. However, addressing the persistently high dropout rates in these online treatments is crucial and necessitates further research. Objective: This study aimed to estimate dropout rates among adults with illicit drug use participating in digital psychosocial intervention trials, and to identify factors associated with attrition. Methods: We conducted a systematic search of five major databases for English-language randomized trials published up to January 27, 2025. A total of 40 studies (80 arms; 9,563 participants) reporting 46 dropout rate estimates were included. A random-effects model was used to calculate pooled dropout rates, with meta-regression and subgroup analyses exploring potential moderators. The study was registered on PROSPERO (CRD42024534389). Results: At post-test, the pooled dropout rate in the intervention group across 17 studies was 22.4% (95% CI: 12.4%–37.2%). Dropout was significantly associated with education level, employment status, baseline clinical diagnosis, intervention frequency, and initial medication use. During the longest follow-up (29 studies), the dropout rate was 27.9% (95% CI: 18.8%–39.3%), with marital status, recruitment source, medication frequency, and intervention modality as significant predictors. Control group dropout rates were 25.9% and 28.3%, both higher than those in the intervention group. Conclusions: This meta-analysis revealed substantial dropout among adults with illicit drug use receiving digital psychosocial interventions. Targeted modifications to intervention design may improve engagement and long-term retention. Clinical Trial: The study was registered on PROSPERO (CRD42024534389).
Background: Few studies have analyzed preschoolers’ screen exposure patterns, especially combined screen time and content, and their neurodevelopmental impacts. Objective: This study aims to identif...
Background: Few studies have analyzed preschoolers’ screen exposure patterns, especially combined screen time and content, and their neurodevelopmental impacts. Objective: This study aims to identify the screen exposure patterns in preschoolers by intelligent technology, and to examine their associations with their neurodevelopment. Methods: This cross-sectional study enrolled preschool children from two kindergartens in Shanghai. Screen time and content types were monitored over 7 consecutive days using a validated intelligent monitoring technology. Neurodevelopmental outcomes were assessed using the Ages and Stages Questionnaire, Third Edition (ASQ-3). K-means clustering analysis identified screen exposure patterns, and binary logistic regression was applied to examine associations between screen exposure patterns and neurodevelopmental outcomes. Results: Of 355 preschool children included, 204 were boys (57.5%) and 251 (70.7%) were aged between 34.5 months and 50.5 months. K-means cluster analysis yielded 4 screen exposure patterns: restrictive use, moderately educational, noneducational, and educational-dominant pattern. Binary logistic regression showed the moderately educational pattern linked to gross motor abnormalities (OR = 2.530, 95% CI: 1.089 – 5.875, P = 0.031), and non - educational to fine motor abnormalities (OR = 3.172, 95% CI: 1.122 – 8.968, P = 0.029). Conclusions: This monitoring study identified heterogeneous screen exposure patterns in preschool-aged children, revealing that excessive use of moderately educational content and noneducational content was associated with lower gross motor and fine motor skills. When limiting total screen time, parents should focus on content selection for preschool-aged children. Future research should focus on the objective measurement of different types of screen content.
Background: Obsessive–compulsive disorder (OCD) affects 2-3% of the global population and is associated with significant morbidity, burden and psychosocial dysfunction. Exposure and Response Prevent...
Background: Obsessive–compulsive disorder (OCD) affects 2-3% of the global population and is associated with significant morbidity, burden and psychosocial dysfunction. Exposure and Response Prevention (ERP) is the gold-standard for dealing with compulsions; however, homework compliance has been a major obstacle in recovery. Artificial intelligence holds significant promise in enhancing the effectiveness of mental health interventions by enabling personalized, scalable, and data-driven approaches to assessment and treatment. Currently, there are few mobile based applications available for ERP, however, they lack a focus on bilingual support and are not customized for Indian populations. Objective: The study aims to develop and evaluate the acceptability, feasibility, and efficacy of a bilingual, therapist-enhanced app for ERP designed for patients with OCD. Methods: The study will be conducted in three phases. Phase 1 will involve desk review and Focus Group Discussion (FGD) among stakeholders (mental health professionals, patients and caregivers) to generate evidence for best principles for app development. App will be developed in phase 2 using “user participatory design” and Phase 3 will involve a pilot parallel-group, pilot randomized control trial for testing its acceptability, feasibility and efficacy. Results: The study received funding in March 2024 and ethics permission and trial registration in September 2024. Phase 1 is ongoing and will be completed by June 2025. Based on these, the team will create a ‘visual walk-through, non-interactive mockup’ mobile app, which will be refined using participatory design and version 1 prototype will be created by June 2025. Study enrolment for pilot RCT will start in July 2025 and the full results will be available by December 2026. Conclusions: The study will demonstrate the acceptability, feasibility and efficacy of a bilingual, therapist-enhanced ERP app in improving adherence and outcomes for OCD treatment in an Indian context. Findings will contribute to evidence supporting culturally and technologically adaptive interventions for mental health disorders. Clinical Trial: Clinical Trials Registry- India (CTRI) REF/2024/04/083167
Background: Diffusion models have shown great promise in generating high-fidelity images, particularly in computer vision. However, their application to diverse medical imaging modalities remains unde...
Background: Diffusion models have shown great promise in generating high-fidelity images, particularly in computer vision. However, their application to diverse medical imaging modalities remains underexplored. Each MRI modality presents unique structural and textural features, making it a challenging but important testbed for generative model evaluation. Objective: This study aims to evaluate the performance of diffusion models across a range of MRI modalities, including brain, chromatin, lung, kidney, spine, and heart. The goal is to understand the ability of diffusion models to capture and replicate modality-specific details critical for medical interpretation. Methods: We conducted a series of experiments using publicly available and synthetic MRI datasets representing six distinct modalities. For each modality, a dedicated diffusion model was trained independently to assess its capacity for high-quality image generation Results: Visual inspection confirmed that modality-specific anatomical features were well-preserved in generated outputs. Conclusions: Diffusion models can effectively learn and replicate the unique characteristics of various MRI modalities, though performance varies depending on data complexity and quality.
Background: Objective Structured Clinical Examinations (OSCEs) are widely used for assessing medical student competency, but their evaluation is resource-intensive, requiring trained evaluators to rev...
Background: Objective Structured Clinical Examinations (OSCEs) are widely used for assessing medical student competency, but their evaluation is resource-intensive, requiring trained evaluators to review 15-minute videos. The physical examination component typically constitutes only a small portion of these recordings, yet current automated approaches struggle with processing long medical videos due to computational constraints and difficulties maintaining temporal context. Objective: To determine whether multimodal large language models (MM-LLMs) can effectively segment physical examination periods within OSCE videos without prior training, potentially reducing the evaluation burden on both human graders and automated assessment systems. Methods: We analyzed 500 videos from five OSCE stations at UT Southwestern Simulation Center, each 15 minutes long, using hand-labeled physical examination periods as ground truth. MM-LLMs processed video frames at one frame per second, classifying them into discrete activity states. A hidden Markov model with Viterbi decoding ensured temporal consistency across segments, addressing the inherent challenges of frame-by-frame classification. Results: Using this combined approach of zero-shot visual classification with Viterbi decoding, GPT-4o achieved 99.8% recall and 78.3% intersection over union (IOU), effectively capturing physical examinations with an average duration of 175 seconds from 900-second videos—an 81% reduction in frames requiring review. Conclusions: Integrating zero-shot multimodal large language models with minimal-supervision temporal modeling effectively segments physical examination periods in OSCE videos without requiring extensive training data. This approach significantly reduces review time while maintaining clinical assessment integrity, demonstrating that AI methods combining zero-shot capabilities and light supervision can be optimized for medical education's specific requirements. The technique establishes a foundation for more efficient and scalable clinical skills assessment across diverse medical education settings.
Background: The widespread use of digital technologies—especially the internet and social media—has raised growing concerns about their impact on mental health. While self-regulation has been prop...
Background: The widespread use of digital technologies—especially the internet and social media—has raised growing concerns about their impact on mental health. While self-regulation has been proposed as a protective factor, little is known about how distinct psychological profiles based on self-regulatory and technology use patterns relate to well-being. Person-centered approaches such as Latent Profile Analysis (LPA) may offer deeper insights, particularly in underrepresented populations. Objective: This study aimed to identify latent psychological profiles based on self-regulation, nomophobia, and problematic use of the internet and social media and to examine their association with mental health outcomes in a Colombian sample. Additionally, the predictive roles of age and gender on class membership were explored.
Methods Methods: 453 participants aged 12 to 57 years (M = 21.03, SD = 8.41; 57% female) completed validated measures of self-regulation, nomophobia, internet use, social media use, and psychological health (GHQ-12). Latent Profile Analysis was conducted using standardized scores of continuous variables. Model fit was assessed using BIC, entropy, and BLRT. Differences in psychological health across latent classes were examined through ANOVA and regression models. A multinomial logistic regression tested the predictive value of age and gender on class membership. Results: The optimal solution revealed four distinct latent profiles (entropy = 0.85):
Class 1 (adaptive): high self-regulation, low nomophobia, and low ICT use; presented the best psychological health. Class 4 (vulnerable): low self-regulation, high nomophobia, and high ICT use; reported the poorest health outcomes. Classes 2 and 3 displayed intermediate profiles, with Class 3 showing slightly better health than Class 4.
Differences in psychological health across classes were statistically significant (ANOVA, p < .001). Age and gender were significant predictors of class membership: younger females were more likely to belong to Class 1, whereas older males were more likely to be classified into Classes 3 and 4. Conclusions: LPA enabled the identification of distinct psychological profiles that vary in mental health outcomes and digital vulnerability. Self-regulation emerged as a central protective factor, suggesting the importance of tailored digital interventions to enhance regulatory capacities. These findings reinforce the value of person-centered approaches and highlight the need for scalable strategies to mitigate the mental health risks associated with problematic ICT use in Spanish-speaking populations.
Background: Digital scribes using ambient listening and generative AI have the potential to streamline clinical documentation and enhance workflow efficiency. However, despite growing interest, real-w...
Background: Digital scribes using ambient listening and generative AI have the potential to streamline clinical documentation and enhance workflow efficiency. However, despite growing interest, real-world evidence on their effects on clinician efficiency, satisfaction, quality, and integration remains limited. Objective: To synthesize evidence on clinician efficiency, user satisfaction, quality, and practical barriers associated with the use of digital scribes employing ambient listening and generative artificial intelligence (AI) in real-world clinical settings. Methods: A rapid review was conducted to evaluate the real-world evidence of digital scribes using ambient listening and generative AI in clinical practice from 2014 to 2024. Data was collected from Ovid MEDLINE, Embase, Web of Science - Core Collection, Cochrane CENTRAL and Reviews, and PubMed Central. Predefined eligibility criteria focused on studies addressing clinical implementation, excluding those centered solely on technical development or model validation. The findings of each study were synthesized and analyzed through the QUEST human evaluation framework for quality and safety and the SEIPS 3.0 Model to assess integration into clinician’s workflows and experience. Results: Of the 1,450 studies identified, six met inclusion criteria. These studies included an observational study, a case report, a peer-matched cohort study, and survey-based assessments conducted across academic health systems, community settings, and outpatient practices. The major themes noted were: (1) They decreased self-reported documentation times, with associated increased length of notes, (2) Physician burnout measured using standardized scales was unaffected, but physician engagement improved, (3) Physician productivity, assessed via billing metrics, was unchanged, (4) the studies fell short when compared to standardized frameworks. Conclusions: Digital scribes show promise in reducing documentation burden and enhancing clinician satisfaction, thereby supporting workflow efficiency. However, the current available evidence is sparse. Future real-world, multifaceted studies are needed before AI scribes can be recommended unequivocally. Clinical Trial: N/A
Background: Meniscal injuries are prevalent knee pathologies. However, the public increasingly relies on online video platforms for health information, where content quality and reliability vary signi...
Background: Meniscal injuries are prevalent knee pathologies. However, the public increasingly relies on online video platforms for health information, where content quality and reliability vary significantly, posing risks of misinformation, particularly in China with its extensive platform usage. Objective: This study aimed to evaluate the quality (GQS), reliability (mDISCERN), understandability (PEMAT-U), and actionability (PEMAT-A) of meniscal injury video content on major Chinese platforms (Bilibili and Douyin/TikTok). It also sought to identify key predictive factors for these dimensions and, innovatively, to understand user perspectives, engagement patterns, and feedback through sentiment analysis and topic modeling of user comments. Methods: In this cross-sectional study, 200 top-ranked meniscal injury-related videos (100 from Bilibili, 100 from TikTok) were collected using a specific keyword and assessed by medical experts using GQS, mDISCERN, and PEMAT-A/U. Statistical analyses, performed with SPSS 27.0, included descriptive statistics, Mann-Whitney U tests, Spearman correlations, and stepwise regression. Approximately 22,000 user comments were analyzed using a fine-tuned BERT model for sentiment classification and BERTopic for thematic structure mining. Results: TikTok videos exhibited higher engagement metrics but shorter durations (P < .001). For GQS scores, professional sources were significantly higher than non-professional sources (P < .001), though no significant platform difference was found (P = 0.455). Regarding mDISCERN scores, Bilibili was significantly superior to TikTok (P < .05), yet no significant difference was observed between professional and non-professional sources (P = 0.23). PEMAT-U scores were significantly higher on TikTok compared to Bilibili (P < .001), but actionability (PEMAT-A) was consistently low across all platforms and sources, with no significant differences (P > .05). Regression analysis indicated that content reliability was the strongest predictor of quality, while video duration and quality significantly predicted reliability. Comment sentiment was predominantly neutral (72.4%), followed by positive (18.9%), with negative being the lowest (8.7%). Topic modeling revealed "Functional and Rehabilitation Discussion," "Discussion on Disease," and "Discussion on Treatment" as key themes. Conclusions: Content quality and reliability vary on Chinese video platforms regarding meniscal injury. While professional sources provide higher quality content, their reliability is not statistically superior to non-professional sources in this context. A universal deficiency in video actionability across all platforms and sources highlights a critical "understandable but not actionable" gap. Content creators should prioritize information accuracy and actionability to better empower public health management in the digital age.
