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Journal Description

JMIR Preprints contains 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!).

 

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    Editorials and Preprints Announcements

    Nov 11, 2015

    Peer-Review 2.0: Welcome to JMIR Preprints, an Open Peer-Review Marketplace for Scholarly Manuscripts

    Authors List:

    Abstract:

    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.

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  • Exploring the Influence of Urban Quality on Frailty, Nutritional Status, and Hematological/Biochemical Profile in Older Adults: Insights from Geospatial Approach

    From: JMIR Aging

    Date Submitted: Mar 21, 2025

    Open Peer Review Period: Apr 2, 2025 - May 28, 2025

    Background: Urban environments influence frailty through factors related to infrastructure for physical activity, social and medical support, and access to quality nutrition. Given the increasing agin...

    Background: Urban environments influence frailty through factors related to infrastructure for physical activity, social and medical support, and access to quality nutrition. Given the increasing aging population, understanding the link between urban quality, frailty, and metabolic health is crucial for effective public health and urban planning interventions. Objective: To investigate the impact of urban quality on frailty and its correlation with nutritional status and hematological/biochemical parameters using geospatial analysis. Methods: A cohort of 251 older adults (aged 65+) was studied. Frailty was assessed using the Frailty Trait Scale 5 (FTS-5), and nutritional status was determined using the Controlling Nutritional Status (CONUT) score. Hematological and biochemical parameters were evaluated in a subset of 70 participants by MINDRAY automatic equipment. A spatial analysis of frailty was conducted by incorporating GIS layers that mapped the distribution of urban facilities, including fruit and vegetable shops, senior centers, pharmacies, emergency health centers, parks and squares, community centers, and sports fields. Statistical analyses included t-tests, Mann-Whitney, ANOVA, and correlation analyses. Results: The prevalence of frailty was 17.5%. Frail individuals exhibited significantly higher BMI (31.5 ± 4.4 vs. 28.5 ± 4.5 kg/m²; p=0.0001). When comparing the upper (Q4) and lower (Q1) quartiles of urban quality, Q4 participants had higher FTS-5 scores (15.2 ± 7.4 vs. 11.8 ± 6.4; p=0.0334) and lower handgrip strength (19.1 ± 4.4 vs. 22.8 ± 7.3 kg; p=0.0059). Frail individuals resided significantly closer to emergency health centers (p<0.0001), family health centers (p<0.05), and sports fields (p<0.05). Additionally, bilirubin (Spearman R=0.3325, p=0.0049), serum iron (Spearman R=0.272, p=0.0272), transferrin saturation (Spearman R=0.2478, p=0.0386), RBC (Spearman R=0.2629, p=0.0303), and RDW (Spearman R=0.2391, p=0.0462) were positively correlated with urban quality. Frail participants also had higher CONUT scores (p=0.0323), which were positive correlated with urban quality (Spearman R=0.2513, p=0.0359). Conclusions: Urban quality significantly influences hematological parameters, nutritional status, and frailty. Frail individuals in areas with better urban quality exhibit lower handgrip strength, higher frailty scores, and greater proximity to emergency rooms, community health centers, and sports fields. This suggests compensatory behaviour to address increased healthcare needs. Urban planning and public health strategies should focus on creating age-friendly environments to prevent frailty and improve health outcomes.

  • Effectiveness of Anonymous, On-Demand, Real-time Moderated Peer Support in Medicaid-Plan-Sponsored Teens: A Retrospective Analysis of Emotional Relief and Sentiment Change

    From: JMIR Pediatrics and Parenting

    Date Submitted: Mar 31, 2025

    Open Peer Review Period: Apr 2, 2025 - May 28, 2025

    Background: Teens from low socioeconomic status (SES) households have a higher risk for emotional distress and less access to support. Emotional distress increases the risk of mental health and other...

    Background: Teens from low socioeconomic status (SES) households have a higher risk for emotional distress and less access to support. Emotional distress increases the risk of mental health and other downstream chronic conditions. Today, all teens, including those from low SES households use technology pervasively. Real-time moderated digital peer support presents an opportunity to connect low income teens to a safe, evidence-based support resource in real time. Objective: The current study focuses on Medicaid-plan-sponsored teens who were given no-cost access to a 24/7, on-demand, anonymous, real-time moderated digital peer support service to better understand the dynamics of how sentiment and emotional states changed throughout the chat conversations. Methods: Using OpenAI’s LLM model, GPT-4o-mini, employing a few-shot learning approach, 1005 conversations were evaluated for non-clinical emotional distress variables including sadness, stress, insecurity, loneliness, anger, and anxiety. Results: Consistent, statistically significant improvement was observed in all emotional states throughout the conversations, with the greatest reductions seen for anger (46.94%, Wilcoxon signed-rank test P = 2.265 × 10⁻¹⁷), loneliness (31.99%, P = 9.968 × 10⁻²⁰), and stress (31.02%, Wilcoxon signed-rank test P = 2.394 × 10⁻²⁵). There were also smaller reductions in anxiety, sadness, and insecurity over the course of the conversations and a corresponding improvement in overall sentiment (196.78% increase, Wilcoxon signed-rank test P = 1.954 × 10⁻¹⁹). Conclusions: Among a cohort of Medicaid-plan-sponsored teens, use of an anonymous, synchronous, real-time moderated digital peer support service was associated with significant reductions in sadness, stress, insecurity, loneliness, anger, and anxiety and a corresponding improvement in optimism by the end of the conversations. These marked reductions in distressing emotions continued as the conversations progressed, reinforcing the potential value of conversation-based engagement on emotional regulation and overall emotional well-being. Teens from low income households face higher incidence of mental health conditions. Digital peer support could be instrumental in easing such emotional distress and addressing the larger teen mental health crisis. Clinical Trial: N/A

  • "The Effectiveness of Virtual Reality and Augmented Reality in the Management of Chronic Musculoskeletal Disorders: A Systematic Review"

    From: JMIR Rehabilitation and Assistive Technologies

    Date Submitted: Mar 22, 2025

    Open Peer Review Period: Apr 2, 2025 - May 28, 2025

    Background: Chronic musculoskeletal disorders (CMDs), such as osteoarthritis, rheumatoid arthritis, and chronic lower back pain, are leading causes of disability and pose significant health and econom...

    Background: Chronic musculoskeletal disorders (CMDs), such as osteoarthritis, rheumatoid arthritis, and chronic lower back pain, are leading causes of disability and pose significant health and economic burdens worldwide. Traditional rehabilitation methods, including physical therapy and pharmacological treatments, often face challenges related to patient adherence and long-term effectiveness. Emerging technologies like virtual reality (VR) and augmented reality (AR) have been proposed as innovative rehabilitation tools to enhance patient engagement, reduce pain, and improve mobility. Objective: This systematic review evaluates the effectiveness of VR and AR in managing CMDs, focusing on their impact on pain relief, functional mobility, psychological well-being, and long-term rehabilitation outcomes. Methods: : A systematic search was conducted in PubMed, PEDro, Cochrane, and Scopus for randomized controlled trials (RCTs) investigating VR or AR interventions in CMD rehabilitation. The inclusion criteria were adult patients with CMDs, VR/AR-based interventions, and validated outcome measures assessing pain, kinesiophobia, disability, balance, or depression. Studies were evaluated for quality using the PEDro scale and the Downs and Black checklist Results: From 388 identified studies, 8 RCTs met the inclusion criteria, comprising 621 participants aged 18-75 years. The PEDro scale yielded an average study quality score of 6.75/10, with two studies classified as "excellent" (9/10), four as "good" (6-7/10), and one as "fair" (4/10). VR interventions significantly reduced pain intensity in CMD patients, with studies reporting improvements on the Visual Analog Scale (VAS) and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). AR-based rehabilitation demonstrated faster recovery times and enhanced functional mobility in post-surgical patients. Psychological benefits, including reduced anxiety and increased motivation, were also observed, particularly in immersive VR environments. However, methodological heterogeneity across studies limited direct comparisons, and no study directly compared AR and VR effectiveness. Conclusions: VR and AR offer promising alternatives to conventional rehabilitation for CMDs, demonstrating benefits in pain management, functional recovery, and psychological well-being. However, long-term effectiveness, cost-efficiency, and ethical considerations regarding data privacy remain underexplored. Future research should focus on conducting meta-analyses, long-term follow-ups, cost-effectiveness evaluations, and ethical framework development to facilitate clinical integration. With continued advancements, VR and AR have the potential to revolutionize musculoskeletal rehabilitation by providing personalized, engaging, and scalable treatment options. Clinical Trial: The a priori protocol for the review is published in the International Prospective Register of Systematic Reviews (PROSPERO): CRD42024589007.

  • Assessment of Readability and Comprehensibility of Online Resources on Biotinidase Deficiency: Cross-Sectional Content Analysis

    From: JMIR Formative Research

    Date Submitted: Mar 24, 2025

    Open Peer Review Period: Apr 2, 2025 - May 28, 2025

    Background: Biotinidase deficiency is a metabolic disorder that is included in newborn screening programmes. This condition prevents individuals from performing biotin metabolism properly and can lead...

    Background: Biotinidase deficiency is a metabolic disorder that is included in newborn screening programmes. This condition prevents individuals from performing biotin metabolism properly and can lead to serious health problems when left untreated. It is important that health resources are understandable and accessible for families to be informed about the disease and to be directed to the right treatment. Objective: This study evaluates the readability and understandability of online resources on biotinidase deficiency, a metabolic disorder included in newborn screening programs. The aim is to determine whether these materials meet health literacy standards. Methods: Fifty online documents were initially identified via Google searches using “biotinidase deficiency.” After excluding academic articles, duplicates, and inaccessible resources, 21 documents were analyzed. They were categorized as nonprofit (13) or private (8) based on domain extensions. Readability was assessed using Readable.io, providing Flesch Reading Ease scores. The Patient Education Materials Assessment Tool (PEMAT) was used to evaluate understandability and actionability, with scores averaged by four reviewers. Statistical analyses compared group differences. Results: Private articles had significantly higher Flesch Reading Ease scores, indicating more difficult readability (mean ± SD: 13.9 ± 2.2 vs. 10.7 ± 2.0; p = 0.002). PEMAT understanding (U) scores showed no significant difference between private and nonprofit articles (mean ± SD: 52.0 ± 10.5 vs. 42.3 ± 11.4; p = 0.060). Similarly, actionability (A) scores were not significantly different (mean ± SD: 29.1 ± 20.0 vs. 13.4 ± 18.0; p = 0.063). Articles with lower readability (levels D and E) had significantly lower actionability scores compared to higher readability articles (levels A to C). Conclusions: Most online biotinidase deficiency resources fail to meet health literacy standards, particularly in readability and actionability. Improving clarity and usability is essential to better support families managing this condition. The study emphasizes patient-centered approaches for creating effective health education materials.

  • A novel primary care planning informatics tool informed by data-driven multimorbidity grouping: User-centered design and feasibility testing

    From: JMIR Formative Research

    Date Submitted: Mar 27, 2025

    Open Peer Review Period: Apr 2, 2025 - May 28, 2025

    Background: Patients with multimorbidity have complex healthcare needs and are at high-risk for adverse health outcomes. Primary care teams need tools to effectively and proactively plan care for thes...

    Background: Patients with multimorbidity have complex healthcare needs and are at high-risk for adverse health outcomes. Primary care teams need tools to effectively and proactively plan care for these patients. We developed VET-PATHS (VETeran PAnel management Tool for High-risk Subgroups), a novel care planning informatics tool for complex primary care patients. VET-PATHS a) groups patients by chronic condition profile via latent class analysis of electronic health record (EHR) data, then b) jumpstarts care planning by suggesting ‘care steps’ based on data-driven high-priority care for the group, indicated as not receive by EHR. Objective: Iteratively adapt VET-PATHS with user input, then test feasibility and acceptability of tool use by frontline primary care teams for their empaneled high-risk patients. Methods: Three rounds of user-centered design sessions with 17 primary care providers and registered nurses were held at 5 sites from 2019-2021, for feedback on VET-PATHS layout, content, and user-interface. Feedback was summarized into 4 user experience domains (useful, desirable, credible, and usable), leading to progressively updated prototypes. After national tool release, we conducted a pilot intervention study in 2023-2024 with 6 primary care teams at 4 sites. Teams used VET-PATHS during asynchronous regular meetings. Tool use and resulting care plans were assessed by templated observation during meetings and post-pilot chart review. Individual qualitative interviews were analyzed by rapid template analysis for themes of feasibility, acceptability, and utility. Results: User-centered feedback led to updates in tool content, context (e.g., use in proactive panel management), targeting of users (e.g., focusing on primary care providers as the principal users), and layout of informational displays. Pilot intervention teams used VET-PATHS over 4-8 weekly team meetings (mean length, 24 min (range 16-49m)), in which they actively reviewed 80% (280/351) of empaneled high-risk patients visible in the tool. Tool use prompted teams to plan 127 new actions for 91 unique patients (33% of patients reviewed), and document >1 new care plans for 19% of patients reviewed. Common actions included requests to return to clinic (27%), referrals (20%), or vaccinations (19%). Of actions planned, 53 (42%) were received by patients. Four teams with general patient panels (n=11 interviews) described higher acceptability. Two ‘focused’ teams with smaller more homogenous patient panels, e.g. substance use disorder, (n=3 interviews) found care steps less useful. Teams described how VET-PATHS improved efficiency of care planning through automated patient grouping and identification of care gaps, and increased multidisciplinary role involvement. Conclusions: User-centered improvements to VET-PATHS were designed to help clinicians process and use complex information about patient multimorbidity to efficiently create new care plans. In subsequent production, VET-PATHS was acceptable and feasible to use by frontline primary care teams, particularly with larger, more heterogenous patient panels, and led to concrete changes to clinical care delivery. Clinical Trial: N/A

  • Safety and efficacy of aspirin and indobufen in the treatment of arteriosclerotic cardiovascular disease: a systematic review and meta-analysis

    From: Interactive Journal of Medical Research

    Date Submitted: Apr 1, 2025

    Open Peer Review Period: Apr 2, 2025 - May 28, 2025

    Background: The pathogenesis of atherosclerotic thrombosis primarily involves platelet activation and aggregation, making antiplatelet therapy the cornerstone of treatment for such diseases. Objective...

    Background: The pathogenesis of atherosclerotic thrombosis primarily involves platelet activation and aggregation, making antiplatelet therapy the cornerstone of treatment for such diseases. Objective: This meta-analysis aimed to compare the safety and efficacy of aspirin and indobufen in antiplatelet therapy for patients with arteriosclerotic cardiovascular disease. Methods: We searched the Cochrane Library, PubMed, EMBASE, Web of Science, and the Chinese Wanfang databases. The literature was screened according to predefined inclusion and exclusion criteria. Relative risk (RR) was used to assess the magnitude of risk associated with exposure. Results: Eighteen clinical trials with a total of 12981 patients were included in this study. Compared with aspirin, indobufen reduced the risk of (1) bleeding events (RR 0.54; 95% CI: 0.41–0.71; P < 0.0001), (2) BARC 2/3/5 bleeding (RR 0.50; 95% CI: 0.26–0.94; P = 0.03), (3) adverse cardiovascular events (RR 0.43; 95% CI: 0.30–0.61; P < 0.00001), and (4) myocardial infarction (RR 0.60; 95% CI: 0.41–0.89; P = 0.01). However, there were no significant differences between the two groups in terms of MACCEs, stroke, or cardiovascular mortality. Conclusions: Compared to aspirin, indobufen demonstrated better safety and was not inferior to aspirin in terms of efficacy, with superior results in some aspects. Further studies with larger sample sizes or longer follow-up periods may provide additional evidence. Clinical Trial: This study is registered with PROSPERO (CRD42024588250) and was conducted in accordance with the 2020 version of the PRISMA statement

  • Comparison of Multimodal Deep Learning Approaches for Predicting Clinical Deterioration in Ward Patients: An Observational Cohort Study

    From: Journal of Medical Internet Research

    Date Submitted: Apr 1, 2025

    Open Peer Review Period: Apr 1, 2025 - May 27, 2025

    Background: Implementing machine learning models to identify clinical deterioration on the wards is associated with improved outcomes. However, these models have high false positive rates and only use...