Background: Chinese patent ethnomedicines(CPMs) are a form of traditional Chinese patent medicine that originate from the traditional medicines of ethnic minorities and are widely used in clinical pra...
Background: Chinese patent ethnomedicines(CPMs) are a form of traditional Chinese patent medicine that originate from the traditional medicines of ethnic minorities and are widely used in clinical practice. However, existing evidence for their application remains unclear. Therefore, to address this gap, this comprehensive scoping review will be performed to provide an overview of the available evidence from Chinese patent ethnomedicine preparations. Objective: This review aims to provide the evidence profile of oral CPMs. This study will elucidate the current state of the evidence with respect to these medicines and identify research gaps. The detailed steps for conducting this review are outlined in this protocol. This review will contribute to a better understanding of CPMs. Methods: This review will include clinical studies of CPMs irrespective of study design. The frameworks described by Arksey and O'Malley, Levac, and the Joanna Briggs Institute will be used to guide the current scoping review. This review will include six steps: (1) identify the research question;(2) collect information about Chinese patent ethnomedicines from national related drug catalogues; (3) search the MEDLINE (via PubMed), Embase, Web of Science, Cochrane Library and Chinese databases from inception to February 2025 to identify relevant publications; (4) screen the literature against the eligibility criteria; (5) extract data by using a predefined standardized data extraction form; and (6) summarize, discuss, analyse, and report the results. We will also present the results via data visualization techniques. Results: We will synthesize data on CPMs by conducting the Scoping Review, drawing the evidence maps, identifying the clinical research characteristics related to AEs features identifying , as well as highlighting the limitations and gaps in the literature. We expect to publish the results in 2026. Conclusions: The information obtained through this review could inform future research involving CPMs. Clinical Trial: Review registration number https://osf.io/e763b.
Background: Digital media memes have emerged as influential tools in health communication, particularly during the COVID-19 pandemic. While they offer opportunities for emotional engagement and commun...
Background: Digital media memes have emerged as influential tools in health communication, particularly during the COVID-19 pandemic. While they offer opportunities for emotional engagement and community resilience, they also act as vectors for health misinformation, contributing to the global infodemic. Despite growing interest in their communicative power, the role of memes in shaping public perception and misinformation diffusion remains underexplored in infodemiology. Objective: This integrative review aims to analyze how memes influence emotional, behavioral, and ideological responses to health crises, and to examine their dual role as both contributors to and potential mitigators of infodemics. The paper also explores strategies for integrating memes into public health campaigns and infodemic management. Methods: Using an integrative narrative approach, this review synthesizes evidence from 14 peer-reviewed studies, including empirical research on social media behavior, misinformation dynamics, and digital health campaigns. The analysis is grounded in infodemiological and infoveillance frameworks as established by Eysenbach, incorporating insights from psychology, media studies, and public health. Results: Memes function as emotionally salient and visually potent carriers of health-related narratives. While they can simplify complex messages and foster adaptive humor during crises, they are also susceptible to distortion, particularly in echo chambers and conspiracy communities. Findings reveal that misinformation-laden memes often leverage humor and disgust to bypass critical thinking, and their viral potential is linked to emotional intensity. However, memes have also been successfully integrated into prebunking strategies, increasing engagement and reducing susceptibility to false claims when culturally tailored. The review identifies key mechanisms that enhance or hinder the infodemiological value of memes, including political orientation, digital literacy, and narrative framing. Conclusions: Memes are a double-edged sword in the context of infodemics. Their integration into infodemic surveillance and digital health campaigns requires a nuanced understanding of their emotional, cultural, and epistemic effects. Public health institutions should incorporate meme analysis into real-time infoveillance systems, apply evidence-based meme formats in prebunking efforts, and foster digital literacy that enables critical meme consumption. Future infodemiology research should further explore the long-term behavioral impacts of memetic misinformation and the scalability of meme-based interventions.
Background: The sugar market in Indonesia reveals unique patterns of consumer behavior shaped not only by economic factors but also by deeply rooted cultural meanings. This study explores how symbolic...
Background: The sugar market in Indonesia reveals unique patterns of consumer behavior shaped not only by economic factors but also by deeply rooted cultural meanings. This study explores how symbolic values attached to sugar drive persistent demand, often beyond rational or controllable consumption, highlighting the need for a demand-side perspective in the economic sociology of sugar markets. Objective: This research seeks to analyze the phenomenon of non-negotiable symbolic value and its implication to the uncontrollable sugar consumption in Indonesia. The exploration of product valuation in the social order of markets (Beckert, 2009) offers insights into both the symbolic and material value of the product. Methods: The applied research methodology complements various digital mixed-method approaches utilized in prior research. Digital data sourced from online media news and YouTube videos were visualized through TNA and SNA to describe the symbolic and material value of sugar. Additionally, in-depth interviews were conducted with key actors and limited field observations were carried out on food and drink labels. Results: This study reveals that the symbolic value of sugar increases significantly when it is processed into food or drinks, particularly impacting food habits and habitus across diverse ethnic groups in Indonesia, which have fostered a strong dependence on sugar from an early age. The lack of adherence to sugar content labelling regulations on food and drink packages poses a challenge in changing consumer perceptions concerning the risks of excessive sugar consumption. Conclusions: This study offers an insight into the demand side of economic sociology concerning the sugar market. It delves into strategies to address or mitigate the sugar-driven food habits and habitus of the community from the perspective of consumer behavior. Simultaneously, it examines how producers adhere to regulations aimed at controlling the sweetness level in food and drinks, thus controlling sugar consumption and reducing the prevalence of degenerative diseases.
Background: The rise of generative artificial intelligence (gAI) has created both opportunities and challenges in higher education. Although the potential benefits of learning support are widely recog...
Background: The rise of generative artificial intelligence (gAI) has created both opportunities and challenges in higher education. Although the potential benefits of learning support are widely recognized, little is known about how incoming medical students in Japan perceive and intend to use such technology. Objective: This study investigated the status of gAI usage, learning behaviors, and perceptions of first-year medical students in Japan. Methods: An anonymous online survey was conducted among 118 first-year medical students at Chiba University in April 2025. The questionnaire assessed prior gAI use, willingness to learn, perceptions of gAI, and the intention to use it academically. Likert scales, correlation analyses, and content analyses of free-text responses were used. Results: Of the respondents, 84.7% had prior experience with the gAI, primarily in language learning and information gathering. However, only 49.2% had learning experiences, mostly through informal sources, such as web browsing and peer interaction. Students showed a high willingness to learn about gAI (mean score: 4.3/5.0), which correlated with positive perceptions. Despite this interest, attitudes toward using gAI for academic assignments were neutral (mean 3.0/5.0). Content analysis of the open-ended responses revealed three types of attitudes: positive, cautious, and negative. Conclusions: Although most students used the gAI, their limited exposure to formal learning suggests that self-directed experience alone may not foster confidence or informed use. Neutral attitudes and mixed qualitative responses highlighted the need for structured gAI literacy education that balances the benefits of ethical and critical considerations in medical education.
Background: Although the medication reconciliation is known to reduce the frequency of medication errors, its practical implementation can be challenging in several respects. In our institution, pharm...
Background: Although the medication reconciliation is known to reduce the frequency of medication errors, its practical implementation can be challenging in several respects. In our institution, pharmacy students perform admission medication reconciliations under the supervision of a pharmacist or pharmacy resident. Objective: The objective of the present study was to establish the feasibility of peer supervision (i.e. the supervision by a pharmacy student of a medication reconciliation performed by another pharmacy student) in terms of the quality and efficiency of admission medication reconciliations. Methods: A prospective, single-center, observational study was conducted in two clinical departments at Lille University Medical Center (Lille, France). Initially, organizational procedures were defined and a checklist for reconciliation supervision was developed. A baseline (reference) time period without peer supervision was compared with an implementation period with peer supervision. Results: A total of 317 medication reconciliations were conducted: 102 without supervision and 215 with supervision by a pharmacy student. Peer supervision reduced the pharmacist time required for this task by half: the mean time fell from 23 to 11 minutes. Furthermore, peer supervision was associated with a decrease in the number of errors made by students (from 1.5 to 0.9 per reconciliation) and detected by pharmacists during the reconciliation validation. Conclusions: Student peer validation appears to be an innovative, strategic method for optimizing medication reconciliations, freeing up pharmacist time, and leveraging the skills of pharmacy students.
Background: Diet-related Health Recommender Systems (HRS) have gained attention for their potential to provide personalized dietary guidance, particularly for patients with chronic conditions. However...
Background: Diet-related Health Recommender Systems (HRS) have gained attention for their potential to provide personalized dietary guidance, particularly for patients with chronic conditions. However, studies on diet-related HRS in healthcare are relatively limited. Objective: This study aims to conduct a scoping review of the current research on diet-related HRS for patients with chronic health conditions, identify existing gaps, and suggest future research directions to enhance their effectiveness in healthcare settings. Methods: The scoping review was conducted in line with the guidelines of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) extension for scoping reviews. A search and screening of English and Chinese literature published in 10 databases from January 2010 to October 2024 was carried out. The literature included was subsequently summarized and analyzed. Results: Of 4370 studies retrieved, 15 studies were included. Thematic analysis was applied to generate the following themes: basic study information, target users, function structure, recommendation content, implementation of recommendation features, and evaluation of the diet-related HRS. Conclusions: Diet-related HRS offer personalized dietary recommendations for patients with chronic health conditions. However, current research in this area is still in its infancy, with a limited number of studies and significant room for improvement. Therefore, future research should focus on expanding their applicability across a wider range of diseases and target users, enhancing the intelligence, accuracy, and user satisfaction of diet-related HRS, standardizing evaluation methods, and improving behavioral changes driven by dietary recommendations. These advancements will collectively enhance the overall effectiveness of diet-related HRS.
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: Sleep is an important component of human health and can be measured longitudinally using digital activity trackers. Further, decentralized digital research data collection has the potentia...
Background: Sleep is an important component of human health and can be measured longitudinally using digital activity trackers. Further, decentralized digital research data collection has the potential to provide a real-world picture of sleep in large populations. We hypothesized that longitudinal sleep patterns from activity trackers could predict risk of obstructive sleep apnea (OSA) similar to the Berlin questionnaire and risk for hypertension based on self-report. Objective: To test the ability of biometric to predict risk for human disease. Methods: We recruited adults ≥18 years nationwide to join our sleep-focused smartphone-based study, called the Research Framework for Exploring Sleep Health (REFRESH). Participants were asked to fill out health-related surveys including the Berlin questionnaire, which also includes self-reported hypertension, and the Horne-Ostberg questionnaire for chronotype. Participants were asked to optionally link their own activity tracker to the application to collect longitudinal sleep data. Results: We analyzed sleep data from 391 participants, 67.9% of which were women, and 40.4% of whom demonstrated an evening chronotype. Collinearity testing showed that OSA risk and self-reported hypertension could be considered independently. Increased sleep variability predicted risk of both OSA and hypertension in this decentralized cohort, when using data from the Berlin questionnaire as the ground truth. Conclusions: Decentralized sleep research could provide important information regarding risk for some health outcomes. Sleep variability is gaining increasing importance in the context of sleep health. Clinical Trial: NCT05197738
Background: Digital health platforms that integrate patient-reported outcome measures (PROMs) with wound image submissions offer new opportunities for remote wound surveillance. However, the alignment...
Background: Digital health platforms that integrate patient-reported outcome measures (PROMs) with wound image submissions offer new opportunities for remote wound surveillance. However, the alignment between patient-reported symptoms and physician clinical judgment remains underexplored, particularly in real-world settings. Objective: This study aimed to evaluate the diagnostic performance of PROM-reported wound infection in predicting physician-initiated callbacks and to explore the symptom features associated with patients' perception of infection. Methods: We conducted a retrospective observational study at a tertiary medical center in Taipei, Taiwan. Patients with acute or chronic wounds were enrolled in a chatbot-assisted digital monitoring program between June 30, 2022, and March 1, 2023. Using their mobile devices, patients submitted wound photographs and completed a structured symptom checklist, including indicators such as redness, darkness, and infection. A senior plastic surgeon independently reviewed each image to determine the need for clinical follow-up (callback), which served as the reference outcome. The presence of “infection” in the PROM checklist served as the primary predictor. Sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve (AUC) were used to assess predictive accuracy. A secondary analysis examined associations between symptom features and infection reporting using logistic regression. Results: Among 2,297 wound image entries from 270 patients, PROM-reported infection showed high sensitivity (94.0%) and an AUC of 0.9575 (95% CI: 0.9502–0.9648) for predicting physician callbacks. In the acute wound subgroup, the AUC remained high (0.9335). Redness was the strongest correlate of infection reporting (OR = 31.6; 95% CI: 23.1–43.2), while skin darkness was negatively associated with perceived infection in acute wounds (OR = 0.415; 95% CI: 0.203–0.850), indicating potential misinterpretation. Conclusions: Patient-reported infection through a digital platform demonstrated high sensitivity in identifying wounds requiring medical attention. However, notable false-negative rates and symptom misinterpretation underscore the need for improved patient education and real-time decision support. These findings support the utility of PROM-based systems for remote triage and highlight the importance of integrating patient-clinician feedback loops to enhance wound care safety.
Background: Adolescent depression has negative health and economic consequences both in the short and long term. Interventions aimed at improving parenting skills to prevent or reduce depressive symp...
Background: Adolescent depression has negative health and economic consequences both in the short and long term. Interventions aimed at improving parenting skills to prevent or reduce depressive symptoms in adolescents show promise, but there has been limited investigation of the cost-effectiveness of online parenting interventions. Objective: To estimate the economic costs, health-related quality of life outcomes and cost-effectiveness of an online personalised parenting intervention to prevent affective disorders in high-risk adolescents compared to a standard educational package. Methods: A cost-utility analysis was conducted based on data from a randomised controlled trial. The base-case analysis took the form of an intention-to-treat analysis conducted from a UK public sector perspective and separately from a societal perspective. Costs (£ 2022–2023 prices) were collected prospectively over a 15-month follow-up period. A bivariate regression of costs and quality-adjusted life-years (QALYs), with multiple imputation of missing data, was conducted to estimate the incremental cost per QALY gained and the incremental net monetary benefit of the personalised parenting intervention in comparison to the standard educational package. Pre-specified sensitivity analyses and subgroup analyses respectively explored uncertainty and heterogeneity surrounding cost-effectiveness estimates. Results: Participants (n=512) were randomised to the personalised parenting intervention (n=256) or the standard educational package (n=256). Mean (standard error) public sector costs over 15 months were estimated at £2,106 (£442) in the personalised parenting arm versus £1,909 (£388) in the standard educational package arm (mean difference: £197, p=0.740). Mean (standard deviation) observed QALY estimates were estimated at 0.84 (0.32) versus 0.82 (0.33), respectively (mean difference: 0.02, p=0.740). The base case (imputed) analysis generated an incremental cost of £639 (95%CI: £272 to £988) and incremental QALYs of 0.013 (95%CI: -0.021 to 0.042), indicating a 13%-27% probability of cost-effectiveness for the personalised parenting intervention, at cost-effectiveness thresholds of £20,000 and £30,000 per QALY. A sensitivity analysis, using observed data only (without imputation) generated an incremental cost of -£1,096 (95%CI: -£2,964 to £771) and incremental QALYs of 0.120 (95%CI: -0.053 to 0.293), but there was insufficient data to estimate probability of cost-effectiveness. The base-case cost-effectiveness results remained robust to other sensitivity analyses. Conclusions: This study found no evidence that an online parenting programme to prevent affective disorders in high risk adolescents was cost effective compared to a standard educational package. Clinical Trial: ISRCTN63358736
Background: Clinical reasoning is a key skill of the medical profession. In many virtual patient environments, the students enter the diagnoses, and all students receive the same feedback with an expl...
Background: Clinical reasoning is a key skill of the medical profession. In many virtual patient environments, the students enter the diagnoses, and all students receive the same feedback with an explanation why a certain diagnosis is considered correct. Results of meta-analyses highlight the benefits of feedbacking information to students based on their individual answers. Such adaptive feedback is time and resource demanding. Objective: We propose computer-supported adaptive feedback as an interactive, resource-optimised and scalable alternative. Methods: In the current study we compare static expert feedback agains computer supported adaptive feedback in two learning modes, individual and collaborative learning modes. Overall 105 students completed a pre and post test, consisting of 10 multiple choice items and 12 key feature items. In the meantime they diagnosed 8 virtual patients with either adaptive feedback or static feedback, either in the collaborative or individual learning mode. Results: Results indicate that students who received computer supported adaptive feedback outperformed students who received static feedback in the posttest independent from the learning mode. Students who worked in the collaborative learning mode had a higher diagnostic accuracy in the learning phase, but not in the posttest, independent from the feedback given. Conclusions: Considering the novelty of the system in itself and the presentation of the adaptive feedback to the students the results are promising. With future development and implementation of artificial intelligence in the generation of answers the learning of medical students. Until then an NLP-based system, such as the one presented in this study, seems to be a viable solution to provide a large number of students with elaborated adaptive feedback. Clinical Trial: 17-250
Objectives: This study examines the relationship between extreme heat and alcohol consumption among older Americans, emphasizing the moderating effects of early-life experiences within a life course f...
Objectives: This study examines the relationship between extreme heat and alcohol consumption among older Americans, emphasizing the moderating effects of early-life experiences within a life course framework.
Methods: Using data from over 20,000 individuals aged 50+ in the Health and Retirement Study (1996–2018), we analyzed the impact of extreme heat (>95 °F) on alcohol consumption, considering early-life factors such as parental substance abuse, law enforcement encounters, and relationships with fathers.
Results: Extreme heat exposure significantly increased alcohol consumption (0.21% per additional extreme heat day, p<0.001). A positive father-child relationship buffered this effect, while adverse early-life experiences, including law enforcement encounters (0.08%, p<0.001) and parental substance abuse (0.05%, p<0.001), exacerbated it.
Conclusion: Given the link between extreme heat and alcohol use in older adults, further longitudinal research and targeted interventions are needed to mitigate associated health risks.
Background: The Niger Delta, despite being Nigeria’s oil-rich region, suffers from severe environmental degradation that threatens food production, community health, and economic stability. Oil spil...
Background: The Niger Delta, despite being Nigeria’s oil-rich region, suffers from severe environmental degradation that threatens food production, community health, and economic stability. Oil spills, gas flaring, deforestation, and ineffective policy responses have transformed this once fertile area into one of the most ecologically and socioeconomically vulnerable zones in the country. This study addresses the pressing need for a comprehensive understanding of how environmental degradation exacerbates hunger and poverty. Objective: This study examines how oil-induced environmental degradation impacts land quality, agricultural productivity, and household food security in the Niger Delta. It assesses local perceptions, evaluates the effectiveness of government and corporate responses, and explores the use of predictive analytics to forecast poverty and food insecurity. Together, these objectives aim to inform targeted, data-driven policy interventions. Methods: A narrative literature review was conducted, drawing from peer-reviewed Q1/Q2 journal articles, government and NGO reports, and international agency publications. Data from 2000–2024 were synthesized using thematic analysis to link oil-related environmental degradation to food production, poverty, and health indicators. Secondary data were complemented by spatial and perception-based insights. Results: The study found that over 240,000 barrels of crude oil are spilled annually, causing large-scale land degradation and biodiversity loss. Cassava and yam production declined by 40% and over 50%, respectively, while fish catch dropped by two-thirds. Over 70% of Niger Delta residents live below the poverty line, and food insecurity affects most households. Local perceptions identified oil spills, gas flaring, and water pollution as primary drivers of hunger. Predictive analytics, when integrated with environmental and socioeconomic data, proved effective in identifying high-risk areas for targeted intervention. Conclusions: Oil-induced environmental degradation is a key driver of hunger, poverty, and social unrest in the Niger Delta. While government and corporate interventions exist, they are often ineffective, poorly aligned with community needs, and marred by lack of transparency. Policymakers should adopt an integrated response strategy that includes predictive poverty analytics, robust environmental governance, and community-led development planning. Strengthening data systems and aligning aid with local realities are essential for resilience building. This study provides a data-driven foundation for understanding the intertwined crises of environmental degradation, food insecurity, and poverty in the Niger Delta. It advocates for the innovative use of AI-enabled predictive tools to drive more effective, equitable, and forward-looking policy responses in ecologically fragile zones.
Background: The growing challenges in European healthcare systems, such as demographic change and the shortage of healthcare professionals, require innovative concepts to improve care and rehabilitati...
Background: The growing challenges in European healthcare systems, such as demographic change and the shortage of healthcare professionals, require innovative concepts to improve care and rehabilitation of cancer patients. Digital health solutions such as point-of-care devices have the potential to enhance treatment pathways and outcomes by facilitating remote monitoring. However, the implementation of eHealth solutions faces major challenges, such as digital infrastructure gaps, various levels of digital health literacy or cultural resistance. This implementation report explores the initial phase of implementing digital solutions for adult cancer patients across the South Baltic Region. Objective: The main objective is to identify and address common problems, barriers, challenges, and opportunities for the implementation of eHealth solutions. Another goal is to support cancer patients through the integration of innovative digital tools, particularly the HemoScreen™ device for point-of-care blood testing and digitally aided early rehabilitation. Ultimately, the research aims to contribute to a structured, standardized implementation model that can optimize digital health services and improve cancer care in diverse settings. Methods: The AMBeR study involved a series of implementation workshops at seven pilot sites in Germany, Denmark, Poland, Lithuania, and Sweden, with participation from various professional groups in cancer care. A process mapping method combining service design and A3 methodology was used to assess current workflows and plan digital interventions. Stakeholder analyses, contextual assessments, and status quo evaluations were conducted using written notes and structured templates provided in advance at each pilot site to support the workshops. The Consolidated Framework for Implementation Research (CFIR) guided the analysis and ensured systematic identification of potential barriers and enabling factors for the implementation of digital health services. Results: The ten workshops revealed strong stakeholder engagement and cross-professional collaboration, indicating strong commitment to implementing eHealth-based interventions. Most pilot sites reported significant potential for improving cancer care and rehabilitation, highlighting long waiting times, accessibility issues, and the need for better digital solutions as key areas for improvement. Interoperability of digital systems and integration into existing national eHealth infrastructures were identified as critical factors, with noticeable differences among countries. Nations like Denmark and Sweden benefited from robust infrastructures, while Germany faced challenges due to fragmented digital integration. Training healthcare personnel and addressing regulatory and cultural issues emerged as essential for successful implementation. Conclusions: Addressing challenges such as infrastructural disparities, data protection concerns, and variations in digital health literacy is essential for widespread and successful implementation. Joint efforts and stronger political coordination, along with tailored strategies for different cultural contexts, are crucial for optimizing digital health solutions for cancer patients across the South Baltic Sea Region. These findings pave the way for developing a comprehensive electronic model that can serve as a guide for integrating innovative eHealth devices into routine oncology care. Clinical Trial: NCT06809101; NCT06768918
Background: Screen-based media use among children has been increasing, particularly in lower socioeconomic groups. As this behavior is linked to obesogenic habits, such as physical inactivity, poor di...
Background: Screen-based media use among children has been increasing, particularly in lower socioeconomic groups. As this behavior is linked to obesogenic habits, such as physical inactivity, poor dietary habits, and disrupted sleep patterns, it is crucial to examine the associations between screen-based media use and adiposity in primary school children, particularly those from socially vulnerable contexts. Objective: To examine the associations between screen-based media use and adiposity in primary school children from socially vulnerable contexts. Methods: This study, part of the BeE-school Project, included 735 children (mean age 7.7 ± 1.2 years) from 10 primary schools located in vulnerable contexts in northern Portugal. Researchers recorded weight, height, and waist circumference, and then Body mass index z-scores (BMIz) and waist-to-height ratio (WHtR) were calculated. Screen-based media use was also reported by parents using the ScreenQ tool that includes four domains (screen access, frequency of use, media content and caregiver-child co-viewing). Sociodemographic and anthropometric data of parents were reported via questionnaire. Generalized Linear Models (GLM) were applied. Results: Higher screen-based media use score was associated with higher BMIz and WHtR (b = 0.064, 95% CI 0.034 to 0.094; b = 0.002, 95% CI 0.001 to 0.003, respectively) even after adjusting for relevant variables. Similar associations were observed for the domains of screen access, frequency of use, and media content. Conclusions: Screen-based media use is linked to increased adiposity in vulnerable children. Reducing screen access, limiting usage frequency, and curating media content could improve health outcomes. Interventions for obesity prevention should consider these factors. Clinical Trial: This study is part of the BeE-school project, a cluster randomized controlled trial registered on ClinicalTrials.gov (identifier NCT05395364).
Background: Transcatheter aortic valve implantation (TAVI) has become a potential treatment modality for symptomatic patients with severe aortic stenosis (AS) across all surgical risk profiles. Howeve...