    Background: Implementing machine learning models to identify clinical deterioration on the wards is associated with improved outcomes. However, these models have high false positive rates and only use structured data. Objective: We aim to compare models with and without information from clinical notes for predicting deterioration. Methods: Adults admitted to the wards at the University of Chicago (development cohort) and University of Wisconsin-Madison (external validation cohort) were included. Predictors consisted of structured and unstructured variables extracted from notes as Concept Unique Identifiers (CUIs). We parameterized CUIs in five ways: Standard Tokenization (ST), ICD Rollup using Tokenization (ICDR-T), ICD Rollup using Binary Variables (ICDR-BV), CUIs as SapBERT Embeddings (SE), and CUI Clustering using SapBERT embeddings (CC). Each parameterization method combined with structured data and structured data-only were compared for predicting intensive care unit transfer or death in the next 24 hours using deep recurrent neural networks. Results: The study included 506,076 ward patients, 4.9% of whom experienced the outcome. The SE model achieved the highest AUPRC (0.208), followed by CC (0.199) and the structured-only model (0.199), ICDR-BV (0.194), ICDR-T (0.166), and ST (0.158). The CC and structured-only models achieved the highest AUROC (0.870), followed by ICDR-T (0.867), ICDR-BV (0.866), ST (0.860), and SE (0.859). Conclusions: A multimodal model combining structured data with embeddings using SapBERT had the highest AUPRC, but performance was similar between models with and without CUIs. The addition of CUIs from notes to structured data did not meaningfully improve model performance for predicting clinical deterioration.

  • Understanding experiences of and unmet needs in online searches for menopause information: a UK-wide exploratory survey

    From: Journal of Medical Internet Research

    Date Submitted: Apr 1, 2025

    Open Peer Review Period: Apr 1, 2025 - May 27, 2025

    Background: Menopause is a significant time in a woman’s life but only recently has there been open discussion about it in the media, workplaces, and in general society. With increasing frequency, w...

    Background: Menopause is a significant time in a woman’s life but only recently has there been open discussion about it in the media, workplaces, and in general society. With increasing frequency, women are choosing to use the internet to research topics related to the menopause. This makes it essential that online sources can provide safe, high-quality, and relevant information. Objective: This study aimed to investigate the current state of the online information landscape about the menopause from the perspective of information-seekers, exploring: (1) information-seeking behavior related to the perimenopause and menopause, and (2) perceptions of online resources for the menopause. Methods: A 10-15 minute online survey was conducted asking about the experience of the menopause and their use, and opinion of online resources specifically for the menopause. The survey was distributed via social media, email, and word-of-mouth. Quantitative data was explored using means and frequencies. Group differences between menopausal groups were analyzed using Chi-squared, Fisher’s Exact, or Kruskall-Wallis test as appropriate. Qualitative data was analyzed using data-driven thematic analysis. Results: Data from 627 participants were included in the analysis (early perimenopause: 27.27%, n=171/627; late perimenopause: 19.94%, n=125/627; post-menopause: 41.79%, n=262/627; surgical menopause: 11.00%, n=69/627). The majority of respondents had used the internet as a source of information (92.66%, n=581/627), with the internet being the first choice of information source 84.17% (n=489/627). The most commonly searched for information online was about menopause symptoms (82.44%, n=479/581), menopause treatment options (76.08%, n=442), and self-help tips or strategies (54.73%, n=318/581). The majority of participants trusted online information to some extent (98.09%, n=615/627), with a slightly lower proportion considering online information accurate to some extent (88.52%, n=555/627). The majority of participants found some but not all of the information they were looking for online (65.23%, n=379/581). Thematic analysis revealed 10 themes related to information quality and accessibility and sought after information (eg, symptom specifics, treatment, and non-formal management strategies). Analysis also indicated that information is lacking for several groups including those in medically induced or surgical menopause. Conclusions: The study showed that online informational resources are widely accessed and widely perceived as useful and trustworthy. Despite this, it is crucial that the quality of online information is evaluated especially considering the large number of users who rely on it as their first or only informational source. Online searches were usually performed to find information related to symptoms, treatment, and self-help recommendations. Thematic analysis reveals gaps in the provision of online information with certain groups such as those in the surgical menopause lacking easy access to relevant information.

  • Association Between Digital Isolation and Sleep Disorders in Older Adults: A Cross-Sectional and Longitudinal Study Using NHATS Data

    From: Journal of Medical Internet Research

    Date Submitted: Apr 1, 2025

    Open Peer Review Period: Apr 1, 2025 - May 27, 2025

    Background: As digital technology becomes increasingly embedded in daily life, digital isolation among older adults has become more pronounced. This isolation may restrict access to health information...

    Background: As digital technology becomes increasingly embedded in daily life, digital isolation among older adults has become more pronounced. This isolation may restrict access to health information and social support, potentially leading to poorer sleep quality. However, most existing studies on digital isolation and sleep disorders are cross-sectional, lacking longitudinal evidence to establish causality. Objective: This study aimed to investigate the association between digital isolation and sleep disorders in older adults using both cross-sectional and longitudinal designs, and to assess the impact of specific components of digital isolation on the risk of sleep disorders. Methods: We analyzed data from the National Health and Aging Trends Study (NHATS) collected from 2011 to 2022, including a discovery sample of 5,989 older adults and a validation sample of 3,443. Digital isolation was measured by the use of mobile phones, computers, email, and the internet, while sleep disorders were identified based on difficulties initiating or maintaining sleep and the use of sleep medication. Multivariable logistic regression and Cox proportional hazards models were employed for cross-sectional and longitudinal analyses, respectively. Results: Cross-sectional analyses revealed a higher prevalence of sleep disorders among those with high digital isolation (discovery: 67.03% vs. 59.06%, OR = 1.23, P < 0.001; validation: 70.10% vs. 61.38%, OR = 1.22, P = 0.033). In longitudinal analyses, high digital isolation was associated with an increased risk of sleep disorders in the discovery (HR = 1.21, P = 0.006) and pooled samples (HR = 1.17, P = 0.005), but the association was not statistically significant in the validation sample after adjustment (HR = 1.11, P = 0.298). Conclusions: Digital isolation is significantly associated with sleep disorders among older adults, particularly in cross-sectional analyses, while longitudinal findings provide partial support for this association. The non-significant result observed in the validation sample may reflect sample heterogeneity, and suggests that mental health may mediate this relationship. Future interventions should address mental health to help mitigate the negative impact of digital isolation on sleep.

  • Harnessing Data Warehousing for Precision in Off-Label Prescription Detection in Psychiatry: Insights from PSYHAMM

    From: Journal of Medical Internet Research

    Date Submitted: Apr 1, 2025

    Open Peer Review Period: Apr 1, 2025 - May 27, 2025

    Background: Off-label drug prescribing is prevalent in medicine, including psychiatry, often due to unmet therapeutic needs and failures of standard treatments. The PSYHAMM project, funded by the Fren...

    Background: Off-label drug prescribing is prevalent in medicine, including psychiatry, often due to unmet therapeutic needs and failures of standard treatments. The PSYHAMM project, funded by the French Research Agency, investigates these practices. To support this research, a clinical data warehouse with advanced data analysis tools has been developed and deployed. This system integrates both structured and unstructured data from electronic health records, facilitating comprehensive data analysis. The goal is to improve understanding, regulation, and safety of off-label drug use in psychiatry by providing insights into prescribing patterns and their impacts, ultimately contributing to better clinical guidelines and patient care. Objective: This study aims to evaluate the effectiveness of a clinical data warehouse in detecting off-label prescriptions in psychiatry. Methods: The PSYHAMM data analysis involved a retrospective study of pathology-medication pairs to evaluate the diagnostic accuracy of a computerized system. This system was compared with manual checks performed by a psychiatrist. The evaluation process included verifying if the condition identified by PSYHAMM was documented in the medical record, assessing diagnostic accuracy with tolerance for schizoaffective disorders, and ensuring the identified treatment was current or prescribed in the past. Precision was measured as the number of relevant documents retrieved divided by the total number of documents proposed. Logistic regression analysis was conducted to determine the impact of precise diagnosis, broad diagnosis, and identified treatment on detecting off-label situations. Results: The study analyzed 197 records, identifying 14 unique drug-pathology combinations. Bipolar disorder treated with sodium valproate represented the majority of cases (54.8%), followed by schizophrenia treated with sodium valproate (18.8%). The overall precision for detecting off-label situations was 51.3%. The precise diagnosis achieved a precision of 75.6%, while the broad diagnosis showed a higher precision of 84.8%. The identified treatment had a precision of 61.4% and the highest impact on detecting off-label situations (coefficient 6.62, P<.001). The primary challenge was temporal discrepancies, such as distinguishing between acute and chronic conditions, which led to incorrect classification in 48.7% of cases. Conclusions: The PSYHAMM project demonstrates the potential of automated systems to accurately identify off-label prescriptions in psychiatry. Despite the promising results, challenges such as temporal discrepancies and data completeness need to be addressed. The findings underscore the importance of continuous refinement and expansion of automated systems, incorporating additional data sources and advanced analytics, to enhance their reliability and effectiveness in clinical practice. Future research should focus on integrating real-time data analytics and expanding to multiple institutions to improve the accuracy and utility of off-label detection systems.

  • Machine Learning-Augmented Surveillance of Surgical Site Infections

    From: JMIR Formative Research

    Date Submitted: Apr 1, 2025

    Open Peer Review Period: Apr 1, 2025 - May 27, 2025

    Background: Surgical Site Infection (SSI) is one of the most common healthcare-associated infections, comprising nearly 20% of all Healthcare-Associated Infections (HAI) in hospitalized patients. SSIs...

    Background: Surgical Site Infection (SSI) is one of the most common healthcare-associated infections, comprising nearly 20% of all Healthcare-Associated Infections (HAI) in hospitalized patients. SSIs contribute to increased hospital length of stay, readmission, and healthcare costs, with an associated mortality rate twice that of non-infected patients. Objective: To develop machine learning models to predict potential SSI cases following colon surgeries, thereby improving the efficiency of SSI surveillance and enabling healthcare professionals to better prioritize patient care. Methods: Data was extracted from the EPIC Electronic Health Record system at a single academic center focusing on colon surgery patients between 2018 and 2023. The dataset included structured features such as demographics, medications, and vital signs, as well as unstructured clinical notes processed using natural language processing techniques. Logistic Regression, Random Forest, and XGBoost models were developed and trained to predict SSI risk. Cost-sensitive learning and Synthetic Minority Over-sampling Technique (SMOTE) were applied to handle the imbalanced dataset. Model evaluation was conducted using performance metrics including accuracy, precision, recall, and Area Under the Receiver Operating Characteristic curve (AUC-ROC). Results: From a cohort of 1508 patients, 66 (4.4%) developed SSIs. The XGBoost model demonstrated the best overall performance with precision of 50%, recall of 38%, and an AUC-ROC score of 0.788. The Random Forest model achieved the highest precision (100%) but with lower recall (23%), while Logistic Regression showed higher recall (46%) but lower precision (10%). Patients who developed SSIs were significantly older (mean age 61.1 vs. 58.5 years), had higher ASA scores (78.8% vs. 45.3% with ASA score 3), more frequently had contaminated wounds (40.9% vs. 27.5%), and more commonly received steroids (83.3% vs. 58.7%). Conclusions: Machine learning has shown promising results in enhancing the efficiency of SSI surveillance by enabling healthcare professionals to prioritize high-risk patients. While the models demonstrated strong overall accuracy, challenges related to imbalanced datasets remain. The XGBoost model provided the best balance between precision and recall, making it potentially the most clinically useful approach for SSI surveillance augmentation.

  • The Effect of Mobile Phone and Home Visit on Childhood Vaccination Uptake in Rural Communities of Bayelsa State Nigeria. A Pragmatic Cluster Randomized Control Trial

    From: JMIR Preprints

    Date Submitted: Apr 1, 2025

    Open Peer Review Period: Apr 1, 2025 - Mar 17, 2026

    Background: Immunization is a critical public health intervention for preventing vaccine-preventable diseases (VPDs) and achieving herd immunity. However, suboptimal vaccination coverage remains a cha...

    Background: Immunization is a critical public health intervention for preventing vaccine-preventable diseases (VPDs) and achieving herd immunity. However, suboptimal vaccination coverage remains a challenge, particularly in rural and underserved areas. Missed appointments due to forgetfulness and logistical barriers contribute significantly to low immunization rates. This study evaluates the impact of mobile phone (MP) reminders and home visits (HV) on childhood immunization completion rates in Bayelsa State, Nigeria. Objective: The study aimed to assess the effectiveness of MP reminders and HV outreach in improving vaccination coverage among children under two years of age. Methods: A pragmatic cluster randomized controlled trial was conducted in rural communities of Bayelsa State, Nigeria. A total of 384 participants were randomly assigned to three study arms: control (no intervention), MP reminders, and HV outreach (128 per arm). A multi-stage sampling technique was employed, and data were collected using a semi-structured WHO SAGE survey tool. Statistical analyses were performed using SPSS v25, with chi-square (χ²) tests used to compare categorical variables. Statistical significance was set at p ≤ 0.05, with effect sizes reported. Results: The study revealed significant differences in immunization completion rates across study groups: control (46.1%, 59/128), MP reminders (59.4%, 76/128), and HV outreach (63.3%, 81/128). Both interventions were effective in improving vaccination uptake, with a statistically significant difference (p = 0.015) and a moderate effect size (0.257). However, HV outreach demonstrated the highest completion rate, suggesting its greater effectiveness in overcoming access and engagement barriers. Conclusions: Integrating MP reminders and HV outreach into routine immunization programs can significantly improve childhood vaccination coverage. HV, in particular, addresses accessibility challenges and enhances community trust, making it a preferred strategy for increasing immunization rates. To optimize immunization coverage, policymakers should implement a hybrid approach, combining MP reminders with HV outreach, particularly in rural and underserved areas. Strengthening community-based health worker engagement and leveraging digital health innovations will further enhance vaccination efforts. Improved immunization coverage through these interventions reduces the risk of VPD outbreaks, enhances herd immunity, and contributes to achieving global vaccination targets. By addressing barriers to vaccine access and adherence, these strategies offer scalable, cost-effective solutions for improving child health outcomes. This trial provides robust evidence on the effectiveness of digital and community-based interventions for improving vaccination coverage. By comparing MP reminders and HV outreach, the study offers practical insights for health policymakers and program implementers. The findings contribute to global immunization research by highlighting scalable, low-cost solutions that can be adapted in resource-limited settings to strengthen immunization programs and reduce childhood morbidity and mortality.

  • Quality and Dissemination of Uterine Fibroid Health Information on TikTok and Bilibili: A Cross-Sectional Study

    From: JMIR Formative Research

    Date Submitted: Mar 28, 2025

    Open Peer Review Period: Mar 31, 2025 - May 26, 2025

    Background: The rise of short-video platforms, such as TikTok (Douyin in China) and Bilibili, has significantly influenced how health information is disseminated to the public. However, the quality, r...

    Background: The rise of short-video platforms, such as TikTok (Douyin in China) and Bilibili, has significantly influenced how health information is disseminated to the public. However, the quality, reliability, and effectiveness of health-related content on these platforms, particularly regarding uterine fibroids, remain underexplored. Uterine fibroids are a common medical condition that affects a substantial proportion of women worldwide. While these platforms have become vital sources of health education, misinformation and incomplete content may undermine their efficacy. Objective: This study aims to address these gaps by evaluating the quality and dissemination effectiveness of uterine fibroid-related health information on TikTok and Bilibili. Methods: A total of 200 uterine fibroid-related videos (100 from TikTok and 100 from Bilibili) were selected through a keyword search. The videos were evaluated by two trained gynecological experts using the Global Quality Score (GQS) and a modified version of the DISCERN tool (mDISCERN). Additionally, the Patient Education Materials Assessment Tool for Audio/Visual Materials (PEMAT-A/V) was employed to assess the understandability and actionability of the videos. Statistical analyses, including the Mann-Whitney U test, Spearman rank correlation, and stepwise regression analysis, were used to assess differences between platforms and identify predictors of video quality. Results: The results indicated that TikTok outperformed Bilibili in terms of user engagement metrics such as likes, comments, shares, and followers (all P < .001). However, Bilibili videos were generally longer than those on TikTok (P < .001). The overall quality and reliability of the videos on both platforms were suboptimal, with median GQS scores of 3 (range: 1-5) for TikTok and Bilibili. The median modified DISCERN scores were also low: 2 (range: 1-4) for TikTok and 2 (range: 1-3) for Bilibili, with no significant differences between the two platforms (P = 0.62 for GQS, P = 0.18 for mDISCERN). Both platforms scored similarly on understandability (median PEMAT-U = 77%) and actionability (median PEMAT-A = 67%). Videos uploaded by medical professionals on TikTok had significantly higher quality scores compared to those uploaded by non-professionals. A moderate positive correlation was observed between the GQS and mDISCERN scores (r = 0.41, P < .01), indicating an interrelationship between quality and reliability. Stepwise regression analysis identified "completeness score," "source," and "PEMAT scores" as significant predictors of video quality. Conclusions: This study highlights the generally low quality of uterine fibroid-related health information on short-video platforms, although TikTok showed better performance in terms of engagement and quality. The involvement of medical professionals was found to enhance video quality. These findings underscore the need for improved oversight of health content on social media platforms and greater involvement of healthcare professionals to ensure the dissemination of accurate and reliable health information.