Background: Transcatheter aortic valve implantation (TAVI) has become a potential treatment modality for symptomatic patients with severe aortic stenosis (AS) across all surgical risk profiles. However, peri-procedural stroke remains a persistent and serious complication with significant implications for patient outcomes and healthcare systems. Reported incidence ranges between 2-7%. As the benefit of cerebral protection devices and the optimal antithrombotic regime following TAVI remain unclear, understanding contemporary risks and timings of stroke are important in order to tailor peri/post procedural stroke risk reduction strategies. Objective: To evaluate the incidence, timing, and predictors of stroke and transient ischaemic attack (TIA) within 30 days post TAVI in a contemporary real-world all-comers registry. Methods: Consecutive patients undergoing TAVI (n=980) between January 2020 and February 2024 were included in this retrospective study. A stroke diagnosis was made based on the Valve Academic Research Consortium-2 (VARC-2), defined as a focal or global neurological deficit >24 hours or <24 hours if haemorrhage or infarct was found on neuroimaging. TIA was defined as the duration of a focal or global neurological deficit <24 hours. Those with documented evidence of stroke or TIA were sub-divided into acute (<24 hours post procedure) and subacute (1-30 days post procedure). Patients from outside our catchment area were excluded (n=46) due to the lack of access to patient records. Two patients were excluded as no valve was deployed. Results: A total of 932 patients (41% female, mean age 81.6±6.9 years) were included in the study. TAVI was performed for severe AS in the context of degenerative calcific disease of native valves in 94% (n=873), 6% (n=57) of TAVIs were valve-in-valve procedures, and only one patient was treated for severe stenosis of a congenital (Bicuspid) aortic valve. 84% (n=779) had no prior history of stroke and 26% had a history of diabetes mellitus. 60% (n=555) of patients were in sinus rhythm prior to TAVI, 35% (n=326) were in atrial fibrillation or flutter and 5% (n=51) were in a paced rhythm. Self-expanding valves were implanted in 58% (n=542) of cases and Balloon-expanding valves were used in the remainder. The majority of cases were performed transfemorally (96%). Pre-dilatation balloon aortic valvuloplasty was performed in 16% (n=150) of cases and the median procedure time was 76 mins [IQR 66.0, 89.0]. Vascular closure device successfully achieved haemostasis in 94% (n=877) of procedures. The thirty-day incidence of stroke/TIA was 3.2% (n=30), with 35% (n=11) occurring within 24 hours and the majority occurring within the first 48 hours (58%, n=18). The median number of days of stroke/TIA post-TAVI was 1.0 [0.0, 3.0]. Most (80%, n=24) were ischaemic strokes and of these one had a haemorrhagic transformation. Diabetes is the only variable predictive of stroke at 30 days HR 2.14 (95% CI 1.01 – 4.56), p=.049 using logistic regression. Conclusions: Most cerebrovascular events occurred early post TAVI. Effective stroke prevention strategies, including optimized antithrombotic regimens and the role of cerebral protection devices, warrant further evaluation. Clinical Trial: n/a
Background: Frozen shoulder is a painful and disabling condition affecting approximately 5% of the population, often leading to prolonged impairment and incomplete recovery. While physiotherapy is the...
Background: Frozen shoulder is a painful and disabling condition affecting approximately 5% of the population, often leading to prolonged impairment and incomplete recovery. While physiotherapy is the mainstay of treatment, adherence remains suboptimal. Gamification—integrating game elements into rehabilitation—has shown potential to enhance motivation and accessibility, though its application in frozen shoulder management remains underexplored. Objective: To evaluate the efficacy of a fully gamified, self-directed home rehabilitation program (HomeRehab) using a laptop-based platform in improving shoulder function, pain, quality of life, sleep, and range of motion in patients with frozen shoulder. Methods: This pilot, single-group, pretest-posttest quasi-experimental study enrolled 20 patients diagnosed with unilateral frozen shoulder. Participants used a customised version of the Rehaboo! platform incorporating physiotherapist- and surgeon-guided exercises. Outcomes measured at baseline, 6, 12, and 24 weeks included the Oxford Shoulder Score (OSS), Disabilities of the Arm, Shoulder, and Hand (DASH), EQ-5D, Pittsburgh Sleep Quality Index (PSQI), and goniometric range of motion (RoM). Statistical analysis was conducted using Friedman tests and Wilcoxon signed-rank tests with Holm-Bonferroni correction. Results: 17 patients were included in the final analysis. The mean age was 58.2 years (SD = 8.9), with 11 males and 6 females. Over the 24-week period, participants demonstrated statistically and clinically significant improvements in several domains. The mean Oxford Shoulder Score (OSS) improved from 29.2 to 16.5 (p = .010), and the mean Disabilities of the Arm, Shoulder and Hand (DASH) score decreased from 63.4 to 41.1 (p = .010). Health-related quality of life also improved, with the EQ-5D score decreasing from 7.2 to 5.5 (p = .030). Sleep quality improved, as indicated by a reduction in Pittsburgh Sleep Quality Index (PSQI) scores from 5.7 to 3.1 (p = .030). Shoulder range of motion improved across all planes—abduction (95° to 132°), external rotation (23° to 48°), internal rotation (32° to 49°), and forward flexion (114° to 144°)—though these changes were not statistically significant. The gains exceeded minimal clinically important differences for OSS, DASH, and EQ-5D. Conclusions: This study supports the potential of a gamified, self-led rehabilitation program to deliver meaningful improvements in function, symptoms, and quality of life for individuals with frozen shoulder. Gamification may enhance accessibility and adherence, offering a promising alternative to traditional physiotherapy. Larger, controlled trials are needed to confirm non-inferiority and long-term efficacy.
Background: Serious games are increasingly recognized as effective tools for healthcare interventions, particularly for adolescents with behavioral and developmental needs. However, inconsistent desig...
Background: Serious games are increasingly recognized as effective tools for healthcare interventions, particularly for adolescents with behavioral and developmental needs. However, inconsistent design frameworks and limited integration of theoretical concepts challenge their scalability and impact. Understanding how these concepts are applied in serious game design is essential for enhancing their real-world impact. Objective: The objective of this systematic review is to examine the current state of the art in the use of serious gaming interventions in healthcare for adolescents with behavioral or developmental issues. The review will focus on elucidating the elements involved in how these games are designed and can contribute to learning. The review is conducted from the theoretical framework perspectives of boundary crossing, transfer and a model of reality. Methods: A total of five databases (PubMed, Scopus, ERIC, PsycINFO and EMBASE) were searched for relevant titles and abstracts. The databases were identified as relevant and cover a wide range of published research into health and social science. Results: A total of 34 relevant studies were included in the review, which covered a range of serious gaming artefacts with the objective of identifying learning or development opportunities for adolescents with behavioral or developmental issues. Conclusions: This review highlights the transformative potential of serious games in healthcare, particularly for individuals with developmental and behavioral needs, by fostering skill acquisition, collaboration, and real-world application. Despite their potential, the development of serious games requires a more structured integration of theoretical frameworks to ensure scalability, replicability, and sustained impact. Future research should prioritize standardized methodologies, longitudinal evaluations, and a focus enhanced collaboration.
Background: Background: Patient safetyisessentialto thequalityofcaregivento patients, and it remainsachallenge for countries at all stages of development. There appears to be a common acceptance of th...
Background: Background: Patient safetyisessentialto thequalityofcaregivento patients, and it remainsachallenge for countries at all stages of development. There appears to be a common acceptance of the necessity of building patient safety culture within health care organizations. Hospitals with a positive patient safety culture are transparent and fair with staff when incidents occur, learn from mistakes, and rather than blaming individuals, look at what went wrong in the system. Health care providers are willing to report the errors but, due to poor reporting system and culture of blame and shame, there exists struggle of disclosure of adverse events. Objective: Objective: This studyaimed To assess incident reporting behavior and associated factors among Nurses working in Addis Ababa Public hospitals in Addis Ababa, Ethiopia, 2024. Methods: Methods: A cross-sectional institutional-based study was conducted with a total of 233 randomly selected participant samples drawn from six public hospitals in Addis Ababa, between July 16 and September 16, 2024. A structured interviewer-administered questionnaire and observational checklist based on previous studies were employed for data collection. Bivariate and multivariate analysis used a binary logistic regression model to determine the relationships between the dependent variables and the independent variables and the strength of association was calculated as Adjusted Odds Ratios (AOR),and 95% Confidence Interval (CI) at <0.05 p-value. Results: Result: A total of 245 study subjects were recruited. 233 were interviewed yielding response rate of 95.8% of the 233 participants were female (162(69.5%)), and had a degree (145 (62%)). The largest group of study participants reported having 6-10 years of experience in the hospital (53.5%) and in the current unit (40%). Additionally, Degree nurse participants had a 3.027 times greater odd ofofreporting patient safety incident when compared to Diploma Nurse (AOR: 3.027; 95%CI: 1.736-5.279). Nursesthat reported more than 5 years (31.7%) of experience had a 1.71 times greater odd of reporting safety incidents compared to nurses that reported less than 5 years of experience (AOR: 1.71; 95%CI: 1.236- 2.379). Conclusions: Conclusion: - Safety incident reporting culture score of participants was less than 70%. Training on patient safety and incident reporting positively affects reporting. Clear guidelines should be put onpatient safety and incident reporting. Focus should be given to trainings. Clinical Trial: Safety culture, reporting,AmongNurseAddisAbaba.
Lung cancer continues to pose a global health burden, with delayed diagnosis contributing significantly to mortality. This study aimed to identify the most predictive behavioural, physiological, and p...
Lung cancer continues to pose a global health burden, with delayed diagnosis contributing significantly to mortality. This study aimed to identify the most predictive behavioural, physiological, and psychosocial factors associated with lung cancer in a young adult population using a multivariate logistic regression framework. A dataset of 276 respondents was analysed after removing duplicates from an original sample of 309. The dependent variable was self-reported lung cancer status, while independent variables included smoking behaviour, symptoms such as fatigue and coughing, and indicators of chronic disease and psychosocial stress. Univariate and bivariate analyses were conducted prior to model development. Nine predictors demonstrated statistical significance and were retained in the final model. The model exhibited strong predictive performance, achieving an AUC of 0.9625 and Tjur’s R² of 0.566, with no evidence of multicollinearity among predictors. Fatigue, chronic disease, coughing, and swallowing difficulty emerged as the most influential risk factors, while smoking had a comparatively smaller effect size, likely due to the young age profile of participants. Peer pressure and yellow fingers were also significant, offering novel contextual insights into behavioural risk adoption. The findings support the integration of multidimensional, low-cost, self-reported indicators into lung cancer screening protocols, especially in resource-limited settings. This study provides a data-driven foundation for developing early detection models and public health interventions tailored to younger populations. Future research should incorporate longitudinal and biomarker data to enhance causal inference and predictive accuracy.
Abstract
Acute promyelocytic leukemia (APL), a subtype of acute myeloid leukemia (AML), is characterized by the t(15;17)(q22;q21) translocation, resulting in the PML/RARα fusion protein. All-trans r...
Abstract
Acute promyelocytic leukemia (APL), a subtype of acute myeloid leukemia (AML), is characterized by the t(15;17)(q22;q21) translocation, resulting in the PML/RARα fusion protein. All-trans retinoic acid (ATRA) is an effective treatment for APL. Among the most severe side effects of ATRA is differentiation syndrome. While skin toxicity is common, scrotal lesions, including ulcerations, are rarely reported, and their pathogenesis remains unclear. We present a case of a 24-year-old male diagnosed with APL who developed painful scrotal ulcers on day 23 of ATRA therapy. These ulcers responded to the discontinuation of ATRA and treatment with topical corticosteroids. Discontinuing ATRA can potentially compromise the hematological response, leading most clinicians to continue ATRA in combination with steroid therapy. However, ATRA should be discontinued if steroid therapy fails. Awareness of this rare adverse effect is essential to ensure timely and appropriate therapeutic management.
Background: Accurate and accessible measurements of inflammatory biomarkers are crucial for the diagnosis and monitoring of inflammatory diseases. The gold-standard C-reactive protein (CRP) requires v...
Background: Accurate and accessible measurements of inflammatory biomarkers are crucial for the diagnosis and monitoring of inflammatory diseases. The gold-standard C-reactive protein (CRP) requires venipuncture, which, despite providing high-quality samples, can cause discomfort, anxiety, and pain, particularly in vulnerable populations such as elderly patients. It is also resource intensive, unsuitable for remote or at-home use, and lacks continuous monitoring capability. These limitations limit patient autonomy and self-management, potentially leading to poorer prognosis due to delays in assessment and medical treatments. As digital health technologies advance, there is increasing interest in leveraging digital biomarkers for remote and real-time monitoring of systemic inflammation (SI). Digital biomarkers derived from non-invasive biofluids could provide a scalable solution for tracking inflammatory status, offering a patient-centered alternative to traditional blood-based assessments. To date, however, there is no consensus on the most suitable modality for assessment or its digitization potential. Therefore, a comprehensive evaluation of the feasibility, reliability, and patient acceptability towards non-invasive, digital inflammatory biomarkers is needed. Objective: Our aim is to evaluate the feasibility of various non-invasive methods to assess inflammatory markers and identify the optimal modality for predicting serum CRP levels. Methods: Inflammatory biomarkers were assessed in 20 participants (10 patients with SI defined as a CRP level >5 mg/l and 10 controls) using six non-invasive samples (urine, sweat, saliva, exhaled breath, core body temperature, and stool samples) alongside serum samples. Patient preferences were retrieved via a questionnaire. Mann-Whitney U test, Spearman’s correlation, and all-subset regression were conducted to assess the relationships between serum and non-serum biomarkers and to identify optimal predictive models for serum CRP levels. Results: CRP levels were significantly elevated in the inflammation group compared to controls in urine (median: 4.5 vs. 0.69 μg/mmol, p=0.001) and saliva (median: 4910 vs. 473 pg/ml, p=0.001). Urine and saliva CRP levels strongly correlated with serum CRP (rsp=0.886, p<0.001; rsp=0.709, p=0.0006). The multi-modal model using urine and saliva CRP predicted serum CRP levels with 76.1% outperforming single-modality models. Patient favored urine and saliva tests over blood tests. Conclusions: Urine and saliva represent promising non-invasive alternatives to traditional blood tests for assessing CRP, enabling more accessible and less invasive diagnostic and monitoring approaches.
Background: Teeth that have undergone endodontic treatment are more likely to fracture because of the remarkable loss of tooth structure. Various post systems, like prefabricated carbon fiber posts, c...
Background: Teeth that have undergone endodontic treatment are more likely to fracture because of the remarkable loss of tooth structure. Various post systems, like prefabricated carbon fiber posts, customized glass fiber posts, have been used to restore endodontically treated teeth (ETT). However, the effectiveness of these in enhancing fracture resistance remains a subject of debate. Objective: To evaluate and compare the fracture resistance of endodontically treated teeth restored using 3 different post types: prefabricated carbon fiber post, custom-made glass fiber post, and SFRC-relined fiber post. Methods: A total 30 extracted human teeth would undergo endodontic treatment and will be segregated into 3 groups based on the post type
1: Pre-fabricated carbon fiber posts
2: Customized glass fiber posts
3: SFRC-relined fiber posts
The samples would be subjected to a universal testing machine to assess their fracture resistance. Data will undergo statistical analysis using ANOVA and post-hoc test. Results: Mean fracture resistance is expected to be highest in the SFRC-relined fiber post group, followed by customized glass fiber post group, and lowest of prefabricated carbon fiber post group. Statistically significant differences are anticipated among groups (p < 0.05). The SFRC-relined fiber posts are also expected to demonstrate more favorable failure modes compared to the other groups. Conclusions: The study suggests that SFRC-relined fiber posts provide superior fracture resistance and more favorable failure modes in comparison with prefabricated carbon fiber and custom-made glass fiber post. This finding highlights potential clinical benefits of using SFRC-relined fiber post. Clinical Trial: Since this investigation will be conducted entirely as an in vitro study, registration with the Clinical Trials Registry - India (CTRI) will not be applicable and therefore not required.
Background: Non-inferiority (NI) trial designs that investigate whether an experimental intervention is no worse than standard of care have been used increasingly in recent years. The robustness of th...
Background: Non-inferiority (NI) trial designs that investigate whether an experimental intervention is no worse than standard of care have been used increasingly in recent years. The robustness of the conclusions are in part dependent on the analysis population set used for the analysis. In the NI setting, the intention-to-treat (ITT) analysis has been thought to be anti-conservative compared to the per-protocol (PP) analysis. Objective: We aim to conduct a methodological review assessing the analysis population set used in NI trials. Methods: A comprehensive electronic search strategy will be used to identify studies indexed in Medline, Embase, Emcare, and Cochrane Central Register of Controlled Trials (CENTRAL) databases. Studies will be included if they are non-inferiority trials published in 2024. The primary outcome is the analysis population used in the primary analysis of the trial (ITT or PP). Secondary outcomes will be the NI margin, effect estimates, point estimates, and corresponding confidence intervals of the analysis. Analysis will be done using descriptive statistics. Results: 1211 studies were captured using the comprehensive search strategy. We estimate around 500 trials will be eligible for extraction. Conclusions: This methodological survey of NI trials will describe the population analysis set used in primary analysis and assess factors which could be associated with each analysis
Background: The anesthesia and critical care residency program in Morocco is a four-year, time-based training program whose effectiveness is evaluated in our study through the performance of residents...
Background: The anesthesia and critical care residency program in Morocco is a four-year, time-based training program whose effectiveness is evaluated in our study through the performance of residents and the factors affecting it, based on the core competencies established by the Moroccan Board of Anesthesiology and Critical Care (MBACC). Objective: To describe anesthesia and critical care residents’ performance and its affecting factors. Methods: We conducted a single-center prospective survey in January 2024, using a self-assessment questionnaire of technical skills related to residents' practice. For each skill, we addressed questions quantifying a given item's difficulty or success rate. An overall performance composite score was calculated based on the scores obtained for each skill assessed. A multivariate analysis was performed to determine the factors affecting this performance. Results: We included 66 residents. Their end-of-course overall performance met MBACC requirements at the end of the curriculum (72.3 [68.5-75.7] for a maximum score of 100), with a progression marked by a plateau between the second and third year. Multivariate analysis identified a prior experience to residency, shift leadership, and the number of patients anesthetized per day as factors improving the overall performance, while critical care-induced stress, shift-induced stress, and the number of shifts per week reduced performance. Conclusions: The progression of residents' overall performance is eligible for optimization through an introduction to critical care, notably via simulation, to reduce the stress during practice and acquire sufficient experience to occupy a chief position during shifts while limiting the number of weekly shifts. The formulation of recommendations requires a higher level of proof, which implies an external confirmatory study on a multi-center scale.
Background: Background: Paramedics face frequent exposure to trauma and intense occupational stress, often under conditions of limited psychological support and ongoing stigma. Digital mental health i...
Background: Background: Paramedics face frequent exposure to trauma and intense occupational stress, often under conditions of limited psychological support and ongoing stigma. Digital mental health interventions have the potential to offer accessible, confidential, and tailored support. However, their acceptability and design must be informed by the lived experiences of paramedics to ensure effectiveness. Objective: Objective: This study aimed to explore UK paramedics’ experiences of trauma exposure in the workplace and their views on the design and delivery of digital mental health interventions. Methods: Methods: Semi-structured interviews were conducted with 22 UK paramedics. Participants were recruited through purposive and snowball sampling. Interviews were transcribed verbatim and analysed using reflexive thematic analysis. Ethical approval was obtained, and trauma-informed principles were applied throughout data collection and analysis. Results: Results: Five key themes were identified: (1) It Has to Feel Easy to Use - highlighting the need for digital tools that reduce cognitive burden and are accessible during unpredictable shifts; (2) Make It Fit My Needs - calling for interventions specifically designed for paramedics, with lived-experience-informed language and delivery; (3) We Need to Talk to Each Other - describing a strong desire for peer connection while recognising barriers such as stigma and shift pressures; (4) I Need to Know It’s Safe - emphasises the importance of anonymity, data privacy, and psychological safety; and (5) Support Needs to Feel Human - reinforcing the value of integrating digital tools with human connection and professional services. Participants expressed strong support for an app-based solution that offers anonymity, rapid accessibility, and flexibility, while preserving opportunities for human interaction. Conclusions: Conclusions: Paramedics face unique mental health challenges that are not adequately addressed by existing services. Digital mental health tools offer promise if they are carefully co-designed to reflect the realities of frontline work. Anonymity, usability, peer connection, and integration with existing support systems are critical to engagement. These findings offer actionable insights for the development of trauma-informed, context-sensitive digital mental health interventions for emergency service workers.
Background: The rising burden of disease associated with mental disorders calls for evidence-based psychological interventions that can be swiftly scaled up. Blending smartphone-based mental health ap...
Background: The rising burden of disease associated with mental disorders calls for evidence-based psychological interventions that can be swiftly scaled up. Blending smartphone-based mental health apps (MHapps) for delivering ecological momentary interventions (EMIs) with traditional in-person interventions may have the benefits of improving treatment adherence, the application of learned techniques into everyday life and, in turn, enhancing clinical response. However, previous work has shown that most existing MHapps were developed for specific research studies or for profit, thereby making them difficult to adapt, particularly in time-limited and resource-scarce settings. Objective: Using a phased approach, this study aimed to demonstrate how a person-centred and theory-informed MHapp could be developed in a timely and low-cost manner for use as part of blended care. Given the scarcity of digital mental health interventions for older adults, we adopted a participatory research approach to co-designing the blended intervention with two groups of older adults. Methods: In Phase 1, we reviewed existing MHapps with consideration of whether they can be adapted by individual researchers or clinicians, their key functions, and whether their efficacy has been tested. ‘No-code’ app builders were additionally reviewed, which may be alternatives if no MHapp can be utilised. In Phase 2, following the IDEAS framework, we built a prototype according to users’ needs, with its content informed by cognitive and behaviour theories (cognitive behavioural therapy [CBT] and the Health Action Process Approach [HAPA]). The prototype was then tested and refined over two rounds of 3-session co-design workshops with Peer Supporters (n = 8) and service users (n = 5) from a stepped-care intervention for older adults with depressive symptoms. Usability testing was conducted with both stakeholder groups in Phase 3. Results: Of the 149 MHapps identified, only 43 (28.9%) can be publicly downloaded. Four of them (8.3%) can be partially adapted, although no new content can be directly added. We therefore developed the MHapp using m-Path, which was the only existing no-code app development platform designed for mental health interventions. A prototype incorporating CBT-based homework and behaviour change techniques informed by the HAPA was built, with its refined version rated as highly easy to use and acceptable by both stakeholder groups. Conclusions: By integrating EMI with CBT, we demonstrated the feasibility and acceptability of a novel blended care model for reference in future work. Preliminary findings suggest high usability and clinical relevance, highlighting the potential of leveraging no-code platforms to facilitate scalable, theory-driven interventions that extend mental health support beyond traditional settings. Grounding the blended intervention in evidence-based psychological and health behaviour change theories, coupled with user involvement throughout the design process, may substantially improve clinical efficacy and reduce implementation barriers, which are areas for further investigations in future work. Clinical Trial: n/a
Background: People experiencing gambling problems often struggle to adhere to their intention to reduce time and money spent gambling. While many techniques exist to reduce gambling harm, consistently...
Background: People experiencing gambling problems often struggle to adhere to their intention to reduce time and money spent gambling. While many techniques exist to reduce gambling harm, consistently applying them across settings and at the right time remains challenging. Providing personalised, real-time support could enhance behaviour change efforts. Objective: This study evaluated a Just-In-Time Adaptive Intervention (JITAI) to help individuals adhere to gambling limits. Drawing on the Health Action Process Approach and Self-Determination Theory, the primary aim was to assess the effect of action and coping planning versus no intervention on adherence to expenditure limits. The primary proximal outcome was goal adherence, defined as unplanned expenditure (≥10% over planned expenditure per day). Secondary outcomes included intention strength, goal self-efficacy, and urge self-efficacy, all measured continuously. Methods: We conducted a fully automated and blinded micro-randomised trial (MRT) with 50:50 randomisation and a 6-month within-group follow-up. Participants were recruited online; eligibility included residing in Australia, enabling notifications, and seeking gambling support. The Gambling Habit Hacker smartphone app delivered tailored behaviour change techniques, including goal setting, action and coping planning, and self-monitoring. The MRT randomised 174 participants to test whether the app provided in-the-moment support for adhering to limits. Participants set personal expenditure goals and completed three Ecological Momentary Assessments (EMAs) daily for 28 days, tracking adherence, intention strength, self-efficacy, and high-risk situations. At each EMA, participants needing support were micro-randomised to receive action/coping planning with support or a control condition involving selection of a self-enactable strategy without support. Results: Of 238 enrolled participants, 174 completed at least one EMA. Most were male (68%) and reported moderate or mild gambling severity (52%). An intervention was delivered at least once to most participants (n = 140, 80%). Receiving an intervention did not increase the probability of adherence compared to no intervention. In contrast, supplementary analyses in which findings from the EMAs were collapsed across each day revealed the intervention was associated with lower rates of unplanned gambling expenditure when compared to the control condition. Within-group follow-up showed a large reduction in monthly expenditure (from $2,700 to just over $260) and gambling frequency (from 8–9 to 1–2 sessions) at six months. Significant improvements with small-to-large effect sizes were also observed at post-treatment and maintained at follow-up for gambling severity (dz = -0.91), self-efficacy (dz = -0.42), psychological distress (dz = -0.52), and well-being (dz = 0.70). Conclusions: Gambling Habit Hacker showed strong overall effects over time but no significant difference in adherence between intervention and control conditions. Given the strong effect over time, future studies should explore an optimised version of the app that is subject to a randomised controlled study design. Clinical Trial: This trial has been registered with the Australian New Zealand Clinical Trials Registry (ACTRN12622000497707) and was approved by the Deakin University Human Research Ethics Committee (2020-304).
Background: First responders play crucial roles for protecting citizens and communities from various hazards. Due to the high-stress nature of their work, first responders suffer significant mental he...