  • Use of Artificial Intelligence for Evaluation of the Entrance Exam of the Brazilian Society of Shoulder and Elbow Surgery: Observational Study

    From: JMIR AI

    Date Submitted: Mar 19, 2025

    Open Peer Review Period: Mar 31, 2025 - May 26, 2025

    Background: Artificial intelligence (AI) has shown growing potential in medical education and assessment. However, its effectiveness in specialized exams, such as those administered by the Brazilian S...

    Background: Artificial intelligence (AI) has shown growing potential in medical education and assessment. However, its effectiveness in specialized exams, such as those administered by the Brazilian Society of Shoulder and Elbow Surgery (SBCOC), remains underexplored. Objective: This study aimed to compare the performance of multiple AI models against human candidates (national average) in the SBCOC entrance exams from 2021 to 2023, focusing on answer accuracy and reliability of cited sources. Methods: We evaluated five AI models—ChatGPT-4, ChatGPT-o1-pro, GEMINI (Google), Meta Llama 3.1, and a trained ChatGPT-4 version restricted to specific reference files—using the official SBCOC exams (50 multiple-choice questions per year). For each question, the AI provided a chosen answer (A/B/C/D) and a cited source. Image-based questions were handled by pasting the same image prompt into each AI interface. Outcomes included accuracy (comparison with the official key) and source reliability (scientific articles/books vs. websites). Statistical comparisons used chi-square and one-way ANOVA (significance level p<0.05) with post hoc tests, and 95% confidence intervals (CIs) were reported where applicable. This study was approved by the Research Ethics Committee of UNIFESP – Escola Paulista de Medicina, under CAAE number 81368024.9.0000.5505. Results: A total of 150 questions (50/year) were analyzed. Across the three years, ChatGPT-o1-pro mode achieved the highest accuracy (66% in 2021, 62% in 2022, 68% in 2023), significantly outperforming the average candidate scores by 14% (p=0.04), 20% (p=0.03), and 36% (p=0.029), respectively. GEMINI (40% in 2021; 28% in 2022; 38% in 2023) and Meta Llama 3.1 (32%, 44%, 50%) consistently underperformed compared to candidates (p>0.01). ChatGPT-4 (untrained) and trained ChatGPT-4 hovered near the passing threshold (>= 50%), displaying no statistically significant difference from candidate performance (p>0.05). Image-based questions showed lower AI consistency, highlighting limitations in visual interpretation. Conclusions: ChatGPT-o1-pro surpassed human performance over three consecutive exams. Both the untrained and trained ChatGPT-4 models performed comparably to the national average. While AI demonstrates considerable potential in multiple-choice medical exams, improved handling of image-based questions and more consistent reference verification remain crucial for broader clinical and educational applications. Clinical Trial: -

  • My Future in Focus: Exploration of Students' Perceptions and Experiences using the Prototype Future Me’ - a Prospection-Based Chatbot ‘Promoting Mental Well-being

    From: JMIR Formative Research

    Date Submitted: Mar 24, 2025

    Open Peer Review Period: Mar 31, 2025 - May 26, 2025

    Background: The growing demand for mental health support has led to exploration of digital interventions to bridge the gap between available resources and those seeking help. Large language models (LL...

    Background: The growing demand for mental health support has led to exploration of digital interventions to bridge the gap between available resources and those seeking help. Large language models (LLMs) have emerged as a promising technology for creating more personalized and adaptive mental health chatbots. Prospection—the ability to envision and plan for future outcomes—represents a transdiagnostic process altered across various mental health conditions that could be effectively targeted through such interventions. Objective: To investigate how people use "Future Me," an LLM-powered chatbot designed to facilitate future-oriented thinking, and what types of support they seek from it; to examine how Future Me enables future-oriented thinking; to assess its acceptability and usability across different user groups; to understand postgraduate students' specific perceptions and needs regarding chatbot-based stress management; and to identify how chatbot design can be improved to better address users' mental wellbeing needs. Methods: Two complementary studies were conducted. Study 1 (n = 20) examined how postgraduate students used Future Me during a single guided session, followed by semi-structured interviews. Study 2 (n=14) investigated how postgraduate students interacted with Future Me over a one-week period, with interviews before and after usage. Both studies analyzed conversation transcripts and interview data using thematic analysis to understand usage patterns, perceived benefits, and limitations. Results: Across both studies, participants primarily engaged with Future Me to discuss career/education goals, personal obstacles, and relationship concerns. Users valued the chatbot's ability to provide clarity around goal-setting, its non-judgmental nature, and its 24/7 accessibility. Future Me effectively facilitated self-reflection and offered new perspectives, particularly for broader future-oriented concerns. However, both studies revealed limitations in the chatbot's ability to provide personalized emotional support during high-stress situations, with participants noting that responses sometimes felt formulaic or lacked emotional depth. Postgraduate students specifically emphasized the need for greater context awareness during periods of academic stress. Conclusions: Future Me demonstrates promise as an accessible tool for promoting prospection skills and supporting mental wellbeing through future-oriented thinking. However, effectiveness appears context-dependent, with prospection techniques more suitable for broader life decisions than acute stress situations. Future development should focus on creating more adaptive systems that can adjust their approach based on the user's emotional state and immediate needs. Rather than attempting to replicate human therapy entirely, chatbots like Future Me may be most effective when designed as complementary tools within broader support ecosystems, offering immediate guidance while facilitating connections to human support when needed.

  • Primary Care Clinician Perspectives on Older Adult Chronic Pain Management and Clinical Decision Support

    From: JMIR Formative Research

    Date Submitted: Mar 23, 2025

    Open Peer Review Period: Mar 31, 2025 - May 26, 2025

    Background: Chronic pain management in older adults can be challenging for primary care clinicians because of comorbidities, side effects, and complicated guideline recommendations. Clinical decision...

    Background: Chronic pain management in older adults can be challenging for primary care clinicians because of comorbidities, side effects, and complicated guideline recommendations. Clinical decision support systems (CDSS) can enhance guideline adherence in chronic pain management by collecting and organizing patient information and aiding clinician decision-making. This study examined clinicians’ views on challenges in managing chronic pain and their opinions on a CDSS that gathered patient preferences and provided clinicians with decision support for chronic pain management. Objective: The objective of this study was to explore primary care clinicians’ perspectives on the challenges of managing chronic pain in older adults and evaluate their opinions on a clinical decision support system (CDSS) designed to gather patient preferences and facilitate guideline-based, multimodal pain management. Methods: We conducted semi-structured interviews with 18 clinicians from two University of Chicago Medicine primary care clinics piloting the CDSS. The interview guide was informed by the Consolidated Framework for Implementation Research. Results: Participants included 89% physicians and 11% advanced practice nurses. Participants stressed the importance of a comprehensive, patient-centered approach to chronic pain management and favored multimodal and non-pharmacological treatments. Challenges included complex medical histories, competing priorities, insurance limitations, and opioid misuse concerns. Clinicians found the CDSS beneficial for promoting multimodal care discussions and enhancing visit efficiency. However, there were concerns regarding its complexity, workflow compatibility, and older patients' technology navigation difficulties. While tools, such as the pre-visit questionnaire and conversation tool, were valued, clinicians emphasized the need for adaptability and streamlined usability. Conclusions: The primary care clinicians in this study were aligned with clinical practice guidelines to provide patient-centered pain management using multimodal treatments. However, they had several concerns regarding how complex chronic pain management can be for older adult patients. They expressed interest in using the CDSS but were concerned about its complexity. I-COPE offers a promising approach to support guideline-based chronic pain and opioid management in primary care. By addressing usability and workflow compatibility, CDSS tools like I-COPE can better equip clinicians to provide comprehensive, patient-centered care, ultimately enhancing treatment outcomes for older adults with chronic pain.

  • User-Driven Development of a Digital Behavioral Intervention for Chronic Pain: A Multi-Methods Study

    From: JMIR Formative Research

    Date Submitted: Mar 21, 2025

    Open Peer Review Period: Mar 31, 2025 - May 26, 2025

    Background: Recent research shows that chronic pain affects 27% of the adult population. For many, pain is significantly impairing quality of life and everyday functioning. Behavioral interventions ha...

    Background: Recent research shows that chronic pain affects 27% of the adult population. For many, pain is significantly impairing quality of life and everyday functioning. Behavioral interventions have shown utility, but access remains limited. Digital health solutions can increase reach but there is a need for user-friendly, feasible, and evidence-based digital interventions. Objective: This study aims to clarify how a digital behavioral intervention can be developed in a user-centered approach to address the needs and preferences of the target population. Methods: This study used a multi-method approach to develop prototypes for a digital behavioral intervention across three phases: Preparation (Phase 0), Design (Phase 1), and Testing (Phase 2). End-user involvement was prioritized through fictional Patient Personas, focus groups with patients (n=5) and therapists (n=12), and pilot testing (n=11 patients, n=3 therapists) of the digital intervention. Results: Based on end-user input, a 6-week digital behavioral intervention for chronic pain was created. Focus groups highlighted the importance of accessibility and adaptability of the digital intervention. Results from the pilot testing demonstrated the usability of the intervention. Conclusions: Results illustrated the utility of Patient Personas when preparing, focus groups when designing, and end-user feedback when testing this new intervention. Findings indicated that the treatment is promising, while also providing relevant end-user suggestions to guide further improvements.

  • Use of Indigenous-based methodologies to enhance the understanding of local context in Ugandan communities: Protocol for a community-based adaptation of a digital health program

    From: JMIR Research Protocols

    Date Submitted: Mar 28, 2025

    Open Peer Review Period: Mar 31, 2025 - May 26, 2025

    Background: With many socially disadvantaged populations experiencing a higher level of illness than the general population, health research has begun to recognize the impact of social determinants on...

    Background: With many socially disadvantaged populations experiencing a higher level of illness than the general population, health research has begun to recognize the impact of social determinants on health outcomes. Community-based research has increasingly become used to understand the complexities of local context. However, given the number of interdependent factors influencing individual well-being, no single methodology can explore this level of complexity alone. To put context into perspective, research processes need to shift from the sole use of Western methodologies and instead incorporate collaborative methods from non-traditional research. Specifically, Indigenous methodologies have been developed to better understand the complexity of context within multiple worldviews, but current studies have failed to apply these approaches within other cultural settings. Objective: This mixed-methods study will utilize Western and Indigenous methodologies to adapt a digital health program for remote communities in Uganda. Methods: Using the principles from community-based research and user-centered design, a four-phased mixed-methods study will be conducted. The Indigenous method of two-eyed seeing will be used to promote a reflexive engagement strategy throughout all study phases. Phase 1 will focus on partnership building to co-develop the project priorities and study design. Phase 2 will involve a needs assessment to elicit a context-focused understanding regarding the local clinic and community environment. Phase 3 will involve a series of system adaptations to co-design the program. Phase 4 will consist of a community-based field study to evaluate the usability and cultural-relevance of the adapted program. Results: The study was approved by the Makerere University School of Medicine Research Ethics Committee (Mak-SOMREC-2021-63) and the UHN Research Ethics Board (ID #: 20-6022). This protocol provides novel strategy leveraging a range of community-based methods to ensure the contextual significance of each community’s challenges are reflected within the design of the Medly Uganda program. Conclusions: By integrating the community’s local knowledge into the design of the Medly Uganda program, this will lead to the development of meaningful interventions that improve health outcomes.

  • High Exposure to Screen: A threat for Health and Mental Wellbeing of School Going Children in Dhaka, Bangladesh

    From: JMIR Human Factors

    Date Submitted: Mar 6, 2025

    Open Peer Review Period: Mar 31, 2025 - May 26, 2025

    Background: In Bangladesh as well as throughout the world, children's screen time has significantly increased. Children spent a lot of time on the internet and digital screens for entertainment, educa...

    Background: In Bangladesh as well as throughout the world, children's screen time has significantly increased. Children spent a lot of time on the internet and digital screens for entertainment, education, and communication which have increased their daily screen time. However, the potential detrimental impacts of excessive screen time on children's mental, physical, and social health have drawn attention. Objective: This study aimed to explore the effect of high exposure to screen on health and mental well-being of school-going children in Dhaka, Bangladesh. Methods: From July 2022 to June 2024, this cross-sectional descriptive study was carried out. 420 kids between the ages of 6 and 14 were enrolled in three English-medium and three Bangla-medium schools in Dhaka city using a stratified random sample technique. Anthropometric measurements, a semi-structured questionnaire, the Pittsburgh Sleep Quality Index Scale (PSQI), the Development and Wellbeing Assessment Scale (DAWBA), and the Strength and Difficulties Questionnaire (SDQ), which was validated in Bangla, were used to gather data. We considered the students who were exposed to screen for less than 2 hours as the low-exposed group and those who were exposed for more than 2 hours as high-exposed group. Results: We found 83% of the students were high exposed group and their average screen time was 4.6 ± 2.3 hours. Compared to the low exposed group, the high exposed group had a significantly higher rate of eye problems (96% vs 4%, P< 0.001). Headache was also common in high exposed group (83%). Moreover, students of high exposed group had a short duration and poor quality of sleep which was statistically significant. Furthermore, obesity was more predominant in the high-exposure group (p < 0.001). Our study revealed overall 40% of children suffered from mental health problems by using DAWBA scale which was increased in high exposed group compared to low exposed group. Behavioral problems, such as conduct issues (28.3%) and peer difficulties (28.8%), were observed among the participants. However, there was no statistically significant difference was found between two groups. Conclusions: A collaborative and coordinated multistage approach will be required to create effective and acceptable guidelines and policies for the optimum and positive use of digital screens for the children of Bangladesh. Further prospective studies on larger scales can be conducted to determine the impacts on health aspects meticulously.

  • Telemedicine Adoption for Dementia Care in Nigeria: A Scoping Review

    From: Interactive Journal of Medical Research

    Date Submitted: Mar 28, 2025

    Open Peer Review Period: Mar 31, 2025 - May 26, 2025

    Background: Dementia is a global health challenge, particularly in Nigeria, where limited healthcare infrastructure, cultural stigmas, and poor awareness hinder its care. Telemedicine can improve pati...

    Background: Dementia is a global health challenge, particularly in Nigeria, where limited healthcare infrastructure, cultural stigmas, and poor awareness hinder its care. Telemedicine can improve patient outcomes, increase healthcare access, and support caregivers. However, challenges like poor internet connectivity, digital literacy, and lack of integrated strategies hinder its adoption, particularly in rural areas Objective: This study evaluates the adoption of telemedicine for dementia care in Nigeria, examining effectiveness in improving patient outcomes, reducing caregiver burden, and enhancing accessibility. It also identifies infrastructural and cultural barriers, proposing strategies for a sustainable telemedicine framework tailored to Nigeria’s sociocultural context. Methods: A scoping review guided by the (PRISMA) framework used databases like PubMed, Scopus, CINAHL, PsycINFO, and Google Scholar. Search terms included “telemedicine”, "dementia care," “Nigeria”, “digital health”, “telehealth interventions”, “video consultations”, and “remote monitoring tools”. Out of 640 results, 23 articles were selected. Issues like poor digital literacy, internet access, and lack of a cohesive policy were identified. Results: Out of 23 studies, 10 (43.5%) focused on m(Health) applications, 8 (34.8%) on video consultations, and 5 (21.7%) on remote monitoring tools. These interventions improved caregiver support, medication adherence, and access to specialist care but faced challenges in rural settings. Conclusions: There is an urgent need for an all-inclusive policy in Nigeria that integrates technological solutions into existing dementia care frameworks. mHealth apps, video consultations, and remote monitoring tools show potential for enhancing healthcare access, improving outcomes, and reducing caregiver burden.