Background: First responders play crucial roles for protecting citizens and communities from various hazards. Due to the high-stress nature of their work, first responders suffer significant mental health issues. Existing mental health interventions, albeit their benefits, do not target cognitive processing of traumatic events such as memory and emotion. Objective: As a novel attempt using immersive virtual reality, the current work aims to examine effects of a semantically irrelevant virtual reality (SIVR) content to intervene in the retrieval of an adverse event memory and associated emotion. Methods: A total of 107 participants were recruited in the experiment and randomly assigned to one of three groups: Control Group, Comparison Group, and Intervention Group. In Stage-1, participants in all groups watched a short video of a house fire. In Stage-2, Control Group stayed seated without doing anything. Comparison Group read a text paragraph about Egyptian Ocean, as semantically irrelevant follow-up information. Intervention Group watched a 360° VR video of Egyptian Ocean. Positive And Negative Affect Schedule survey was administered each after the two stages. In Stage-3, the memory accuracy of the house fire video was assessed using a forced recognition test of 15 pairs of a true image and a fake image, generated by AI software. Results: One-way ANOVA revealed no difference of the memory accuracy between three groups. However, repeated measures ANOVA found that the SIVR experience significantly boosted positive emotion of Intervention Group participants and reduced negative feelings of participants in all groups. Conclusions: Our findings suggest that SIVR serves as a quick and affordable way to address psychological reaction after watching a traumatic event. Future research is required to generate the memory suppression effect of the SIVR content.
Background: Increasing adherence to physical activity (PA) guidelines could prevent chronic disease morbidity and mortality, save considerable healthcare costs, and reduce health disparities. We previ...
Background: Increasing adherence to physical activity (PA) guidelines could prevent chronic disease morbidity and mortality, save considerable healthcare costs, and reduce health disparities. We previously established the efficacy and cost-effectiveness of a web-based PA intervention for Latina women, which increased PA but few participants met PA guidelines and long-term maintenance was not examined. A new version with enhanced intervention features was found to outperform the original intervention in long-term guideline adherence. Objective: to determine the costs and cost-effectiveness of the enhanced multi-technology PA intervention vs. the original web-based intervention in increasing minutes of activity and adherence to guidelines Methods: Latina adults (N=195) were randomly assigned to receive a Spanish language individually tailored web-based PA intervention (Original), or the same intervention additional phone calls and interactive text messaging (Enhanced). PA was measured at baseline, 12 months (end of active intervention), and 24 months (end of tapered maintenance) using self-report (7-Day Physical Activity Recall Interview) and ActiGraph accelerometers. Costs were estimated from a payer perspective and included all features needed to deliver the intervention, including staff, materials, and technology. Cost effectiveness was calculated as the cost per additional minute of PA added over the intervention, and the incremental cost effectiveness ratios of each additional person meeting guidelines. Results: at 12 months, the costs of delivering the interventions were $16/person/month and $13/person/month in the Enhanced and Original arms, respectively. These costs fell to $14 and $8 at 24 months. At 12 months, each additional minute of self-reported activity in the Enhanced group cost $0.09 vs. $0.11 in Original ($0.19 vs. $0.16 for ActiGraph), with incremental costs of $0.05 per additional minute in Enhanced beyond Original. At the end of maintenance (24 months), costs per additional minute fell to $0.06 and $0.05 ($0.12 vs. $0.10 for ActiGraph), with incremental costs of $0.08 per additional minute in Enhanced ($0.20 for ActiGraph). Costs of meeting PA guidelines at 12 months were $705 vs. $503 in Enhanced vs. Original, and increased to $812 and $601 at 24 months. The ICER for meeting guidelines at 24 months was $1837 (95% CI $730.89-$2673.89) per additional person in the Enhanced vs. Original arm. Conclusions: As expected, the Enhanced intervention was more expensive, but yielded better long-term maintenance of activity. Both conditions were low costs relative to other medical interventions. The Enhanced intervention may be preferable in high risk populations, where more investment in meeting guidelines could yield more cost savings. Clinical Trial: NCT03491592
Background: Empty Nose Syndrome (ENS) is a debilitating condition that can occur after partial or total turbinectomy, leading to impaired nasal airflow sensation, breathing difficulties, and sleep dis...
Background: Empty Nose Syndrome (ENS) is a debilitating condition that can occur after partial or total turbinectomy, leading to impaired nasal airflow sensation, breathing difficulties, and sleep disturbances. While ENS is often diagnosed using the ENS6Q questionnaire, its precise causes remain unclear. Some patients with significant turbinate loss develop minor ENS symptoms, whereas others experience severe symptoms after minor mucosal cauterization. Understanding the structural and aerodynamic factors contributing to ENS is crucial for improving diagnosis and prevention. Objective: This study aims to identify correlations between the ENS6Q score and key anatomical and aerodynamic parameters obtained from computational fluid dynamics (CFD) simulations in ENS patients. Methods: We reconstructed patient-specific nasal cavity models from computed tomography (CT) scans and performed CFD simulations. The analysis focused on five key parameters: the remaining turbinate volume, total mucosal surface area, nasal resistance, average cross-sectional area, and airflow imbalance between the two nasal cavities. These parameters were then compared to ENS6Q scores. Results: Preliminary findings suggest that a lower remaining turbinate volume, reduced mucosal surface area are associated with higher ENS6Q scores. Additionally, significant airflow asymmetry between the two nasal cavities appears to correlate with more severe symptoms. Furthermore, our data indicate that individuals with larger nasal cavities and greater preoperative mucosal surface area tend to be more resilient to turbinectomy. For an equivalent amount of turbinate resection, patients with initially smaller nasal cavities thus having less mucosal surface experience more severe ENS symptoms. Conclusions: By quantifying the anatomical and aerodynamic characteristics of ENS patients, this study provides new insights into the structural factors contributing to ENS severity. These findings may help refine diagnostic criteria and guide surgical approaches to minimize ENS risk.
Background: Menopause symptoms are common but often inadequately addressed by primary care clinicians due to limited time for discussions and resources. Mobile health applications can play a crucial r...
Background: Menopause symptoms are common but often inadequately addressed by primary care clinicians due to limited time for discussions and resources. Mobile health applications can play a crucial role in symptom identification and management, yet many existing menopause-focused apps lack evidence-based content and medical expertise. Objective: To describe the protocol study design and methodology of a randomized controlled trial (RCT) to evaluate the effectiveness of the emmii mobile app for improving menopause-related knowledge, and shared decision-making compared to a traditional menopause education pamphlet. Methods: This RCT will recruit women aged 45–55 years with upcoming primary care appointments at Mayo Clinic within 3 weeks of the date of initial outreach. Eligible participants must be English-speaking, able to provide informed consent, and report a Menopause Rating Scale (MRS) score ≥5, which indicates that they are experiencing significant menopause-related symptoms. Eligible participants will be randomized to have access to either the emmii app (intervention, n=200) or an evidence-based menopause education pamphlet (control, n=200). The emmii app is developed with direct input from primary care clinicians certified by The Menopause Society and offers symptom tracking, personalized treatment recommendations based on a protocol, and a discussion guide to support communication between patients and their primary care clinicians. Outcomes will include a post visit survey sent to the participants and their primary care clinicians within 3 days of the appointment, and assessment of patient knowledge, clinical treatment plans and both patients and clinicians experience. The study will also compare prescribing rates of hormonal and nonhormonal therapies for menopause symptoms between the emmii intervention and control groups to assess the app’s influence on treatment patterns. Data will be analyzed using descriptive statistics, including Chi-square tests, Wilcoxon rank sum tests and multivariable modeling. Results: Data collection is scheduled to begin in April 2025. Conclusions: This protocol outlines the design and methodology of a RCT that aims to assess the impact of the emmii app in facilitating menopause care through primary care clinician-patient communication and shared decision-making. Clinical Trial: NCT06919887
Background: Long-term disease status and susceptibility to disease recurrence lead to an increasing disease burden in patients with non-Hodgkin's lymphoma (NHL). Although adverse influence of frailty...
Background: Long-term disease status and susceptibility to disease recurrence lead to an increasing disease burden in patients with non-Hodgkin's lymphoma (NHL). Although adverse influence of frailty in physical symptoms has been repeatedly reported, little attention has been paid to NHL patients and with the very limited studies, mostly are cross-sectional in nature. Our protocol provide a detailed mothods to explore the trajectory type and risk factors for frailty in NHL patients, to provide a panorama about how frailty affects NHL patients over time. Objective: The research aims to explore the frailty trajectories and influencing factors. It could offer healthcare professionals dynamic insights into frailty progression and facilitate the early identification and intervention of high-risk populations through systematic screening of contributing factors, thereby preventing the onset of frailty. Methods: This longitudinal mixed-methods study will recruit 240 patients newly diagnosed with NHL from five large public hospitals in China. Quantitative data will be collected at three time points: before chemotherapy, during the third cycle of chemotherapy, and at the end of chemotherapy. We will use validated questionnaires (i.e Tilburg Frailty Indicator) to gather information on sociodemographic data, frailty, cognition, physical condition, health literacy, anxiety and nutrition. Qualitative data will be collected via semi-structured interviews and observations at the end of chemotherapy. The growth mixture model and logistic regression analysis will be used to analyse quantitative data, and the diachronic analysis method and the directed content analysis method will be used to analysis qualitative data. Both types of data will be analyzed in parallel and separately. Finally, we will integrate the data sets to identify areas of confirmation, complementation or discordance. Results: The research protocol and informed consent form were approved by the Medical Ethics Committee of the First Affiliated Hospital of Henan University of Science and Technology (2024-03-K171). Participant recruitment began in Sep 2024. As of April 2025, the data collection for T0 (prechemotherapy) was successfully completed, with a total of 270 patients enrolled in the study. At T1 (the third cycle of chemotherapy), follow-up assessments have been conducted for 157 participants. To date, 8 patients have been lost to follow-up due to various reasons, including 4 deaths, 2 refusals to continue participation, and 2 transfers to other medical facilities. Additionally, the data collection at T2 (end of chemotherapy) has been finalized for 78 patients. Data analysis is scheduled to begin in October 2025, with the results anticipated to be published in January 2026. Conclusions: As a pilot trial, the research could offer healthcare professionals dynamic insights into frailty progression and facilitate the early identification and intervention of high-risk populations through systematic screening of contributing factors, thereby preventing the onset of frailty. Clinical Trial: ChiCTR2500097921
Background: Across populations, risky drinking has been demonstrated to increase HIV risk behaviors. This is of special concern for sexually minoritized cisgender men and transgender (SMMT) young adul...
Background: Across populations, risky drinking has been demonstrated to increase HIV risk behaviors. This is of special concern for sexually minoritized cisgender men and transgender (SMMT) young adults (aged 18-34), who report greater incidence of hazardous drinking (as defined by AUDIT-C criteria) and HIV compared to their heterosexual and/or cisgender peers. Objective: This study examined alcohol perceptions, patterns of use, and the role that anti-LGBTQ+ (lesbian, gay, bisexual, transgender, queer) policies and discrimination played in alcohol risk behaviors for SMMT individuals. Results were used to inform development of an alcohol reduction intervention for this population. Methods: A qualitative study was conducted with data collected via four focus groups and one in-depth interview among young adult SMMT individuals in the United States from April-June 2023 (n=22). Participants were grouped according to SMMT identity: cisgender men, transgender men, transgender women, and nonbinary individuals. Transcripts were analyzed using codebook thematic analysis. Results: Alcohol use was described as a way to navigate belonging, social connection, and identity expression within LGBTQ+ contexts. Alcohol was viewed as a mainstay of LGBTQ+ spaces, with many using it as a social lubricant and coping mechanism for LGBTQ+ related stress, as well as for relaxation and having fun. Drinking intensity was often tied to an individual’s comfort with their evolving SMMT identity, with drinking being higher in earlier stages of exploration. The consequences of drinking discussed by participants included impaired decision-making and negative effects on mental and physical health. Anti-LGBTQ+ laws and policies were seen as contributing to the further stigmatization of SMMT individuals and hazardous use of alcohol was used as a means of escape and coping. Conclusions: Alcohol use among SMMT is an important aspect of negotiating identity within different social settings and coping with stigma. Findings have valuable implications for tailoring alcohol reduction interventions for SMMT young adults as they encounter stressors in real-time.
Background: The burden of paralytic ileus (PI) in the intensive care unit (ICU) remains high, and the Charlson Comorbidity Index (CCI) is strongly associated with the prognosis of several acute and ch...
Background: The burden of paralytic ileus (PI) in the intensive care unit (ICU) remains high, and the Charlson Comorbidity Index (CCI) is strongly associated with the prognosis of several acute and chronic diseases. However, there is no literature on the clinical value of CCI as a prognostic assessment tool for critically ill patients with PI in the ICU. Objective: The aim of this study was to investigate the relationship between CCI and clinical prognosis in critically ill patients with PI. Methods: In this study, data from the Critical Care Medical Information Marketplace IV 2.2 database were used to determine the optimal cutoff value of CCI for predicting mortality in patients with PI using receiver operating characteristic (ROC) curves, and the relationship between CCI and mortality was evaluated using Cox regression and restricted cubic spline analysis. A machine learning (ML) prediction model was then constructed to predict hospital mortality by combining CCI and other clinical characteristics. Results: The study included 863 patients with PI (median age 65.4 years [interquartile range 54.6-75.5 years], 66.6% male). The ROC curve identified an optimal cut-off value of 4.5 for CCI. Multivariate Cox regression analysis showed that compared to the lowest CCI quartile, patients with elevated CCI levels were more likely to have elevated hospital (Q4: HR 2.447, 95% CI 1.210-4.951), 28-day (Q4: HR 3. 891, 95% CI 1.956-7.740) and 90-day (Q4: HR 3.994, 95% CI 2.224-7.173) all-cause mortality were significantly associated with elevated CCI levels; however, the association with ICU mortality (Q4: HR 1.892, 95% CI 0.653-5.480) was weak. Among the 11 ML models, the LightGBM model performed best, with internal validation results showing an area under the curve of 0.811, a G-mean of 0.670, and an F1 score of 0.895. Conclusions: The CCI is an important predictor of hospital, 28-day, and 90-day all-cause mortality in critically ill patients with PI, and the optimal threshold is 4.5. ML models including the CCI show high accuracy in predicting hospital mortality, and the CCI occupies an important position in the model. This suggests that the CCI helps to identify high-risk patients, supports clinical decision making, and improves prognosis. Clinical Trial: NO
Background: Virtual reality (VR) is increasingly applied in rehabilitation training. Flow experience, a critical factor for enhancing user engagement and training efficacy, exhibits age-related differ...