  • Participant recruitment strategies to population cohort studies: the lessons learned from Generation Scotland

    From: Journal of Medical Internet Research

    Date Submitted: Mar 28, 2025

    Open Peer Review Period: Mar 31, 2025 - May 26, 2025

    Background: Generation Scotland (GS) is a genetic family health cohort study established in 2006 (N~24,000). A new wave of recruitment was initiated in 2022 aimed at adding a further 20,000 new partic...

    Background: Generation Scotland (GS) is a genetic family health cohort study established in 2006 (N~24,000). A new wave of recruitment was initiated in 2022 aimed at adding a further 20,000 new participants to the cohort using online data collection and remote saliva sampling (for genotyping and DNA methylation profiling). Eligible individuals included anyone living in Scotland aged over 12 years. New participants give consent for linkage to their medical and administrative records, and to provide a saliva sample for DNA. The current study evaluates the different strategies employed to recruit new participants to the GS cohort for those aged 16+ (recruitment of ages 12-15 will be presented separately due to additional strategies). Objective: This study aimed to evaluate recruitment strategies employed to recruit new participants to the GS cohort. Recruitment strategies were compared in terms of overall numbers as well as sociodemographic characteristics of the recruits, sample return rates and cost-effectiveness. Methods: From May 2022 to the end of December 2023 recruitment was undertaken by the following methods: snowball recruitment (through friends and family of existing volunteers), invitations to those who participated in a previous survey during the pandemic (CovidLife: the GS COVID-19 impact survey) and Scotland-wide recruitment through social media (including sponsored Meta advertisements), news media and TV advertisement. Method of recruitment was self-reported by participants in the baseline questionnaire. Results: Over the above period, 7,889 new participants were recruited to the cohort. According to the different strategies, this included, in order: social media (N=2,436, 30.9%), CovidLife survey responder invitations (N=2,049, 26.0%), TV advertising (N=1,367, 17.3%), snowball (N=891, 11.3%), news media (N=747, 9.5%) and other methods/unknown (N=399, 5.0%). More females signed up than males (70.5% female participants). To date, 83.5% of participants have returned their postal saliva sample. Sample return varied between demographic factors (>60 years 90.5% vs 16-34 years 71.1%). The average cost per participant across all recruitment strategies was £13.52. Past survey invitations (CovidLife) were most cost-effective at £0.37 per recruit, social media cost £14.78 per recruit, whilst TV advertisement recruitment was the most expensive at £33.67. Conclusions: We present the challenges and successes of recruitment of new participants to a large ongoing cohort using remote assessment. Besides targeting existing survey responders, social media advertising has been the most cost-effective and easily sustained strategy for recruitment. We note different strategies resulted in successful recruitment over varying timescales (e.g. consistent sustained recruitment for social media, and large spikes for news media and TV advertising) which may be informative for future studies with different requirements of recruitment periods. Limitations include self-reported methods of recruitment, and difficulties in capturing multi-layered recruitment. Overall, these data demonstrate the potential cost requirements and effectiveness of different strategies that could be applied to future research studies. Future work will report success and challenges of recruitment activities aimed at younger individuals, under 16 years.

  • Sociotechnical Challenges in Implementing Domestic Violence Screening via Telehealth and In-Person Care: A Qualitative Study on Clinicians’ Perspectives in Healthcare Settings

    From: Journal of Medical Internet Research

    Date Submitted: Mar 31, 2025

    Open Peer Review Period: Mar 30, 2025 - May 25, 2025

    Background: The COVID-19 pandemic significantly accelerated the adoption of telehealth services, reshaping healthcare delivery and leading to the widespread use of hybrid care models that combine digi...

    Background: The COVID-19 pandemic significantly accelerated the adoption of telehealth services, reshaping healthcare delivery and leading to the widespread use of hybrid care models that combine digital and in-person care. As a result, clinical care is delivered both in digital and physical environments. This shift has brought to light the complex challenges associated with implementing domestic violence (DV) screening protocols in both digital and in-person care settings. New York State’s Public Health Law Section 2805-z (NYS PHL §2805-z) mandates, among other requirements, that hospitals implement policies and procedures for the identification of DV in order to strengthen support of DV survivors. However, the pandemic’s impact on healthcare systems raised critical questions about the effectiveness and adaptability of mandated screenings within the context of telehealth. Understanding how these challenges emerge in practice is crucial for improving DV screening and ensuring survivors receive appropriate support. Objective: This study explores the challenges healthcare providers face in implementing DV screening to comply with NYS PHL §2805-z requirements to establish policies and procedures for identifying DV, as well as ways of supporting effective screening practices. By exploring two distinct care delivery settings, the telehealth environment and traditional in-person environment, our objective is to identify the sociotechnical challenges healthcare providers face in meeting policy requirements and identify potential sources of support to address these challenges. By identifying barriers to effective DV screening, this study seeks to provide actionable insights for enhancing policy implementation and improving care for DV survivors. Methods: We conducted interviews with healthcare professionals—nurses, social workers, and physicians—across New York City, who are involved in DV screening. These interviews were analyzed using a sociotechnical framework to understand how policy, organizational structures, and individual practices intersect and impact the effectiveness of DV screening, especially within telehealth settings. Results: Our findings reveal significant gaps in the awareness and consistent application of NYS PHL §2805-z among healthcare providers, leading to variable screening practices. The shift to telehealth introduced additional layers of complexity, with challenges in ensuring patient privacy and safety, with a lack of clear guidelines tailored to remote DV screenings. Moreover, current training programs appear inadequate in preparing providers for the nuances of telehealth-based DV screening, which is crucial for adhering to policy mandates. Conclusions: As telehealth becomes an integral part of healthcare, there is an urgent need to refine and reinforce DV screening policies and procedures designed to comply withNYS PHL §2805-z and similar laws. This study highlights the importance of developing practical and consistent telehealth protocols, enhancing provider training, creating supportive workflows, allotting adequate resources, and fostering collaboration among stakeholders to ensure that DV survivors receive the care they need in both remote and in-person clinical settings.

  • Bridging Knowledge and Practice Gaps in Lassa Fever Prevention: Awareness, Attitudes, and Infection Control Measures Among Healthcare Workers and Residents in Edo, Ondo, and Kwara States

    From: JMIR Preprints

    Date Submitted: Mar 30, 2025

    Open Peer Review Period: Mar 30, 2025 - Mar 15, 2026

    Background: Lassa fever, an acute viral hemorrhagic illness endemic in West Africa, remains a significant public health concern in Nigeria, particularly in Edo, Ondo, and Kwara States. Despite recurre...

    Background: Lassa fever, an acute viral hemorrhagic illness endemic in West Africa, remains a significant public health concern in Nigeria, particularly in Edo, Ondo, and Kwara States. Despite recurrent outbreaks, limited data exist on the knowledge, attitudes, and practices (KAP) of residents and healthcare personnel across these states, creating a critical research gap. Effective prevention and control require a thorough understanding of these factors to inform targeted interventions and policy decisions. Objective: This study aimed to assess the KAP of residents and primary healthcare (PHC) personnel regarding Lassa fever across Edo, Ondo, and Kwara States. Specifically, it examined awareness levels, preventive behaviors, misconceptions about transmission, and compliance with infection control measures, including the use of personal protective equipment (PPE). The findings provide insights for evidence-based interventions to reduce the burden of Lassa fever in these endemic regions. Methods: A cross-sectional survey was conducted among 3,582 residents and 540 PHC personnel across Edo, Ondo, and Kwara States. Data were collected through structured questionnaires assessing knowledge, attitudes, and practices related to Lassa fever. Statistical analyses, including cross-tabulations and the Relative Importance Index (RII), were employed to identify patterns and disparities across different residential and professional groups. Results: Among residents, 80.1% recognized Lassa fever as a severe illness, yet only 6.9% had participated in awareness campaigns. Preventive behaviors were inadequate, with only 12.1% storing food in rodent-proof containers and 25.4% engaging in frequent environmental sanitation. Knowledge gaps persisted, as only 3% were aware of the disease’s 1–21-day incubation period, and 0.3% acknowledged sexual transmission. Socioeconomic disparities significantly influenced compliance with sanitation measures (p < 0.001), with higher-income households demonstrating better adherence. Furthermore, preventive practices such as using traps (14.5%) and participating in sanitation campaigns (6.8%) varied significantly by residence type (p < 0.001). PHC personnel demonstrated strong theoretical knowledge, with an RII of 0.960 for key facts, including the classification of Lassa fever as a viral hemorrhagic illness and the identification of rats as primary reservoirs. However, only 84% recognized alternative reservoirs such as bats and mosquitoes. PPE adherence was poor, particularly for facemasks and eye protection (RII = 0.217), highlighting significant gaps in infection control practices. Conclusions: The study reveals critical gaps in awareness, preventive behaviors, and infection control measures across Edo, Ondo, and Kwara States. While healthcare workers displayed strong theoretical knowledge, practical compliance with PPE use was insufficient, posing a risk of disease transmission. Addressing these gaps is essential for effective Lassa fever control. Targeted health education campaigns should be implemented to enhance public awareness and dispel misconceptions about Lassa fever transmission. Strengthened training programs for PHC personnel, stricter PPE compliance policies, and improved access to sanitation resources should be prioritized. Additionally, community-based interventions, including regular environmental sanitation and rodent control, should be encouraged to reduce exposure risks. Bridging the knowledge and practice gaps in Lassa fever prevention is essential to mitigating outbreaks, reducing fatalities, and strengthening public health resilience in Edo, Ondo, Kwara States, and other endemic regions.

  • Speech Emotion Recognition in Mental Health: A Systematic Review of Voice Based Applications

    From: JMIR Mental Health

    Date Submitted: Mar 24, 2025

    Open Peer Review Period: Mar 30, 2025 - May 25, 2025

    Background: The nascent field of Speech Emotion Recognition (SER) encompasses a wide variety of approaches with AI technologies providing improvements in recent years. The links between subjects’ em...

    Background: The nascent field of Speech Emotion Recognition (SER) encompasses a wide variety of approaches with AI technologies providing improvements in recent years. The links between subjects’ emotional states and pathological diagnoses are of particular interest. This study aims to investigate the performance of tools combining these approaches with a view to their use within clinical contexts. Objective: The objective of this review was to determine if and how SER technologies have been applied within clinical contexts. Methods: The review includes studies applied to speech (audio) signal, for a select set of pathologies/disorders and only includes those studies that include an evaluation of diagnosis performance using machine learning performance metrics or statistical correlation measures. PubMed, IEEE Explore, ArXiv and Science Direct databases were queried, as recently as February 2025. The QUADAS framework was used to measure the Risk of Bias. Results: A total of 17 articles were included in the final review. The included papers addressed the suicide risk (3), depression (9), psychotic disorders (3) and autism spectrum disorders (2). Conclusions: SER technologies are mostly used indirectly in mental health research and in a wide variety of manners including different architectures, datasets and pathologies. This diversity makes a direct assessment of the technology challenging. Nonetheless, promising results are obtained in various studies that attempt to diagnose patients based on either indirect or direct results from SER models. These results highlight the potential for this technology to be used within a clinical setting. Future work should focus on how these technologies can be used collaboratively by clinicians. Clinical Trial: Prospero ID 1006669

  • Application of Digital Technology-Assisted PBL in Clinical Education of Trauma Orthopedics

    From: JMIR Medical Education

    Date Submitted: Mar 27, 2025

    Open Peer Review Period: Mar 28, 2025 - May 23, 2025

    Background: Medical education has evolved significantly over the past few decades, with increasing emphasis on interactive and student-centered learning approaches. Traditional lecture-based learning...

    Background: Medical education has evolved significantly over the past few decades, with increasing emphasis on interactive and student-centered learning approaches. Traditional lecture-based learning (LBL), once the dominant method of instruction in medical schools, has faced criticism for its passive nature and limited engagement in developing clinical reasoning and problem-solving skills. In response, problem-based learning (PBL) has emerged as an alternative, placing students in more active roles, where they work through real-life clinical cases and collaboratively develop solutions. PBL has been shown to foster critical thinking and enhance long-term retention of medical knowledge compared to conventional methods. Objective: This study aims to address the challenges commonly encountered in trauma orthopedic education, such as the complex morphology of fractures and the limited experience of novice learners. By integrating advanced digital technologies with Problem-Based Learning (PBL), the study seeks to enhance teaching effectiveness in this clinical setting. Methods: The study included 50 clinical interns from the eight-year medical program at Tongji Medical College, Huazhong University of Science and Technology, who completed a one-week internship in the trauma orthopedic department of Union Hospital. Participants were randomly assigned to either a group utilizing a digital technology-assisted PBL model or a group following the traditional lecture-based learning (LBL) approach. The educational content focused on hip fractures, and the effectiveness of the teaching methods was evaluated through assessments of theoretical knowledge, clinical skills, and a satisfaction survey. Data were analyzed using SPSS 20.0 to determine the effectiveness of the digital technology-assisted PBL approach in improving clinical education outcomes. Results: The use of 3D-printed models enhanced the visualization and practical application of anatomical structures, positively influencing students' engagement and fostering autonomous learning. The PBL method significantly promoted active learning, improving collaboration and communication skills among students. However, digital technologies presented certain limitations, including high costs and the inability to represent soft tissue structures, while the PBL approach posed challenges such as increased student workload and higher instructional demands on educators. Conclusions: The integration of digital technology with PBL in trauma orthopedic education demonstrated significant pedagogical advantages, contributing to improved teaching quality and learning outcomes. This approach warrants further investigation and broader implementation in clinical education. Clinical Trial: none

  • Comparative Evaluation of Advanced AI Reasoning Models in Korean National Licensing Examination OpenAI vs DeepSeek

    From: JMIR Medical Education

    Date Submitted: Mar 27, 2025

    Open Peer Review Period: Mar 28, 2025 - May 23, 2025

    Artificial intelligence (AI) has advanced in natural language processing and reasoning, with large language models (LLMs) increasingly assessed for medical education and licensing exams. Given the gro...

    Artificial intelligence (AI) has advanced in natural language processing and reasoning, with large language models (LLMs) increasingly assessed for medical education and licensing exams. Given the growing use of AI in medical licensing examinations, evaluating their performance on non-Western, region-specific tests like the Korean Medical Licensing Examination (KMLE) is crucial for assessing their real-world applicability. This study compared five LLMs—GPT-4o, o1, o3-mini (OpenAI), DeepSeek-V3, and DeepSeek-R1 (DeepSeek)—on the KMLE. A total of 150 multiple-choice questions from the 2024 KMLE were extracted and categorized into three domains: Local Health & Medical Laws, Preventive Medicine, and Clinical Medicine. Graph-based questions were excluded. Each model completed five independent runs via API, with accuracy assessed against official answers. Statistical differences were analyzed using ANOVA, and consistency was measured using Fleiss' kappa coefficient. o1 achieved the highest overall accuracy (94.3%), excelling in Clinical Medicine (97.5%) and Local Health & Medical Law (81.0%), while DeepSeek-R1 led in Preventive Medicine (92.6%). Despite domain-specific variations, all models surpassed passing criteria. For consistency, o1 ranked highest (97.1%), with DeepSeek-V3 excelling in Local Health & Medical Law (97.5%). Performance declined in Local Health & Medical Law, likely due to legal complexities and limited Korean-language training data. This is the first study to compare OpenAI and DeepSeek models on medical licensing exam, demonstrating their strong performance, with o1 and DeepSeek-R1 ranking within the top 10% of human candidates. While o1 was the most accurate, DeepSeek-R1 provided a cost-effective alternative. Future research should optimize LLMs for non-English exams and develop Korea-specific AI models to improve accuracy in legal domains.

  • COVID 19 Diagnosis Analysis using Transfer Learning

    From: JMIRx Med

    Date Submitted: Mar 26, 2025

    Open Peer Review Period: Mar 28, 2025 - May 23, 2025

    Coronaviruses, including SARS-CoV-2, are responsible for COVID-19, a highly transmissible disease that emerged in December 2019 in Wuhan, China. During the past five years, significant advancements ha...

    Coronaviruses, including SARS-CoV-2, are responsible for COVID-19, a highly transmissible disease that emerged in December 2019 in Wuhan, China. During the past five years, significant advancements have been made in understanding and mitigating the virus. Although the initial outbreak led to global health crises, improved vaccination strategies, antiviral treatments, and AI-driven diagnostic tools have contributed to better disease management. However, COVID-19 continues to pose risks, particularly for immuno-compromised individuals and those with pre-existing conditions. This study explores the use of deep learning for a rapid and accurate diagnosis of COVID-19, addressing ongoing challenges in healthcare infrastructure and testing accessibility. We propose an enhanced automated detection system leveraging state-of-the-art convolutional neural networks (CNNs), including updated versions of VGG16, VGG19, and ResNet50, to classify COVID-19 infections from chest radiographs and computerized tomography (CT) scans. Our results, based on an expanded dataset of over 6000 medical images, demonstrate that the optimized ResNet50 model achieves the highest classification performance, with 97.77% accuracy, 100% sensitivity, 93.33% specificity, and a 98.0% F1-score. These findings reinforce the potential of AI-assisted diagnostic tools in improving early detection and pandemic preparedness.

  • Effects of Prevention Messages for Electronic Gambling Machines on Behaviours and Cognitions: Protocol for a Two-Arm Stratified Block Randomised Controlled Study

    From: JMIR Research Protocols

    Date Submitted: Mar 27, 2025

    Open Peer Review Period: Mar 28, 2025 - May 23, 2025

    Background: Electronic Gambling Machines and online gambling are the reputedly most damaging gambling type from a public health perspective. Pop-up messages are often used as a responsible gambling (R...

    Background: Electronic Gambling Machines and online gambling are the reputedly most damaging gambling type from a public health perspective. Pop-up messages are often used as a responsible gambling (RG) measure to prevent harm for these screen-based types of gambling. Despite some evidence of effectiveness in the literature for these messages, limitations persist, among which low ecological validity is of particular concern. Objective: This study aims to test (1) the potential of pop-up messages as a prevention measure in a gambling setting, and (2) if this potential is moderated by characteristics of people exposed to the messages. Secondary objectives also tackle some fundamental assumptions of gambling studies conducted in a laboratory setting. Methods: This is a two-arm stratified block randomised controlled study. Eighty participants are recruited under the false pretense of evaluating the realism of a gambling session in a laboratory replicating a bar. Duplicity is also used to make participants believe that they are risking their own money during the experimentation (i.e. winnings and losses are real). Participants are randomised to one of the two arms in a 1:1 ratio: (1) Experimental group (regular gambling session with prevention pop-up messages presented on a fixed schedule; (2) Active control group (regular gambling session). Outcomes measures include behaviours, cognitive and emotional responses to the pop-up-messages. Believability of the gambling session’s realism is also evaluated. Results: Ethical approval was obtained from the Comités d’éthique de la recherche avec des êtres humains de l’Université Laval (CÉRUL; reference no 2020-076 A-1 / 27-05-2024). Recruitment began in February 2024 and was extended to conclude in December 2025. Study completion is expected in February 2026. No results are currently available. Conclusions: This study will provide new insights on the efficacy of pop-up messages as a prevention measure for gambling. Clinical Trial: ClinicalTrials.gov NCT06341504; https://clinicaltrials.gov/study/NCT06341504

  • Development of the SCI-BodyMap: Measuring mental body representations in adults with SCI: A study protocol for item generation, reliability, and validity testing

    From: JMIR Research Protocols

    Date Submitted: Mar 27, 2025

    Open Peer Review Period: Mar 28, 2025 - May 23, 2025

    Background: About 69% of Americans with spinal cord injury (SCI) have neuropathic pain. Research suggests that impairments in mental body representations (MBR, i.e., representations of the body in the...

    Background: About 69% of Americans with spinal cord injury (SCI) have neuropathic pain. Research suggests that impairments in mental body representations (MBR, i.e., representations of the body in the brain) likely contribute to neuropathic pain. Clinical trials in adults with SCI, focused on restoring MBR, led to improvements in sensation and movement, and neuropathic pain relief. Scales measuring aspects of MBR exist but none of them assess SCI-related MBR impairments. Objective: As our first aim, we will generate items of a new MBR scale for adults with SCI (the SCI-BodyMap). As our second aim, we will assess inter-rater reliability, test-retest reliability, concurrent validity, face validity, and utility of the SCI-BodyMap. Methods: Our preliminary work will encompass initial item generation by SB, an Italian Physical Therapist (PT) specialized in Cognitive Multisensory Rehabilitation (CMR), which is a therapeutic approach that focuses on restoring MBR in adults with neurological disorders and/or chronic pain. Further item refinements will be done by Italian PTs (n=7) and Brazilian PTs (n=3) specialized in CMR. In Aim 1, American PTs or Occupational Therapists (OT) (n=8) and adults with SCI (n=8) will provide feedback on the SCI-BodyMap. Then, American PTs (n=3) will administer the SCI-BodyMap to adults with SCI (n=3) and will provide more feedback during an in-person visit. In Aim 2, two assessors will administer the SCI-BodyMap to a sample of adults with SCI (n=30) for inter-rater reliability. The self-report items in the scale will be administered at 2 separate time points to assess test-retest reliability. We will also administer the SCI-BodyMap to uninjured adults (n=30) to identify whether those without SCI score statistically different on the scale than adults with SCI. We will assess concurrent validity through correlations between the MBR scale, the Revised Body Awareness Rating Questionnaire, and the Multidimensional Assessment Interoceptive Awareness-2. Face validity and utility will be assessed using the QQ-10. Results: As of March 2025, we have enrolled 8 PT/OTs and 8 adults with SCI in this study for Aim 1. Conclusions: A reliable and valid MBR scale is needed to identify MBR deficits in adults with SCI and evaluate the effects of interventions on MBR outcomes in adults with SCI. Improving MBR can lead to safer, more efficient day-to-day activities such as transfers, functional independence, quality of life, as well as reduced neuropathic pain, spasms, and improved sensorimotor function. Clinical Trial: N/A

  • Evaluating AI-Assisted Clinical Documentation with Medical Student Perceptions of CarePilot in Simulated Encounters: A Cross-sectional Study

    From: JMIR AI

    Date Submitted: Mar 19, 2025

    Open Peer Review Period: Mar 27, 2025 - May 22, 2025

    Background: Artificial Intelligence (AI) is transforming healthcare by streamlining clinical documentation and enhancing physician workflow. AI-powered systems, such as CarePilot, have the potential t...

    Background: Artificial Intelligence (AI) is transforming healthcare by streamlining clinical documentation and enhancing physician workflow. AI-powered systems, such as CarePilot, have the potential to reduce administrative burdens and mitigate physician burnout by automating tasks like transcribing patient encounters and predicting medical coding. Objective: This study evaluated the experiences of medical students using the CarePilot system during a simulated clinical encounter, thereby providing insights into its usability and potential impact on clinical documentation practices. Methods: In this cross-sectional study conducted at the Burnett School of Medicine at Texas Christian University, 44 third- and fourth-year medical students participated in a standardized simulation featuring a patient with a chief complaint of headache. Participants were tasked with recording patient history, physical examination findings, clinical reasoning, and management decisions using CarePilot, which was configured to emulate a typical electronic health record workflow. Following the encounter, each participant completed a 27-question electronic survey based on a Likert scale, designed to assess aspects such as ease of use, documentation efficiency, and overall system functionality. Results: Survey results revealed that over 75% of respondents rated key features—including ease of use, learnability, interface likability, and documentation organization—positively. However, approximately 30% of participants expressed neutral or dissatisfied opinions regarding overall satisfaction, citing workflow disturbances and limitations in functionalities that could impact patient interaction time. Conclusions: These findings suggest that while CarePilot is generally effective and user-friendly, targeted refinements in workflow integration and feature set are needed to further optimize its clinical application and support improved physician-patient engagement.

  • Determinants of Health-Promoting Behaviors Among Indonesian Adolescents Living in Child Welfare Institutions: A Structural Equation Modeling Study

    From: JMIR Public Health and Surveillance

    Date Submitted: Mar 27, 2025

    Open Peer Review Period: Mar 27, 2025 - May 22, 2025

    Background: Adolescents in child welfare institutions often experience challenges in adopting health-promoting behaviors (HPB), which leads to significant health vulnerabilities. Objective: This study...

    Background: Adolescents in child welfare institutions often experience challenges in adopting health-promoting behaviors (HPB), which leads to significant health vulnerabilities. Objective: This study aimed to identify the HPB of adolescents in child welfare institutions and the determinants influencing them, using the Health Promotion Model. Methods: A cross-sectional design was employed. A total of 276 adolescents from 17 child welfare institutions in East Java Province, Indonesia, participated in this study. Structural equation modeling was utilized to examine the relationships among the determinants. Results: HPB had a positive correlation with health literacy (r=0.13, P<.05), self-esteem (r=0.31, P<.001), perceived self-efficacy (r=0.66, P<.01) and social support (r=0.53, P<.01), and a negative correlation with perceived barriers to action (r=-0.15, P<.05). In the final model, both perceived self-efficacy and social support accounted for 47.9% of HPB. In addition, perceived barriers to action were influenced by health literacy (β=-0.234, P<.001), self-esteem (β=-0.194, P<.01), and perceived self-efficacy (β=-0.185, P<.01). Self-esteem indirectly affected HPB through perceived self-efficacy (β= 0.099, P<.01) and social support (β= 0.078, P<.001). Conclusions: To improve the HPB of adolescents in these institutions, their self-esteem needs to be increased in order to further enhance their self-efficacy and social support. Careful attention and monitoring of HPB among these adolescents may lead to better health outcomes and support their transition from child welfare institutions to the broader community.

  • Portraits of Large Language Models: Deciphering the Taxonomy of Medical LLMs

    From: JMIR Medical Informatics

    Date Submitted: Feb 26, 2025

    Open Peer Review Period: Mar 26, 2025 - May 21, 2025

    Background: Large Language Models (LLMs) continue to enjoy enterprise-wide adoption in healthcare while evolving in number, size, complexity, cost, and more importantly performance. Performance benchm...

    Background: Large Language Models (LLMs) continue to enjoy enterprise-wide adoption in healthcare while evolving in number, size, complexity, cost, and more importantly performance. Performance benchmarks play a critical role in their ranking across community leaderboards and subsequent adoption. Objective: Given the small operating margins of healthcare organizations and growing interest in LLMs and conversational AI, there is an urgent need for objective approaches that can assist in identifying viable LLMs without compromising their performance. The objective of the present study is to generate a taxonomy portrait of medical LLMs (N = 33) whose domain-specific and domain non-specific multivariate performance benchmarks were available from Open-Medical LLM and Open LLM leaderboards on Hugging Face. Methods: Hierarchical clustering of multivariate performance benchmarks is used to generate taxonomy portraits revealing inherent partitioning of the medical LLMs across diverse tasks. While domain-specific taxonomy is generated using nine performance benchmarks related to medicine from the Hugging Face Open-Medical LLM initiative, domain non-specific taxonomy is presented in tandem to assess their performance on a set of six benchmarks on generic tasks from the Hugging Face Open LLM initiative. Subsequently, non-parametric Wilcoxon Ranksum test and linear correlation is used to assess differential changes in the performance benchmarks between two broad groups of LLMs and potential redundancies between the benchmarks. Results: Two broad families of LLMs with statistically significant differences (\alpha = 0.05) in performance benchmarks are identified for each of the taxonomies. Consensus in their performance on the domain-specific, and domain non-specific tasks revealed inherent robustness of these LLMs across diverse tasks. Subsequently, statistically significant correlations between performance benchmarks revealed inherent redundancies, indicating a subset of these benchmarks may be sufficient in assessing the domain-specific performance of medical LLMs. Conclusions: Understanding the medical LLM taxonomies is an important step in identifying LLMs with similar performance while aligning with the needs, economics, and other demands of healthcare organizations. While the focus of the present study is on a subset of medical LLMs from the Hugging Face, enhanced transparency of performance benchmarks and economics across a larger family of medical LLMs is needed to generate more comprehensive taxonomy portraits accelerating their strategic and equitable adoption in healthcare. Clinical Trial: Not applicable

  • Development of a tongue image-based machine learning tool for the diagnosis of acute respiratory tract infection

    From: JMIR Medical Informatics

    Date Submitted: Mar 18, 2025

    Open Peer Review Period: Mar 26, 2025 - May 21, 2025

    Background: Tongue characteristics, widely utilized in traditional Chinese medicine for health assessment, have been shown to correlate with specific respiratory infections. With the ongoing global sp...

    Background: Tongue characteristics, widely utilized in traditional Chinese medicine for health assessment, have been shown to correlate with specific respiratory infections. With the ongoing global spread of Human adenoviruses (HAdVs), COVID-19, and other seasonal respiratory viruses, this study aims to enhance the convenience and cost-effectiveness of respiratory infection diagnoses by developing prediction models based on tongue characteristics. Method: This study utilized deep learning to extract features from 280 tongue images collected from COVID-19 patients, HAdVs patients, and healthy individuals. Machine learning diagnostic models were subsequently trained on these tongue characteristics to distinguish between normal cases and those indicative of COVID-19 and HAdVs infections. The key features identified by the machine learning algorithms were further visualized in a two-dimensional space. Result: Nine significant tongue features were identified: tongue coating color (red, green, blue), the presence of tooth marks, tongue coating crack ratio, tongue coating moisture level, texture directionality, texture roughness, and texture contrast. Diagnostic models trained on these features achieved an area under the precision-recall curve exceeding 70%, with the area under the receiver operating characteristic curve surpassing 80% for general performance. The SHAP value revealed that tongue color, moisture level, and texture direction were the most influential features. Conclusion: Our findings demonstrate the potential of tongue diagnosis in identifying pathogens responsible for acute respiratory tract infections at the time of admission. This approach holds significant clinical implications, offering the potential to reduce clinician workloads while improving diagnostic accuracy and the overall quality of medical care.

  • Impact of a multi-component intervention to build capacity of public health workers to make algorithmic diagnosis and management of high-risk pregnancies: Protocol for a matched-control, before-after quasi-experimental study with a mixed-method design in Uttar Pradesh, India.

    From: JMIR Research Protocols

    Date Submitted: Mar 26, 2025

    Open Peer Review Period: Mar 26, 2025 - May 21, 2025

    Background: In India, 20-30% pregnancies fall under high-risk category, contributing to 75% of perinatal mortality and morbidity. An effective approach to reduce maternal and neonatal mortality/morbid...

    Background: In India, 20-30% pregnancies fall under high-risk category, contributing to 75% of perinatal mortality and morbidity. An effective approach to reduce maternal and neonatal mortality/morbidity is early identification, effective management, and timely referral of high-risk pregnancies (HRPs). The Integrated High-Risk Pregnancy Tracking and Management (IHRPTM) program aims to enhance capacity of auxiliary nurse midwives (ANMs), medical officers (MOs), and specialist gynaecologists by: i. providing algorithmic, color-coded, detailed (yet simple) protocols for six HRP conditions, customized for each role, ii. offering live training, iii. delivering digital training and hand-holding, and iv. facilitating tracking pregnancies and management of HRPs. Equipping health workers (HWs) on these interventions facilitates early identification, effective management, and timely referrals, ultimately improving primary care and satisfaction of mothers with HRPs. Stated interventions are implemented in the intervention arm for 18 months, while during this period, HWs of intervention and control arms will receive routine training through state and national programs, ensuring pregnant women have equal access to routine maternity services. Objective: At the system level, the program evaluates the impact on improvement in the knowledge and skills of HWs in diagnosing and managing HRPs. At the community level, it assesses the translation of this knowledge and into practice, in terms of early diagnosis and effective management, among women with HRPs. Methods: The program will be implemented in two intervention districts (Sambhal and Shravasti) and two matched control districts (Baduan and Gonda) of Uttar Pradesh, on six HRPs. Study uses a ‘quasi-experimental, before-and after trial design’, with intervention and control arms. However, impact of program will be assessed only on three HRPs: moderate/severe anaemia, pregnancy-induced hypertension, and antepartum haemorrhage (APH), including placenta previa/abruptio placenta. System level impacts will be assessed through qualitative data collected from district officials, specialist gynaecologists, MOs and ANMs, at baseline and endline. Community level outcomes will be measured quantitatively using baseline and endline data from recently delivered women (RDW), with or without HRPs. Results: The impact evaluation protocol was approved by ARMMAN’s Scientific Review Board and Sigma’s Institutional Review Board. The protocols for six HRP-conditions were vetted by the government of Uttar Pradesh. By November 2024, all the ANMs, MOs, specialist gynaecologists, staff nurses, and community health officers in two intervention districts were trained on six HRP-protocols. Digital learning tool and WhatsApp support system was also introduced to facilitate continued learning and handholding of ANMs in managing HRPs and/or to clear doubts. Pre-intervention/baseline data was collected from two arms, during June-October 2024. Conclusions: This trial will provide valuable insights into the feasibility and effectiveness of the program, at system and community levels, in a low resource setting like Uttar Pradesh. If successful, these insights can feed into capacitating HWs, at scale, in all the districts on diagnosis and management of HRPs, with significant potential for improving maternal and neonatal outcomes of the state.