Background: Virtual reality (VR) is increasingly applied in rehabilitation training. Flow experience, a critical factor for enhancing user engagement and training efficacy, exhibits age-related differences that are essential for designing elderly-friendly rehabilitation tasks. However, current VR rehabilitation systems often overlook age-related subjective experience disparities, leading to insufficient engagement among older adults. Objective: This study aims to explore differences in flow experience between younger and older adults during identical VR rehabilitation tasks and provide empirical evidence for designing personalized elderly rehabilitation programs. Methods: We recruited 21 older adults (mean age: 63.00 ± 6.64 years, 10 males) and 19 younger adults (mean age: 24.68 ± 1.16 years, 9 males). Participants performed the "Space Pop" task in Kinect Adventures (simulating limb coordination training) using VR. Flow experience was measured using the Chinese version of the Flow State Scale-2 (CFSS-2). Group differences were analyzed via Wilcoxon rank-sum tests. Results: Older adults exhibited significantly lower overall flow experience than younger adults (p < 0.001, d = 1.45), with significant differences in the dimensions of "challenge-skill balance" (p < 0.001), "clear goals" (p = 0.044), "sense of control" (p < 0.001), and "loss of self-consciousness" (p = 0.048). Other dimensions (e.g., concentration, time transformation) showed no statistical differences. Conclusions: Age significantly impacts flow experience in VR rehabilitation tasks. Tailoring designs through dynamic difficulty adjustment, intuitive goal cues, and reduced motor demands can enhance older adults’ control, immersion, and active participation, thereby improving health outcomes.
Background: Patient safety remains a global priority, with preventable adverse events—often caused by communication failures among healthcare professionals—posing serious risks. Interprofessional...
Background: Patient safety remains a global priority, with preventable adverse events—often caused by communication failures among healthcare professionals—posing serious risks. Interprofessional education (IPE) is a promising strategy to improve collaboration and communication, thereby enhancing care quality and patient outcomes. While IPE has been widely studied in student populations, limited evidence exists regarding its implementation and effectiveness for licensed rehabilitation professionals such as physical therapists (PTs), occupational therapists (OTs), and speech-language pathologists (SLPs). Objective: This scoping review aimed to comprehensively map the implementation, content, and effects of interprofessional education (IPE) targeting groups including licensed physical therapists (PTs), occupational therapists (OTs), and speech-language pathologists (SLPs). Methods: This scoping review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping review guidelines. Searches were performed using PubMed, Web of Science, CINAHL, MEDLINE, and ERIC databases, targeting studies published up to March 2024. The study population consisted of licensed PTs, OTs, and SLPs. Regarding concept, we targeted studies in which IPE was provided to groups with at least one licensed PT, OT, or SLP. Regarding context, we included studies reporting the effects of IPE in clinical settings. Controlled vocabulary (e.g., MeSH) for terms such as IPE, PT, OT, and SLP was used to develop the search strategy. Eight reviewers extracted data and identified eligible studies. Results: Of the 3,389 records identified, eight were included. Mapping revealed that IPE implementation primarily involved lectures, discussions, and team-based practices. The content covered theories and concepts, treatment, and workplace problem-solving. Regarding effects, the results demonstrated that IPE improved role understanding, collaboration skills, knowledge, and confidence in the long term. However, simulation training did not improve interprofessional attitudes or network expansion. Conclusions: IPE targeting licensed PTs, OTs, and SLPs was structured in a way that combined multiple implementation methods to enable comprehensive learning, with the content adjusted to meet participant needs. Future studies should consider systematic reviews and meta-analyses to identify recommended combinations of IPE implementation and content. Clinical Trial: Not applicable.
Background: Implementing new technologies in healthcare settings is often a complex and challenging process. Virtual reality (VR) has demonstrated promising results in terms of feasibility, acceptabil...
Background: Implementing new technologies in healthcare settings is often a complex and challenging process. Virtual reality (VR) has demonstrated promising results in terms of feasibility, acceptability, and effectiveness across various health conditions. However, little research has been done on patients’ acceptance of VR technology in psychiatric care. Objective: This study aimed to explore patients’ experiences of being offered the use of a virtual calm room when feeling anxious or worried in a psychiatric inpatient setting. Methods: A mixed-methods design was employed, with a qualitative → quantitative (QUAL → QUAN) approach. Data were gathered through individual interviews (n = 10) and a three-item rating scale (n = 59). The qualitative findings were then validated within a larger population using the quantitative data. Results: The majority of participants reported being satisfied with the option of using VR. Their initial impressions of the virtual calm room were that it seemed like a creative and stimulating environment that could potentially have a positive impact on them. They expected the VR experience to enhance their feelings of relaxation and concentration. The participants highlighted human interaction as a particularly valuable aspect to consider when implementing VR, emphasizing its role in enhancing the overall experience and ensuring a sense of connection and support throughout the process. Participants reported no significant difficulties in using the VR technology. They expressed high willingness to use the virtual calm room again in future and viewed the method as modern and innovative. Conclusions: The qualitative findings highlighted patients’ openness to innovative methods for enhancing their engagement in the psychiatric inpatient setting. Patients expressed a desire for increased availability of the virtual calm room. However, maintaining a balance between innovative technologies and human support is crucial for the successful implementation of such methods. Quantitative results demonstrated high acceptance of the option of using the virtual calm room, with no significant difficulties reported.
Background: Mental health conditions account for significant distress, burden, and societal costs. Despite efforts to implement evidence-based practices, access to high quality mental health treatment...
Background: Mental health conditions account for significant distress, burden, and societal costs. Despite efforts to implement evidence-based practices, access to high quality mental health treatment in general practice remains limited, and clinical outcomes sub-optimal. Measurement-based care (MBC) is a transtheoretical and transdiagnostic strategy that has the potential, when implemented effectively, to improve the quality of care. Digital tools can also support clinicians by alleviating administrative tasks and providing in-the-moment performance data and clinical decision support. In this study, we examine the clinical outcomes of a technology-enabled psychotherapy practice, where clinicians are supported by a suite of innovations including an MBC platform, clinical decision support tools, and tools designed to alleviate administrative burden. Objective: The current study examines client retention and depression and anxiety outcomes within a technology enabled psychotherapy practice. Methods: This retrospective cohort study examines 2,984 adults who initiated mental health treatment with Two Chairs, a hybrid technology enabled behavioral health provider, between January 1 to June 30, 2024. Rates of reliable change, recovery, remission, and magnitude and trajectory of symptom change in depression and anxiety symptoms were assessed using the PHQ-9 and GAD-7. Results: The population demonstrated high rates of retention in care (89.9%), as well as high rates of MBC survey completion (96.3%). From baseline to the 12th session, patients showed significant symptom improvements in depression and anxiety, achieving high rates of reliable improvement (65.8%) and recovery (53.2%). Aggregate clinical outcomes continued to improve up to the point of termination. Pre to post-treatment effect sizes were large (all Cohen’s d’s > 0.9). Conclusions: This study demonstrates how technology-enabled measurement-based care and clinical decision support systems may drive high quality patient outcomes in mental health. Implications for healthcare costs and value-based payment models are discussed.
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: Isolated premature thelarche (IPT) is characterized by early breast development in girls under 8 years old without other signs of puberty. Zhibai Dihuang Ointment Prescription, a tradition...
Background: Isolated premature thelarche (IPT) is characterized by early breast development in girls under 8 years old without other signs of puberty. Zhibai Dihuang Ointment Prescription, a traditional Chinese medicine (TCM) formulation, has been proposed as an alternative. Objective: This study aims to explore parents' perceptions of using this intervention for treating IPT in their children. Methods: Semi-structured individual interviews were conducted online with 14 parents of children diagnosed with IPT who had been treated with Zhibai Dihuang Ointment Prescription for over six months. Participants were recruited through purposive sampling. Interviews were audio-recorded, transcribed verbatim, and analyzed using template analysis. NVivo 12 software was used to facilitate data. Results: Three main themes emerged: (1) facilitators of Zhibai Dihuang Ointment Prescription for IPT, (2) barriers of Zhibai Dihuang Ointment Prescription for IPT, and (3) parental demands on Zhibai Dihuang Ointment Prescription for IPT. Facilitators included: (a) positive impacts on children and parents and (b) good acceptance among children and parents. Barriers included (a) limitations of the use of Zhibai Dihuang Ointment Prescription and (b) limitations in medical resources. Parental demands focused on (a) improvements in medication experience and (b) improvements in hospitals’ medical services. Conclusions: Zhibai Dihuang Ointment Prescription positively impacts children's development and family well-being. However, challenges like bitter taste, long treatment periods, and occasional side effects affect adherence. Improved healthcare access and patient-centered approaches are needed. Future quantitative and qualitative research are needed to evaluate its effects and understand patient experiences.
Background: Mobile health (mHealth) technologies show promise in addressing suboptimal anticoagulation adherence among venous thromboembolism (VTE) patients Objective: To evaluate the impact of a mobi...
Background: Mobile health (mHealth) technologies show promise in addressing suboptimal anticoagulation adherence among venous thromboembolism (VTE) patients Objective: To evaluate the impact of a mobile VTE application (mVTEA) on thromboprophylaxis adherence in VTE or moderate-to-high-risk patients. Methods: This single-center pilot study enrolled 88 patients at the Chinese PLA General Hospital (August–December 2023). Participants used mVTEA for automated medication reminders and self-management. Adherence was assessed using the Morisky Medication Adherence Scale-8 (MMAS-8) and Beliefs about Medicines Questionnaire-Specific (BMQ-Specific). Real-time adherence data were analyzed at 1 month (Trial registration: ChiCTR2200063206). Results: Among 45 completers (age 60.8±15.2 years; 35.6% female), baseline adherence was suboptimal (good: 28.9%; moderate/poor: 71.1%). Primary non-adherence drivers included forgetfulness (Q2: 0.69±0.47) and premature discontinuation (Q6: 0.78±0.42). BMQ-Specific revealed higher necessity than concern scores (17.58±3.12 vs. 14.58±3.34, p<0.001). At 1-month follow-up, 100% achieved perfect adherence, with 80% completing mVTEA check-ins. Patients utilizing check-in features demonstrated superior necessity-concern differentials (NCD>0: 80.6% vs. 0%, p<0.001). No adverse events occurred. Conclusions: mVTEA significantly improved short-term anticoagulation adherence through behavioral nudges and real-time monitoring. Individualized patient education may further optimize outcomes. Clinical Trial: ChiCTR2200063206
Background: Febrile seizures, although typically benign, can cause significant emotional distress for parents. Their diverse etiological risk factors underscore the need for further research. Ecologic...
Background: Febrile seizures, although typically benign, can cause significant emotional distress for parents. Their diverse etiological risk factors underscore the need for further research. Ecological Momentary Assessment (EMA) offers a cost-effective and timely method for real-time data collection. The FeverApp, an EMA-based registry for fever management, enables parents to document febrile seizures as they occur. Objective: This study systematically evaluates febrile seizure records from the FeverApp registry to assess their characteristics and explore the clinical implications of the findings. By providing real-world data on seizure management, this research demonstrates the potential of app-based EMA in pediatric care. Additionally, it offers insights for targeted interventions and improved febrile seizure management. Methods: Parents descriptions of 226 seizures belonging to 161 children were qualitatively analysed. Group differences in quantitative data were assessed through matched-pair sampling, comparing 114 children. Statistical methods were tailored to the nature of the respective variables, which included prevalence, age, gender, health and febrile history, fever management, temperature, well-being, and parental confidence. Results: Qualitative analyses provided detailed descriptions of seizure symptoms, seizure duration, and seizure management practices. Additionally, the data revealed a high rate of emergency consultations related to febrile seizures. However, there was underreporting of febrile seizures within the FeverApp, with a reported incidence of only 0.4% among febrile children. In a matched sample controlled for gender and age, significant differences were observed between febrile children with and without febrile seizures in several parameters, including maximum recorded temperature (P < .001), prevalence of chronic diseases (P = 0.004), parental confidence (P = 0.014), and frequency of emergency consultations (P < .001). Conclusions: This study offers valuable insights into the characteristics, temporal dynamics, management strategies, and parental responses to febrile seizures in children. Despite the limitation of potential underreporting in an EMA-based registry, the findings highlight the critical importance of parental education and support in managing febrile seizures. Enhancing these areas has the potential to reduce unnecessary medical consultations and improve the overall care of affected children. Furthermore, integrating improvements in the FeverApp's education and documentation system regarding febrile seizures could facilitate better management and support future research efforts. Clinical Trial: DRKS00016591
Background: Nursing is a stressful and threatening occupation, and nurses face different stressors and risks during their professional practice, such as the coronavirus disease 2019 (COVID-19) pandemi...