  • Examining Possible Relationship of Online Engagement on Older Adults’ Subjective Memory Capability: Path Analysis

    From: JMIR Human Factors

    Date Submitted: Feb 23, 2025

    Open Peer Review Period: Mar 26, 2025 - May 21, 2025

    Background: The utility of online engagement in enhancing quality of life and mitigating social isolation among older adults is well-documented. However, its effects on cognitive functions, mainly thr...

    Background: The utility of online engagement in enhancing quality of life and mitigating social isolation among older adults is well-documented. However, its effects on cognitive functions, mainly through online social engagement, require further exploration. Objective: This study investigates the potential of active online engagement via a Virtual Senior Center (VSC) to enhance subjective memory capability among older adults, thereby potentially improving their psychological well-being and loneliness. Methods: Utilizing a cohort of 53 homebound older adults participating in the VSC program, which offers diverse online classes to promote social interaction, using path analysis to investigate the relationship between online engagement, subjective memory capabilities, the quality of social relationships, and overall well-being. Results: The findings reveal that increased participation in VSC activities is significantly associated with improved subjective memory capability. Conclusions: This enhanced self-assessment of memory capability is linked to a better quality of life and reduced loneliness. Although online engagement has no direct association, these indirect effects suggest the critical role of positive subjective memory capability, fostered through online engagement, in enriching social interactions. It posits the potential of digital platforms to augment traditional methods of socialization, especially for those contending with physical or geographical barriers to interaction.

  • Interpretable Machine Learning Model for Pulmonary hypertension Risk Prediction: a retrospective cohort study

    From: JMIR Medical Informatics

    Date Submitted: Mar 18, 2025

    Open Peer Review Period: Mar 26, 2025 - May 21, 2025

    Background: Pulmonary hypertension (PH) is a progressive disorder characterized by elevated pulmonary artery pressure and increased pulmonary vascular resistance, ultimately leading to right heart fai...

    Background: Pulmonary hypertension (PH) is a progressive disorder characterized by elevated pulmonary artery pressure and increased pulmonary vascular resistance, ultimately leading to right heart failure. Early detection is critical for improving patient outcomes. Objective: To establish a novel machine learning-based diagnostic model for PH. Methods: A diagnostic model for the early detection of pulmonary hypertension (PH) was developed through a two-step approach. First, Recursive Feature Elimination (RFE) was employed to select the most relevant echocardiographic variables, which were subsequently integrated into a composite ultrasound index using machine learning techniques such as XGBoost. In the second step, this ultrasound index was integrated with clinical variables identified through LASSO regression. Together, these elements were combined to construct a logistic regression model for diagnosis. The model’s performance was rigorously evaluated using ROC curves, calibration plots, and decision curve analysis (DCA) to ensure its clinical relevance and accuracy. Results: Machine learning identified key echocardiographic and clinical predictors, with the XGBoost model achieving high AUC, sensitivity, and specificity. LASSO regression identified critical clinical variables, including prothrombin time activity and serum cystatin C. The diagnostic model demonstrated high predictive accuracy, with an AUC of 0.997. Calibration and decision curve analyses indicated close alignment between predicted and observed outcomes validating the model’s clinical value, especially at higher risk thresholds. Conclusions: This model enhances early pulmonary hypertension (PH) diagnosis through a non-invasive approach and demonstrates strong predictive accuracy. It facilitates early intervention and personalized treatment, with potential applications in broader cardiovascular disease management. Clinical Trial: The study was approved by the Research Ethics Commission of Wuhan Zhongnan Hospital and the requirement for informed consent was waived by the Ethics Commission (Approval No.2023185)

  • Evaluating the Role of Marine Protected Areas (MPAs) in Enhancing Biodiversity and Supporting Sustainable Economic Growth in the Blue Economy

    From: JMIR Preprints

    Date Submitted: Mar 26, 2025

    Open Peer Review Period: Mar 26, 2025 - Mar 11, 2026

    Background: Marine ecosystems face increasing threats from overfishing, pollution, and climate change, leading to biodiversity loss and habitat degradation. Marine Protected Areas (MPAs) serve as a st...

    Background: Marine ecosystems face increasing threats from overfishing, pollution, and climate change, leading to biodiversity loss and habitat degradation. Marine Protected Areas (MPAs) serve as a strategic conservation tool to mitigate these impacts while supporting economic sustainability. However, their effectiveness varies based on governance structures, enforcement mechanisms, and financial sustainability. This study evaluates the role of MPAs in enhancing biodiversity conservation and fostering sustainable economic growth within the blue economy. Objective: This study aims to assess the impact of MPAs on biodiversity, fisheries, and eco-tourism, identify governance and enforcement challenges, and propose actionable policy recommendations to enhance their ecological and economic effectiveness. By analyzing global case studies, the study provides data-driven insights to strengthen participatory governance, financial sustainability, and adaptive management strategies. Methods: A systematic review methodology was employed, following PRISMA guidelines. Data was collected from peer-reviewed journals, book chapters, and reputable databases, focusing on empirical studies evaluating MPAs' ecological and economic impacts. The analysis was structured around three core components: ecological outcomes, economic benefits, and governance frameworks. Selected case studies, including the Great Barrier Reef, Tanzania’s Coastal MPAs, Mediterranean MPAs, Lekki Conservation Centre, and Niger Delta MPAs, were examined to illustrate the diversity of MPA impacts and governance challenges. Results: Findings indicate that well-managed MPAs enhance biodiversity by increasing species richness, apex predator recovery, and habitat restoration. Economically, MPAs contribute significantly to fisheries sustainability and eco-tourism revenues, fostering job creation and local economic resilience. However, governance challenges such as weak enforcement, inadequate funding, and limited community engagement hinder MPA effectiveness. Participatory governance models and revenue-sharing mechanisms improve conservation outcomes and stakeholder compliance. Conclusions: MPAs play a vital role in maintaining marine biodiversity and supporting sustainable economic development. Effective governance, stringent enforcement, and stable financial mechanisms are crucial to maximizing their benefits. Scaling up MPA coverage, integrating adaptive management strategies, and fostering multi-stakeholder collaborations are essential for long-term success. Future MPA development should prioritize participatory governance, innovative financing strategies, and science-based conservation planning. Strengthening enforcement through technology, investing in local capacity-building, and aligning MPAs with broader economic policies will enhance their impact. International collaborations and policy integration should be leveraged to improve MPA management worldwide. This study underscores the importance of MPAs as a conservation and economic sustainability tool. By protecting critical marine habitats, MPAs contribute to climate resilience, biodiversity preservation, and global food security. Strengthening their governance and financial sustainability will ensure their effectiveness in mitigating environmental threats while promoting sustainable blue economy initiatives.

  • AI Paradox in Higher Education: Understanding Over-Reliance, its Impact, and Sustainable Integration

    From: Journal of Medical Internet Research

    Date Submitted: Mar 25, 2025

    Open Peer Review Period: Mar 25, 2025 - May 20, 2025

    Background: The rapid development of artificial intelligence (AI) has significantly reshaped the landscape of higher education. While AI offers transformative potential, increasing reliance on these t...

    Background: The rapid development of artificial intelligence (AI) has significantly reshaped the landscape of higher education. While AI offers transformative potential, increasing reliance on these tools by educators raises concerns related to teaching autonomy, decision-making, and the erosion of pedagogical identity. Most existing research has been conducted in Western or Chinese contexts, with limited exploration of cross-cultural perspectives. Objective: This study aimed to: (1) explore the underlying causes of educators’ overreliance on AI; (2) investigate the impact of this reliance on teaching autonomy, professional decision-making, and long-term pedagogical practices; and (3) identify challenges associated with AI dependency while proposing strategies to foster balanced AI integration. Methods: A qualitative research design was employed. Data were collected from a total of 46 participants through semi-structured interviews and focus group discussion sessions. Participants were selected to represent diverse medical sciences backgrounds and institutional contexts. Thematic analysis was used to interpret the data and identify recurring patterns and themes. Results: The analysis revealed several key factors contributing to educators' AI dependency, including pressure to maintain academic reputation, low self-efficacy in adapting to new teaching demands, and institutional policies encouraging AI adoption. The consequences of this dependency included professional skill atrophy, increased procrastination, and reduced interpersonal engagement, leading to social fragmentation within academic communities. However, participants also acknowledged the potential of hybrid intelligence and the value of integrating AI into teaching in a balanced and reflective manner. Conclusions: The study highlights the nuanced implications of AI reliance in higher education, emphasizing the need for intentional, balanced approaches to AI use that preserve human agency and pedagogical integrity. Although the sample size was limited, the findings offer valuable insights and set the stage for future research across broader and more diverse educational contexts.AI dependency, Generative AI, procrastination, AI reliance, hybrid intelligence

  • A Novel Framework of Multi-Domain Behavioral Change Agents to Coach Chronic Disease Patients Towards Achieving Personalized Health Goals

    From: JMIR Formative Research

    Date Submitted: Mar 12, 2025

    Open Peer Review Period: Mar 25, 2025 - May 20, 2025

    Background: Unhealthy lifestyle behaviors have been identified as a major cause of numerous health issues with a steady global increase. Addressing this challenge requires comprehensive behavioral cha...

    Background: Unhealthy lifestyle behaviors have been identified as a major cause of numerous health issues with a steady global increase. Addressing this challenge requires comprehensive behavioral changes to promote sustainable healthier lifestyle adoption. However, despite the prevalent need, cost effective and successful health-related behavior change virtual coaching, remain scarce. Objective: This paper presents a holistic framework for designing, modeling and executing behavioral change strategies, through a multi-agent reasoning system that selects optimal virtual coaching techniques based on individual assessments and integrates data-driven decision making. Methods: Behavioral change theories have been explored to design a multi-agent system that aims to achieve sustainable lifestyle changes. This system selects behavior change techniques (BCTs) based on individual user assessments, prioritizing those with the strongest impact on key behavioral components. The framework incorporates evidence-based practices stemming from behavioral change science and integrates them into Healthentia Behavioral Change Coaching (BCC) scheme. Healthentia, a certified software as medical device (SaMD), implements this framework specifically for chronic disease management, serving as an eHealth solution advancing decentralized care by enabling remote monitoring, data-driven content selection and personalized virtual coaching that adjusts to patient progress and engagement patterns. Results: This paper explores the application of the Healthentia BCC scheme in Type 2 diabetes patients and presents preliminary results that show improvements in weight (-2.53 kg, p=0.0352), BMI (-0.925 kg/m², p=0.0348), and trends toward improvement in fasting glucose and sleep goal fulfillment. The positive outcomes are at least partly attributed to the personalized delivery of content, 85% of which is well-received by the patients. Conclusions: Our study of this multi-agent system, tested through simulated patient behavior and a preliminary, limited Type 2 diabetes patient behavior observations, promises improved health outcomes using personalized virtual coaching strategies. Future directions include optimization of the multi-agent selection process, a further exploration of the Type 2 diabetes program and an in-depth evaluation of its results, including HbA1c measurements, and an applications’ expansion to other chronic conditions.

  • Iterative LLM-Guided Sampling and Expert-annotated Benchmark Corpus for Harmful Suicide Content Detection

    From: JMIR Medical Informatics

    Date Submitted: Mar 12, 2025

    Open Peer Review Period: Mar 25, 2025 - May 20, 2025

    Background: Harmful suicide content on the internet poses significant risks, as it can induce suicidal thoughts and behaviors, particularly among vulnerable populations. Despite global efforts, existi...

    Background: Harmful suicide content on the internet poses significant risks, as it can induce suicidal thoughts and behaviors, particularly among vulnerable populations. Despite global efforts, existing moderation approaches remain insufficient, especially in high-risk regions like South Korea, which has the highest suicide rate among OECD countries. Previous research has primarily focused on assessing the suicide risk of individuals rather than the harmfulness of content itself, highlighting a gap in automated detection systems for harmful suicide content. Objective: In this study, we aimed to develop an AI-driven system for classifying online suicide-related content into five levels: illegal, harmful, potentially harmful, harmless, and non-suicide-related. Additionally, the researchers construct a multi-modal bench- mark dataset with expert annotations to improve content moderation and assist AI models in detecting and regulating harmful content more effectively. Methods: We collected 43,244 user-generated posts from various online sources, including social media, Q&A platforms, and online communities. To reduce the workload on human annotators, GPT-4 was used for pre-annotation, filtering and categorizing content before manual review by medical professionals. A task description document ensured consistency in classification. Ultimately, a benchmark dataset of 452 manually labeled entries was developed, including both Korean and English versions, to support AI-based moderation. The study also evaluated zero-shot and few-shot learning to determine the best AI approach for detecting harmful content. Results: The multi-modal benchmark dataset showed that GPT-4 achieved the highest F1 scores (66.46 for illegal and 77.09 for harmful content detection). Image descriptions improved classification accuracy, while directly using raw images slightly decreased performance. Few-shot learning significantly enhanced detection, demonstrating that small but high-quality datasets could improve AI-driven moderation. However, translation challenges were observed, particularly in suicide-related slang and abbreviations, which were sometimes inaccurately conveyed in the English benchmark. Conclusions: This study provides a high-quality benchmark for AI-based suicide content detection, proving that LLMs can effectively assist in content moderation while reducing the burden on human moderators. Future work will focus on enhancing real-time detection and improving the handling of subtle or disguised harmful content.

  • A Human-Centered Baby Massage Mobile Application to Enhance Growth and Development in Infants with Low Birth Weight: A Study in Indonesia

    From: JMIR Pediatrics and Parenting

    Date Submitted: Feb 26, 2025

    Open Peer Review Period: Mar 25, 2025 - May 20, 2025

    Background: Low birth weight (LBW) is linked to higher risks of neonatal morbidity, developmental delays, and long-term health issues. Although baby massage has been proven to enhance growth and neuro...

    Background: Low birth weight (LBW) is linked to higher risks of neonatal morbidity, developmental delays, and long-term health issues. Although baby massage has been proven to enhance growth and neuro-developmental outcomes in LBW infants, access to suitable training and compliance with massage regimes continue to be challenges, especially in low-resource settings. Mobile health (mHealth) interventions represent a novel solution for addressing these challenges through the provision of scalable and standardized education in Baby Massage. Objective: This study aimed to design and test a human-centered baby massage mobile application (app) to promote the growth and development of LBW infants in Indonesia. Methods: We used a human-centered iterative design framework to create the mobile application. System Usability Scale (SUS) was used to assess the usability of the application among 42 caregivers of LBW infants. Feedback was collected qualitatively through semi-structured interviews, and thematic analysis was applied to understand user experience. A pilot study assessed the impact of the application on caregiver knowledge, confidence, adherence to baby massage practices, and infant growth outcomes. Weight pre- and post-intervention assessments were compared using paired t-tests. Results: The mobile application was found to have high usability, evidenced by an average SUS score of 78.6 (SD = 8.2). The majority of participants (85%) rated the app as "excellent" or "good" with respect to ease of use and navigation. Qualitative feedback emphasized its effectiveness at increasing caregiver confidence and its cultural relevance. Statistical analyses from the pilot study showed significant gains in caregiver knowledge (+20.5 points, p < 0.01), confidence (+21.6 points, p < 0.01), and adherence to baby massage practices (+20.3 points, p < 0.05). Statistically significant weight (+330 grams, p < 0.01) and head circumference (+1.3 cm, p < 0.01) improvement was observed in infants in the intervention group. Conclusions: The human-centered baby massage mobile application showed promising evidence of feasibility and effectiveness in increasing knowledge, confidence, and adherence to baby massage practices by caregivers. The application features a culturally tailored and user-friendly design, which makes it accessible, especially in low-resource settings. This was a small-scale study and future work should involve scaling the intervention as well as evaluating the long-term effects on infant health outcomes.

  • User requirements to develop an artificial intelligence assisted tool that identifies patients with multimorbidity and complex polypharmacy to improve the process of medication reviews

    From: Journal of Medical Internet Research

    Date Submitted: Mar 25, 2025

    Open Peer Review Period: Mar 25, 2025 - May 20, 2025

    Background: Background: Structured Medication Reviews (SMRs) are an essential component of medication optimisation, especially for patients with multimorbidity and polypharmacy. However, the process r...

    Background: Background: Structured Medication Reviews (SMRs) are an essential component of medication optimisation, especially for patients with multimorbidity and polypharmacy. However, the process remains challenging due to the complexities of patient data, time constraints, and the need for coordination between healthcare professionals (HCPs). This study explores HCPs perspectives on the integration of AI-assisted tools to enhance the SMR process, with a focus on the potential benefits and barriers to adoption. Objective: Objective: To identify the key user requirements for AI-assisted tools to improve the efficiency and effectiveness of SMRs, specifically for patients with multimorbidity, complex polypharmacy and frailty. Methods: Methods: A qualitative study was conducted involving focus groups and semi-structured interviews with HCPs and patients in the UK. Participants included doctors, pharmacists, clinical pharmacologists, psychiatrists from primary and secondary care, a policy maker, and patients with multimorbidity. Data were analysed using a hybrid inductive and deductive thematic analysis approach to identify themes related to AI-assisted tool functionality, workflow integration, user-interface visualisation, and usability in the SMR process. Results: Results: Four major themes emerged from the analysis: Innovative AI Potential; Optimising Electronic Patient Record Visualisation; Functionality of the AI tool for SMRs; Facilitators and Barriers to AI Tool Implementation. HCPs identified the potential of AI to support patient identification and prioritising those at risk of medication-related harm. AI-assisted tools were viewed as essential in detecting prescribing gaps, drug interactions, and patient risk trajectories over time. Participants emphasised the importance of presenting patient data in an intuitive format, with a patient interface for shared-decision making. Suggestions included colour-coding blood results, highlighting critical medication reviews, and providing timelines of patient medical histories. HCPs stressed the need for AI tools to integrate seamlessly with existing electronic patient record systems and provide actionable insights without overwhelming users with excessive notifications or ‘pop-up’ alerts. Factors influencing the uptake of AI-assisted tools included the need for user-friendly design, evidence of tool effectiveness, though some were sceptical about the predictive accuracy of AI models, and addressing concerns around digital exclusion. Conclusions: Conclusion: The findings highlight the potential for AI-assisted tools to streamline and optimise the SMR process, particularly for patients with multimorbidity and complex polypharmacy. However, successful implementation depends on addressing concerns related to workflow integration, user acceptance, and evidence of effectiveness. User-centred design is crucial to ensure that AI-assisted tools support HCPs in delivering high-quality, patient-centred care while minimising cognitive overload and alert fatigue.

  • Overdose-Related Trends in Online Search Behavior in Japan: An Analysis Using Infodemiological Methods

    From: Journal of Medical Internet Research

    Date Submitted: Mar 25, 2025

    Open Peer Review Period: Mar 25, 2025 - May 20, 2025

    Overdoses of medications, including over-the-counter (OTC) and prescription drugs, have increased in Japan, with digital platforms contributing to inappropriate use patterns. This study analyzed overd...

    Overdoses of medications, including over-the-counter (OTC) and prescription drugs, have increased in Japan, with digital platforms contributing to inappropriate use patterns. This study analyzed overdose-related online search trends by using data from Yahoo! JAPAN between 2020 and 2024. Search volume for “overdose” increased approximately fivefold, from 89,800 in 2020 to 240,000 in 2024. Female individuals accounted for 52.67%-72.11% of the users who conducted overdose-related searches. The most frequently searched medication class (36.6%) in the context of overdose was benzodiazepines. Furthermore, compounds contained in OTC drugs accounted for approximately 11.8% of all medication-related searches. These findings reveal a concerning trend in medication overdose risk in Japan and underscore the importance of developing targeted prevention strategies based on the digital surveillance of online search patterns.

  • Self-health Monitoring by Smart Devices and Ontology Technology for Older Adults with Uncontrolled Hypertension: Quasi-Experimental Studies

    From: JMIR Nursing

    Date Submitted: Mar 3, 2025

    Open Peer Review Period: Mar 25, 2025 - May 20, 2025

    Background: Hypertension is a prevalent concern among older adults, and when left uncontrolled, it can lead to complex cardiovascular complications. Tele-nursing technology facilitates self-management...

    Background: Hypertension is a prevalent concern among older adults, and when left uncontrolled, it can lead to complex cardiovascular complications. Tele-nursing technology facilitates self-management, empowering older adults with uncontrolled hypertension to regulate their behaviors and achieve sustainable disease control. Objective: This study aimed to study the effects of self-health monitoring using smart devices and ontology technology on disease-controlling behavior and mean arterial pressure of older adults with uncontrolled hypertension. Methods: The design was quasi-experimental research. The sample was older adults with uncontrolled hypertension who lived in Bangkok, Thailand, which was divided into 46 experimental people and 45 control people. The implementation tools were a program of self-health monitoring using smart devices and ontology technology. It featured the "HT GeriCare@STOU" application on smartphones that was linked to detecting blood pressure from smartwatches, and telenursing could be provided through the application and video calls. The data-collecting questionnaires had a Cronbach's alpha coefficient of 0.83 and a content validity index of 0.98 for disease-controlling behavior. Descriptive and t-test statistics analyzed the data. Results: The results revealed that after joining the program, the disease-controlling behavior of older adults with uncontrolled hypertension was better than before joining the program, but was not better than the comparison group at P<.05. However, the mean arterial pressure of older adults with uncontrolled hypertension was lower than before joining the program and lower than the comparison group at P<.05. Conclusions: A program of self-health monitoring using smart devices and ontology technology was effective for older adults with uncontrolled hypertension. The technological and cost problems are potential obstacles to eHealth programs. More experimental and longitudinal studies with larger sample sizes are needed to properly evaluate this program. Clinical Trial: Trial Registry Number: Thai Clinical Trials Registry (TCTR20250110003)

  • A Comprehensive Profiling System Integrating MBTI and DISC for Personalized Health Training: A Correlational Analysis and Usability Evaluation

    From: JMIR Human Factors

    Date Submitted: Mar 3, 2025

    Open Peer Review Period: Mar 25, 2025 - May 20, 2025

    Background: This study proposes an integrated approach to developing personalized health behavior change programs by combining personality traits and behavior types. Existing tools like MBTI and DISC...

    Background: This study proposes an integrated approach to developing personalized health behavior change programs by combining personality traits and behavior types. Existing tools like MBTI and DISC have limitations: MBTI reflects internal tendencies but lacks behavioral insights, while DISC highlights behavior but overlooks deeper personality aspects. To address these gaps, the study integrates MBTI and DISC to create a comprehensive profiling system. Objective: The goal of this research is to design a novel profiling system that merges MBTI and DISC for personalized health management. This system aims to link personality traits with behavior patterns to enhance the effectiveness of tailored health behavior change programs. Methods: The study involved three phases: administering MBTI and DISC tests to 130 participants to analyze correlations, developing an integrated survey for health behavior analysis, and testing its usability with 20 experts for validation. Results: Significant correlations were observed between MBTI and DISC indicators, including a notable negative correlation between Thinking-Feeling (T/F) and Dominance (D), suggesting an inverse relationship between decision-making preferences and assertiveness. Usability testing results indicated high participant satisfaction, with an average SUS score of 86.0, exceeding industry benchmarks for system usability. Expert evaluations further reinforced the system’s practical applicability, highlighting its potential to enhance user engagement through personalized behavioral insights. Conclusions: This study presents a combined MBTI and DISC profiling system, offering both theoretical insights and practical tools for health behavior change programs. Future research should validate its effectiveness with larger samples and explore broader applications in various health domains.

  • Impacts of Environmental Distractions and Interruptions on Unsupervised Digital Cognitive Assessments in Older Adults: A cognitive ecological momentary assessment study

    From: JMIR mHealth and uHealth

    Date Submitted: Feb 17, 2025

    Open Peer Review Period: Mar 25, 2025 - May 20, 2025

    Background: Unsupervised cognitive assessments are becoming commonly used in studies of aging and neurodegenerative diseases. Because assessments are completed in everyday environments and without a p...

    Background: Unsupervised cognitive assessments are becoming commonly used in studies of aging and neurodegenerative diseases. Because assessments are completed in everyday environments and without a proctor, there are concerns about how common distractions may impact performance and whether these distractions may differentially impact those experiencing the earliest symptoms of dementia. Objective: We examined the impact of location and social context, and self-reported interruptions on remote cognitive assessments in older adults. Methods: Participants from the Ambulatory Research in Cognition (ARC) smartphone study were classified as cognitively normal (N = 380) or as having very mild dementia (N = 37). Participants completed daily tests of processing speed, working memory, and associate memory. At each assessment, participants were asked to report on their current location and social surroundings, which was used to quantify if participants were either at home (or not) and by themselves (or not). After each assessment session, participants were asked if they experienced any interruptions. Mixed effect modeling was used to test the interactions between location, social context, and clinical status. Additional analyses were conducted by removing sessions where participants reported that they were interrupted at any point during the testing period. Results: Across all participants, momentary effects of environmental distractions were minimal. Specifically, when tests were completed in the presence of others, participants exhibited slightly increased variability in processing speed. However, these momentary effects of environmental distractions were dependent upon cognitive status. Cognitively normal older adults had better visuospatial working memory performance when they completed tests at home compared to when they completed tests away from home. However, older adults with very mild dementia showed no effect of testing location on the same task. Conversely, cognitively normal older adults did not differ in their processing speed at either testing location. Older adults with very mild dementia were slightly faster when not at home. Social context only impacted variability in processing speed for participants with very mild dementia. When considering tests completed in the most distracting environments (away from home and in the presence of others) those with very mild dementia showed larger differences only on the visuospatial working memory measure. Additional analyses demonstrated that after removing sessions in which participants self-reported experiencing an interruption (~12% of assessments), these small effects of environmental distractions on cognition remained, but were more apparent in those with very mild dementia. Conclusions: Social context and location of unsupervised remote cognitive testing has small impacts on performance, but these impacts were not consistent across cognitive domains and were mostly limited to participants demonstrating the earliest symptoms of dementia. Remote cognitive testing provides valid and reliable data in older adults, but care should be taken to allow participants to report distractions that may occur during testing.

  • The Effect of Mindful Breathing Virtual Reality with Biofeedback on Stress and Symptom Severity in Breast Cancer Patients Undergoing Chemotherapy: Randomized Controlled Trial

    From: Journal of Medical Internet Research

    Date Submitted: Feb 28, 2025

    Open Peer Review Period: Mar 25, 2025 - May 20, 2025

    Background: Breast cancer patients undergoing chemotherapy often experience high levels of stress and symptom burden. Mindful breathing virtual reality with biofeedback may offer an effective non-pha...

    Background: Breast cancer patients undergoing chemotherapy often experience high levels of stress and symptom burden. Mindful breathing virtual reality with biofeedback may offer an effective non-pharmacological intervention for stress management, yet its efficacy remains underexplored. Objective: This study evaluated the effect of mindful breathing virtual reality with biofeedback in reducing stress and symptom severity in breast cancer patients undergoing chemotherapy. Methods: A three-arm parallel randomized controlled trial was conducted from August to November 2023 at a medical center in Taiwan. A total of 82 participants were randomly assigned to the mindful breathing virtual reality group (n = 25), the mindful breathing audio training group (n = 28), and the control group (n = 29). Outcomes included stress, symptom severity, and physiological features such as electroencephalography, heart rate variability, respiratory signals, and galvanic skin response. Machine learning analyses were used to identify stress response patterns. Results: Participants in the mindful breathing virtual reality group showed a significant reduction in stress level (p < .05) and symptom severity (p < .001) compared to the other groups. Additionally, physiological features demonstrated improvements in electroencephalography, heart rate variability, respiratory signals, and galvanic skin response. Machine learning analyses further confirmed the superior accuracy of the mindful breathing virtual reality intervention in detecting and differentiating stress responses. Conclusions: Mindful breathing virtual reality effectively reduces stress and symptom severity in breast cancer patients undergoing chemotherapy, with measurable physiological benefits. These findings highlight the potential of virtual reality as an innovative, non-pharmacological intervention to support stress management in oncology care. Clinical Trial: This study was registered on ClinicalTrials.gov under the identifier NCT06541587.

  • Clinician perceptions of a novel multicomponent digital Care Assistant and support Program for people after Stroke or transient ischaemic attack (CAPS) for secondary prevention of stroke: a qualitative study

    From: JMIR Human Factors

    Date Submitted: Feb 19, 2025

    Open Peer Review Period: Mar 25, 2025 - May 20, 2025

    Background: We co-designed a novel multicomponent Care Assistant and support Program for people after Stroke or transient ischaemic attack (CAPS) to augment secondary prevention of stroke. Objective:...

    Background: We co-designed a novel multicomponent Care Assistant and support Program for people after Stroke or transient ischaemic attack (CAPS) to augment secondary prevention of stroke. Objective: Following completion of a feasibility study, we sought feedback from Australian clinicians and service provider representatives (the potential deliverers of CAPS) regarding their perceptions of CAPS for secondary prevention, and pathways to real-world adoption. Methods: Qualitative descriptive study of clinicians and service provider representatives involved in delivery of stroke care around Australia. A pragmatic convenience sample was obtained from previous CAPS co-design study participants, leveraging professional networks (e.g., LinkedIn), and distributing study flyers and newsletters via Primary Healthcare Networks, General Practitioner (GP) networks, and social media posts (CSIRO LinkedIn pages). Semi-structured interviews and focus groups were conducted virtually with clinicians and representatives of the Stroke Foundation (Australia). Data were thematically analysed using an integrated approach. Results: Three Stroke Foundation representatives and eighteen clinicians participated, from five Australian states, including medical specialists, GPs, nurses, and allied health professionals. We collected their perceptions of CAPS, including potential benefits of the program for secondary prevention, and considerations for facilitators and challenges to real-world program implementation. Discussion regarding the perceived benefits focussed more on the benefits to patients than to clinicians. Program implementation sub-themes included program initiation and duration, patient support considerations; and workflow alignment, which included consideration of barriers and enablers to uptake within primary care practice and Stroke Foundation outreach support programs. Conclusions: There was support from participants for the potential of CAPS to improve secondary prevention of stroke. However, addressing the challenges raised by participants including further implementation and integration considerations, such as sustainability of the model of care, are likely required for CAPS to be successfully embedded within clinical settings.

  • A digitally supported person-centered, integrated and proactive care system. What does it look like, and how do we get there? A qualitative study of healthcare system stakeholder perspectives.

    From: Journal of Medical Internet Research

    Date Submitted: Mar 24, 2025

    Open Peer Review Period: Mar 25, 2025 - May 20, 2025

    Background: In the face of the demographic change, patients, authorities, and professionals express a need to radically reorganize health services for patients with long-term and complex needs (CLNs)...

    Background: In the face of the demographic change, patients, authorities, and professionals express a need to radically reorganize health services for patients with long-term and complex needs (CLNs) to maintain sustainability and quality of care. In line with policy recommendations, the Patients and Professionals in Partnership (3P)-project transition from reactive, single-disase, profession-centric care to digitally supported Person-centered, Integrated, and Proactive (Digi-PIP)-care. In this paper we collected insights from a wide stakeholder group associated with 3P, representing those who use, work for, or shape the Norwegian care system. Objective: To answer the following research questions: • What do stakeholders understand by the terms digitally supported, Person-centered, Integrated, and Proactive care? • How do we transform care towards Digi-PIP care? Methods: This research was a collaborative effort involving observations and co-creation in 4 Workshops, with 104 stakeholders representing patients, informal caregivers, professionals at all levels of care, healthcare decision-makers, e-health providers, and health service researchers from four innovation hubs in Norway and Denmark. Participants worked in groups, each creating three oral poster presentations of their discussions and insights. A condensed summary of the 45 filmed presentations was the basis for an inductive/deductive content analysis structured by the research questions. Results: A wide range of healthcare stakeholders recognize Person-centered, Integrated, and Proactive as intuitive, critical and synergistic features of high-quality and sustainable care. Stakeholders agreed on the essence of the three concepts: • Person-centered care (PCC) is guided by the patient’s answer to the What Matters To You? (WMTY?) question. • Integrated care recognizes the patient journey as a team product that requires a digital shared information flow. • Proactive care is key to sustainability. It builds on a prioritized shared care plan, which supports patient involvement and engagement for realistic self-care and “WMTY?”-goals. In addition, proactive care involves the active use of health data, sensors and algorithms to identify opportunities for prevention/ early treatment. Stakeholders suggested a wide range of innovations to transition to Digi-PIP care: • Education and training to support professionals in the delivery of person-centered care. • New organizational roles and logic to reduce care fragmentation. • A shared digitized information flow to enable all contributors to be aware of personal goals, shared care plans, and risk-reduction strategies. Conclusions: Stakeholders agreed on what Person-centered, Integrated, and Proactive care is and found these features useful in describing sustainable high-quality patient journeys. Transforming care requires multiple synergistic innovations in education, organization, and digital information systems. There is a need for further research into the regulatory and economic support of such innovation

  • ChatGPT-Assisted Deep Learning Models for Influenza-Like Illness Prediction in Mainland China

    From: Journal of Medical Internet Research

    Date Submitted: Mar 24, 2025

    Open Peer Review Period: Mar 25, 2025 - May 20, 2025

    Background: Background While deep learning shows potential for influenza forecasting, implementation complexity persists. Large language models like ChatGPT enable automated code generation and model...