Background: Nursing is a stressful and threatening occupation, and nurses face different stressors and risks during their professional practice, such as the coronavirus disease 2019 (COVID-19) pandemic. Therefore, they need great self-care ability to improve and protect their health. Spiritual self-care (SSC) is one of the main aspects of self-care. However, there is limited scientific evidence about the process of SSC formation among nurses. The present study will be conducted to develop the theory of Nurses’ SSC in Biological Events and strategies to improve nurses’ SSC in biological events. Objective: The present study will be conducted to develop the theory of Nurses’ SSC in Biological Events and strategies to improve nurses’ SSC in biological events. Methods: This multi-methods study will be conducted using the grounded theory method, Systematic Scoping Review, and the Delphi technique. Participants will be hospital nurses with experience in patient care provision during the COVID-19 pandemic and will be selected through purposeful and theoretical sampling. Data will be collected through semi-structured interviews and will be analyzed through Corbin and Strauss’s method. Then, a Systematic Scoping Review will be conducted to determine the experiences of nurses in other countries. The findings of the grounded theory study and Systematic Scoping Review will be provided to a panel of experts, and their comments will be gathered to develop the best strategies to improve nurses' SSC in the form of a policy brief. Results: The findings of this study will be the theory of Nurses’ SSC in Biological Events and a policy brief containing strategies to improve nurses’ SSC in biological events. Conclusions: The findings of this study can be used in nursing practice, education, and research to improve nurses’ SSC in biological events.
Background: Osteoarthritis (OA) is a chronic degenerative joint condition and is the 15th major cause of disability worldwide. Family physicians play a significant role in managing these patients; the...
Background: Osteoarthritis (OA) is a chronic degenerative joint condition and is the 15th major cause of disability worldwide. Family physicians play a significant role in managing these patients; their up-to-date knowledge is essential for evidence-based management. Objective: This study assesses family physicians’ knowledge, attitude, and practice toward OA management. Furthermore, it explores knowledge gaps and discrepancies in practice and compares them with similar studies in the Arabian Peninsula. Methods: We conducted a cross-sectional online survey at Primary Healthcare Corporation (PHCC), Qatar. We sent a targeted online survey link via PHCC intranet email to 724 family physicians working across twenty-eight health centers in Qatar. Results: About 100 family physicians responded to the survey. Out of 100, 75 (75%) were male, 59 out of 100 (59%) were consultants, and the average age of respondents was 48 (SD 7.1). Overall knowledge of family physicians was 76.7%, exhibiting a positive attitude and good practice. A substantial majority of family physicians, 78 out of 100 (78%), acknowledged that OA adversely affects patients’ mental well-being, leading to anxiety and concern. 75 out of 100 (75%) of the participants believed they had adequate training to manage OA. 88 out of 100 (88%) family physicians frequently recommended non-pharmacological management approaches, particularly weight loss. Oral non-steroidal anti-inflammatory drugs (NSAIDs) were offered (75%) most of the time by general practitioners compared to specialists (16.7%) (P=.019). Notably, female physicians exhibited significantly higher utilization rates of pharmacological treatments, which include topical capsicum (P=.013), topical NSAIDs (P=.048), and oral NSAIDs (P=.049), and non-pharmacological treatment like thermotherapy (P=.011). Conclusions: Overall, this study found that PHCC family physicians’ knowledge, attitude, and practice in managing OA were good. However, targeted educational interventions are required, along with professional development programs, to promote evidence-based practices and address gender disparities in prescribing. Future research is necessary to delve deeper into the factors that contribute to the existing gaps in prescribing behavior between male and female physicians. Enhancing OA management further can lead to better patient outcomes and improved quality of care.
Background: Effective management of cardiometabolic conditions requires sustained positive nutrition habits, often hindered by complex and individualized barriers. Direct human management is simply no...
Background: Effective management of cardiometabolic conditions requires sustained positive nutrition habits, often hindered by complex and individualized barriers. Direct human management is simply not scalable, while deterministic automated approaches to nutrition coaching may lack the personalization needed to address these diverse challenges. Objective: We report the development and validation of a novel large language model (LLM)-powered agentic workflow designed to provide personalized nutrition coaching by directly identifying and mitigating patient-specific barriers. Methods: We used behavioral science principles to create a comprehensive workflow that can map nutrition-related barriers to corresponding evidence-based strategies. First, a specialized LLM agent intentionally probes for and identifies root causes of a patient’s dietary struggles. Subsequently, a separate LLM agent delivers tailored tactics designed to overcome those specific barriers. We conducted a user study with individuals with cardiometabolic conditions (N=16) to inform our workflow design and then validated our approach through an additional user study (n=6). We also conducted a large-scale simulation study, grounding on real patient vignettes and expert-validated metrics, where human experts evaluated the system’s performance across multiple scenarios and domains. Results: In our user study, the system accurately identified barriers and provided personalized guidance. Five out of 6 participants agreed that the LLM agent helped them recognize obstacles preventing them from being healthier, and all participants strongly agreed that the advice felt personalized to their situation. In our simulation study, experts agreed that the LLM agent accurately identified primary barriers in more than 90% of cases. Additionally, experts determined that the workflow delivered personalized and actionable tactics empathetically, with average ratings of 4.17-4.79 on a 5-point Likert scale. Conclusions: Our findings demonstrate the potential of this LLM-powered agentic workflow to improve nutrition coaching by providing personalized, scalable, and behaviorally-informed interventions. Clinical Trial: NA
Background: The global incidence of spinal cord injury (SCI) is between 10 and 80 new cases per million people each year, with more traumatic injuries occurring than non-traumatic. This equates to bet...
Background: The global incidence of spinal cord injury (SCI) is between 10 and 80 new cases per million people each year, with more traumatic injuries occurring than non-traumatic. This equates to between 250,000 and 500,000 injuries worldwide, per year. In the UK it is estimated that 4400 people per year sustain a SCI. People with tetraplegia report upper limb function as their highest priority for improvement after SCI. Using immersive virtual reality (VR) headsets, physical rehabilitation exercises can be completed in engaging digital environments. Immersive VR therefore has the potential to increase the amount of therapy undertaken, leading to improvements in arm and hand function. There is little evidence supporting immersive VR as exercise in SCI, especially while SCI patients are undergoing acute rehabilitation. This study recruited people with tetraplegia and therapists to establish the design direction for a VR-based upper limb exercise platform. In spinal cord injury research, co-design of new interventions is not a widely adopted approach, yet people with SCI want to contribute with their expert knowledge on their experiences of SCI. Objective: To explore the lived experiences of people with tetraplegia and specialist SCI therapists related to acute upper limb rehabilitation and to co-design immersive virtual reality-based upper limb activities. Methods: Seven focus groups were conducted online using Microsoft Teams: four with people with tetraplegia (n = 15, age range 36-65 years) and three with occupational therapists and physiotherapists specialising in spinal cord injury rehabilitation (n = 11). Participants were asked to discuss their experiences and expertise about acute SCI upper limb rehabilitation and their opinions on the use of VR for upper limb rehabilitation. The transcripts were analysed using content analysis enabling the proposition of design characteristics of a VR-based intervention for upper limb exercise. Results: The study identified five major themes describing the clinical features, treatment, and recovery of spinal cord injured people during the acute stage of SCI, and suggestions for the design of a VR intervention in treating the upper limbs following SCI. The results highlighted what motivates people with SCI to participate in therapy and how these motivators could be encouraged and maintained using VR. These findings can be used to design accessible VR applications for use by people with SCI and their therapists. They can also contribute to the better understanding of the advantages of using VR as an adjunct to upper limb rehabilitation, as well as features of VR-based interventions to avoid. Conclusions: The themes identified in this study allow the elicitation of software requirements for a bespoke immersive VR platform for upper limb rehabilitation following spinal cord injury. Additionally, participants used their expertise to suggest factors that would enable the development of a usable and effective intervention as well as identifying potential pitfalls and software features to avoid during the intervention development.
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
Among the countless decisions healthcare providers make daily, many clinical scenarios do not have clear guidelines, despite a recent shift towards the practice of evidence-based medicine. Even in cli...
Among the countless decisions healthcare providers make daily, many clinical scenarios do not have clear guidelines, despite a recent shift towards the practice of evidence-based medicine. Even in clinical scenarios where guidelines do exist, these guidelines do not universally recommend one treatment option over others. As a result, the limitations of existing guidelines presumably create an inherent variability in provider decision-making and the corresponding distribution of provider behavioral variability in a clinical scenario, and such variability differs across clinical scenarios. We define this variability as a marker of provider uncertainty, where scenarios with a wide distribution of provider behaviors have more uncertainty than scenarios with a narrower provider behavior distribution. We propose four exploratory analyses of provider uncertainty: (1) field-wide overview; (2) subgroup analysis; (3) provider guideline adherence; and (4) pre-/post-intervention evaluation. We also propose that uncertainty analysis can also be used to help guide interventions in focusing on clinical decisions with the highest amounts of provider uncertainty and therefore the greatest opportunity to improve care.
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.
Background: Abstract (237 words)
The American Civil War has been commemorated with a great variety of monuments,
memorials, and markers. These monuments were erected for a variety of reasons, begi...
Background: Abstract (237 words)
The American Civil War has been commemorated with a great variety of monuments,
memorials, and markers. These monuments were erected for a variety of reasons, beginning with
memorialization of the fallen and later to honor aging veterans, commemoration of significant
anniversaries associated with the conflict, memorialization sites of conflict, and celebration of
the actions of military leaders. Sources reveal that during both the Jim Crow and Civil Rights
eras, many were erected as part of an organized propaganda campaign to terrorize African
American communities and distort the past by promoting a ‘Lost Cause’ narrative. Through
subsequent decades, to this day, complex and emotional narratives have surrounded interpretive
legacies of the Civil War. Instruments of commemoration, through both physical and digital intervention approaches, can be provocative and instructive, as the country deals with a slavery legacy and the commemorated objects and spaces surrounding Confederate inheritances.
Today, all of these potential factors and outcomes, with internationally relevance, are surrounded by swirls of social and political contention and controversy, including the remembering/forgetting dichotomies of cultural heritage. The modern dilemma turns on the question: In today’s new era of social justice, are these monuments primarily symbols of oppression, or can we see them, in select cases, alternatively as sites of conscience and reflection encompassing more inclusive conversations about commemoration? What we save or destroy and assign as the ultimate public value of these monuments rests with how we answer this question. Objective: I describe monuments as symbols in the “Lost Cause” narrative and their place in enduring Confederate legacies. I make the case, and offer documented examples, that remnants of the monuments, such as the “decorated” pedestals, if not the original towering statues themselves, should be left in place as sites of reflection that can be socially useful in public interpretation as disruptions of space, creating disturbances of vision that can be provocative and didactic. I argue that we should see at least some of them as sculptural works of art that invite interpretations of aesthetic and artistic value. I point out how, today, these internationally relevant factors and outcomes of retention vs. removal are engulfed in swirls of social and political contention and controversy within processes of remembering and forgetting and changing public dialogues. Methods: This article addresses several elements within the purview of the Journal: questions of contemporary society, diversity of opinion, recognition of complexity, subject matter of interest to non-specialists, international relevancy, and history. Drawing from the testimony of scholars and artists, I address the contemporary conceptual landscape of approaches to the presentation and evolving participatory narratives of Confederate monuments that range from absolute expungement and removal to more restrained responses such as in situ re-contextualization, removal to museums, and preservation-in-place. In a new era of social justice surrounding the aftermath of dramatic events such as the 2015 Charleston shooting, the 2017 Charlotteville riot, and the murder of George Floyd, should we see them as symbols of oppression, inviting expungement, or selectively as sites of conscience and reflection, inviting various forms of re-interpretation of tangible and intangible relationships?
I describe monuments as symbols in the “Lost Cause” narrative and their place in enduring Confederate legacies. I make the case, and offer documented examples, that remnants of the monuments, such as the “decorated” pedestals, if not the original towering statues themselves, should be left in place as sites of reflection that can be socially useful in public interpretation as disruptions of space, creating disturbances of vision that can be provocative and didactic. I argue that we should see at least some of them as sculptural works of art that invite interpretations of aesthetic and artistic value. I point out how, today, these internationally relevant factors and outcomes of retention vs. removal are engulfed in swirls of social and political contention and controversy within processes of remembering and forgetting and changing public dialogues. Results: I argue that we should see at least some of them as sculptural works of art that invite interpretations of aesthetic and artistic value. I point out how, today, these internationally relevant factors and outcomes of retention vs. removal are engulfed in swirls of social and political contention and controversy within processes of remembering and forgetting and changing public dialogues. Conclusions: Today, all of these potential factors and outcomes, with internationally relevance, are surrounded by swirls of social and political contention and controversy, including the remembering/forgetting dichotomies of cultural heritage. The modern dilemma turns on the question: In today’s new era of social justice, are these monuments primarily symbols of oppression, or can we see them, in select cases, alternatively as sites of conscience and reflection encompassing more inclusive conversations about commemoration? What we save or destroy and assign as the ultimate public value of these monuments rests with how we answer this question.