    Background: Background While deep learning shows potential for influenza forecasting, implementation complexity persists. Large language models like ChatGPT enable automated code generation and model optimization, potentially lowering technical barriers in epidemiological research. Objective: To evaluate the effectiveness of deep learning models in predicting Influenza-Like Illness (ILI) positive rates in Mainland China and explore the utility of ChatGPT as a development assistant in model construction and optimization. Methods: ILI positive rate data spanning from 2014 to 2024 were obtained from the Chinese CDC database. Five deep learning architectures, Long Short-Term Memory (LSTM), Neural Basis Expansion Analysis for Time Series (N-BEATS), Transformer, Temporal Fusion Transformer (TFT), and Time-series Dense Encoder (TiDE), were implemented with ChatGPT's assistance for code generation, debugging, and optimization. Models were trained on data from 2014 to 2023 and evaluated on 2024 data (weeks 1-39) using Mean Squared Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) metrics. Results: ILI cases in China exhibited clear seasonal patterns withwinter peaks and summer troughs, showing marked fluctuations during 2020-2022. TIDE demonstrated superior performance nationally (MAE = 5.551, MSE = 43.976, MAPE = 72.413%) and in southern China (MAE = 7.554, MSE = 89.708, MAPE = 74.475%). Northern region predictions were challenging across all models, with TIDE still performing best (MAE = 4.131, MSE = 28.922) despite high percentage errors (MAPE > 400%). ChatGPT significantly accelerated model development through automated code generation and optimization suggestions. Conclusions: Deep learning models, particularly TIDE, show promise for ILI forecasting in China, with performance varying by region. Large language models like ChatGPT can substantially enhance research efficiency in epidemic prediction modeling, offering a scalable approach for public health preparedness.

  • Effect Size and Associated Factors of Digital Shams on Generalized Anxiety Symptoms: Systematic Review and Meta-Analysis

    From: Journal of Medical Internet Research

    Date Submitted: Mar 24, 2025

    Open Peer Review Period: Mar 24, 2025 - May 19, 2025

    Background: Digital therapeutics (DTx) have attracted attention as the substitutes or add-ons to conventional pharmacotherapy. The number of clinical trials for DTx has increased recently and one of t...

    Background: Digital therapeutics (DTx) have attracted attention as the substitutes or add-ons to conventional pharmacotherapy. The number of clinical trials for DTx has increased recently and one of the main targets for DTx is psychiatric disorders. Generalized Anxiety Disorders (GAD) is one of the most common and notable psychiatric disorders and it’s known that the magnitude of placebo effect in the pharmacotherapy is quite large. The randomized clinical trials (RCTs) with digital shams are the most reliable clinical trials to evaluate the safety and efficacy of DTx. However, the effect size and the associated factors of digital shams on GAD have not been investigated although they are critical to assess the true treatment effect of DTx. Objective: The objectives of this study were to identify RCTs with digital shams as comparators which evaluated GAD assessment scores, to review the characteristics of the RCTs and of the digital shams in the systematic review, and to investigate the effect size and the associated factors in the meta-analysis. Methods: The RCTs evaluating the GAD assessment scores by setting digital shams as comparators were identified by searching the database of PubMed, Web of Science and Scopus in July 2024. The characteristics of the RCTs and of the digital shams were reviewed systematically. The meta-analysis including sub-group analyses and meta-regressions were conducted to investigate the effect size and the associated factors of the digital shams. Results: 54 RCTs were included in the systematic review and 32 RCTs with 3 GAD assessment scores were included in the meta-analysis with a total of 5311 participants. The pooled effect size of digital sham for all the included studies was large (Hedge’s g=0.28, 95% CI 0.18 to 0.38). The sub-group analyses showed the significant difference in the effect size among target population (p=.03), sham approach (p=.02) and baseline values (p=.02). The meta-regressions also indicated that the primary psychiatric patients in the target population (p=.01), removed type in sham approach (p=.04) and high baseline values (p=.02) were associated with the effect size of digital shams. Conclusions: This study showed the large effect size of digital shams on GAD assessment scores, which is consistent with the large placebo effect in pharmacotherapy. Target population, sham approach and baseline values were also identified as the associated factors of the effect size. It would be effective to create the study protocols for the DTx trials with digital shams by considering the factors identified in this study.

  • Interactive Affordance of Integrative Internet Social Media Platform Use by Patients and Physicians: A Mixed-Method Approach

    From: Journal of Medical Internet Research

    Date Submitted: Mar 24, 2025

    Open Peer Review Period: Mar 24, 2025 - May 19, 2025

    Background: Integrative internet social media platform (IISMP) integrates the features of mobile and social media technologies as well as the legacy healthcare systems to support healthcare processes...

    Background: Integrative internet social media platform (IISMP) integrates the features of mobile and social media technologies as well as the legacy healthcare systems to support healthcare processes for patients and physicians that enables patient-centered care. To better understand the use of IISMP, especially the digital interactions between patients and physicians, we develop the concept of interactive affordance and use a mixed-method approach to identify and present the interactive affordance patterns based on patient event logs, physician-patient online consultation conversation texts, interviews, and focused group from a large hospital. Objective: This study proposes a new type of affordance, referred to as interactive affordance, which represents the interactions between physician and patient when they both use IISMP for providing care to the patient. We identify interactive affordance patterns and investigate their impacts on organizational changes in the healthcare context. Methods: We use a mixed-method approach to analyze various data collected from both primary and secondary sources. The data includes 45,147 archival healthcare event logs, 13,332 conversation texts, 15 interviews, and eight focus groups data from a large hospital that has implemented an IISMP. We use grounded theory analysis, process mining, text mining, and social network analysis to identify interactive affordance patterns and their impacts on healthcare processes and outcomes. Results: Based on the results from text mining, processing mining, social network, and ground coding analysis, we identify virtual healthcare consultation between patient and physician using IISMP as interactive affordance. The analysis results from the mixed-method approach confirm that interactive affordance, virtual consultation affordance, of IISMP use contributes to the changes in the communication and decision-making processes between patients and physicians. The virtual consultation affordance promotes patient-centered care by increasing patient's access to care, empowerment, and engagement. Conclusions: The concept of interactive affordance is proposed as a new type of affordance to represent the interactions between patients and physicians emergent by using IISMP in healthcare organizations. This new affordance type explains organizational changes toward patient-centered care.

  • Determinants of Inquiry Responses in Nonprofit Mental Health Forums: An Interpretable Machine Learning Approach

    From: Journal of Medical Internet Research

    Date Submitted: Mar 23, 2025

    Open Peer Review Period: Mar 24, 2025 - May 19, 2025

    Background: In recent years, there has been a noticeable increase in individuals seeking psychological assistance and therapeutic interventions through virtual mental health platforms. The increasing...

    Background: In recent years, there has been a noticeable increase in individuals seeking psychological assistance and therapeutic interventions through virtual mental health platforms. The increasing demands and contributions of users constitute pivotal elements underpinning the development of these online psychological communities. Nevertheless, limited attention has been given to the quality and quantity of information exchange within these virtual mental health forums. Objective: The primary objective of this study is to investigate the determinants influencing user inquiries and response volumes to queries within virtual mental health forums. This study aims to provide empirical data and theoretical underpinnings, as well as suggestions, to improve the service of online mental health communities. Methods: This study employs a pretrained deep learning-based natural language processing model named BERT to conduct a thematic analysis of the content in the inquiry and response sections of online mental health communities. In addition, sentiment analysis is performed based on a sentiment dictionary. We then utilize a machine learning method (LightGBM) for predictive analysis of the response volumes. Furthermore, the SHAP analytical technique is employed to better explain the determinants of response behavior. Results: The findings indicate that user inquiries can be categorized into seven themes: job, love, depressive moods, relationships, school, marriage, and family. The sentiment analysis reveals that topics related to 'relationships' and 'marriage' are associated with positive emotions and high view counts and contribute positively to the number of replies. Conversely, topics such as 'romance' and 'depression' usually carry neutral or adverse emotional tones and negatively impact response rates. Notably, posts with sufficiently high levels of positive or negative emotions tend to receive a higher number of responses. Conclusions: This study has both theoretical and practical implications for advancing the contribution of user knowledge in online mental health communities, as well as for improving the quality of services provided by these communities.

  • Assessing the Quality of Artificial Intelligence Explanations on Atrial Fibrillation: A Comparative Analysis of ChatGPT and Google Gemini

    From: JMIR Formative Research

    Date Submitted: Mar 10, 2025

    Open Peer Review Period: Mar 24, 2025 - May 19, 2025

    Background: Atrial fibrillation (AF), a common arrhythmia, is a major stroke risk factor, making patient education critical. Artificial intelligence (AI) platforms like Google Gemini and ChatGPT are e...

    Background: Atrial fibrillation (AF), a common arrhythmia, is a major stroke risk factor, making patient education critical. Artificial intelligence (AI) platforms like Google Gemini and ChatGPT are emerging tools for medical education. Objective: This study aimed to (1) assess the quality of ChatGPT and Google Gemini’s explanations of AF and its treatment, (2) compare responses from both platforms and (3) analyze differences in interpretation between cardiologists and non-medical professionals. Methods: On September 6, 2024, the prompt “Explain atrial fibrillation and how to treat it to a patient” was entered into ChatGPT and Google Gemini. A survey based on PEMAT-P and DISCERN criteria was completed by 11 cardiologists and 17 non-medical professionals. Averages and standard deviations were calculated and compared using the Wilcoxon signed-rank test. Results: No significant quality difference was observed between ChatGPT and Google Gemini. Cardiologists rated bias lower (3.82 vs. 4.33, p=0.04) and explanations of consequences of no treatment higher (2.85 vs. 1.86, p=0.005) compared to non-medical professionals. Visual cues, informative headers, concise sections, actionable advice, and direct addressing of the reader received significantly higher ratings from cardiologists. Conclusions: The comparable quality of ChatGPT and Google Gemini suggests that both are viable for AF education. Cardiologists’ higher ratings for critical aspects of explanation highlight a gap in patient understanding, underscoring the need for clearer AI-driven educational tools. Clinical Trial: n/a

  • Does a Higher than Standard-Intensity INR Goal Benefit Patients with MAVR and Additional Thrombotic Risk Factors: A Protocol for Systematic Review and Meta-analysis

    From: JMIR Research Protocols

    Date Submitted: Mar 21, 2025

    Open Peer Review Period: Mar 24, 2025 - May 19, 2025

    Background: Lifelong anticoagulation with vitamin K antagonists is required to prevent prosthetic valve thrombosis after mechanical aortic valve replacement (MAVR). Current guidelines recommend a stan...

    Background: Lifelong anticoagulation with vitamin K antagonists is required to prevent prosthetic valve thrombosis after mechanical aortic valve replacement (MAVR). Current guidelines recommend a standard international normalized ratio (INR) of 2.5 for MAVR patients without additional thromboembolic risk factors, while a higher INR of 3.0 is advised for those with conditions such as atrial fibrillation, prior thromboembolism, or left ventricular dysfunction. However, limited clinical data exist to validate the optimal anticoagulation intensity for this high-risk population, necessitating further investigation. Objective: This systematic review and meta-analysis aim to assess the risks and potential benefits of higher-intensity anticoagulation goals (INR>3.0) in MAVR patients with additional thromboembolic risk factors. Methods: A comprehensive literature search will be conducted, including case studies, randomized controlled trials (RCTs), and follow-up studies published before December 18, 2024. The study population includes MAVR patients on Warfarin therapy, with and without additional thromboembolic risk factors. Studies involving bioprosthetic valves, non-bileaflet mechanical valves, and patients not on Warfarin will be excluded. Data will be extracted and analyzed following PRISMA guidelines, with statistical comparisons evaluating thromboembolic and bleeding events. Results: The study follows a structured timeline: protocol development was completed in December 2024, with the search strategy finalized in January 2025. Screening stages (title, abstract, and full-text) span February to May. Data extraction, synthesis, and risk of bias assessment occur in May and June, followed by data analysis and manuscript drafting from July to August. Submission and peer review are scheduled for September 2025. Conclusions: This systematic review will provide critical insights into anticoagulation management in MAVR patients with thromboembolic risk factors. Given the scarcity of targeted research, these findings may inform future guideline revisions, balancing thrombotic prevention with bleeding risks. Further prospective studies will be needed to validate these conclusions. Clinical Trial: CRD42025639037

  • A Social Support Just-In-Time Adaptive Intervention for Individuals with Elevated Depressive Symptoms: A Feasibility Study with Micro-Randomized Trial Design

    From: JMIR Mental Health

    Date Submitted: Mar 18, 2025

    Open Peer Review Period: Mar 24, 2025 - May 19, 2025

    Background: Just-In-Time Adaptive Interventions (JITAIs) aim to provide psychological support during critical moments in daily life. Objective: This preregistered study evaluated the feasibility of a...

    Background: Just-In-Time Adaptive Interventions (JITAIs) aim to provide psychological support during critical moments in daily life. Objective: This preregistered study evaluated the feasibility of a social support JITAI for individuals with elevated depressive symptoms awaiting psychotherapy. Triggered by Ecological Momentary Assessment (EMA) reports, the intervention encouraged participants to activate their (digital) social support networks. Methods: Twenty-five participants completed 2,689 EMAs and received 377 JITAIs over an 18-day intervention period, including a micro-randomized trial design to compare four strategies to trigger an intervention: Fixed cutoff points of distress variables, personalized thresholds (through Shewhart Control Charts) of distress variable, momentary support need, and no intervention. Results: The results showed high feasibility, with participants completing 85% of EMA surveys, low study-related attrition rate (7%), and reporting minimal technical issues. Engagement and perceived helpfulness were heterogenous and moderate, with participants seeking support in one-third of triggered instances. JITAIs triggered by self-reported need for support were rated as more appropriately timed, helpful, and effective for promoting support-seeking behavior compared to those based on distress indicators, despite being triggered less frequently. Barriers such as time constraints and perceived unavailability of support providers likely affected support seeking behavior, as indicated by additional qualitative analyses. Exploratory effectiveness analyses indicate Cohen’s d effect sizes between 0.06 - 0.14 in reducing distress after JITAIs were received. Conclusions: These findings demonstrate that a social support JITAI is feasible to implement, with high compliance and minimal technical issues. Yet, further research is needed to evaluate the JITAI’s effectiveness and to optimize trigger strategies in addressing individual needs and barriers to engagement.

  • Validation of the mjn-SERAS medical device for the early detection of epileptic seizures in refractory epilepsy patients in a normalised environment: Protocol for a prospective, multicentre, controlled and randomized, pilot clinical study

    From: JMIR Preprints

    Date Submitted: Mar 24, 2025

    Open Peer Review Period: Mar 23, 2025 - Mar 8, 2026

    Background: Approximately one third of epilepsy patients are resistant to anti-seizure medication (ASM). There are currently no mobile devices that allow early detection of seizures. Hypothesized that...

    Background: Approximately one third of epilepsy patients are resistant to anti-seizure medication (ASM). There are currently no mobile devices that allow early detection of seizures. Hypothesized that the use of an intra-aural EEG device (mjn-SERAS) will allow the activity recording and the subsequent processing by the AI algorithm of MJN to anticipate the event of suffering an epileptic seizure in those patients already diagnosed previously, generating an alert to prevent accidents. Objective: To assess the epilepsy-related quality of life in patients with drug-resistant epilepsy using the mjn-SERAS solution compared to the control group To assess the seizure-related safety in patients with drug-resistant epilepsy using the mjn-SERAS solution compared to the control group in terms of the number of accidents caused by seizure episodes Methods: A prospective, multicentre, pilot clinical trial, with a controlled and randomized design, is proposed to validate a medical device (mjn-SERAS), CE certificated. This new validation will be in the participant's normalized environment, in individuals over 2 years of age, with a diagnosis of refractory epilepsy, which will make it possible to determine the impact of the mjn-SERAS device on the early detection of epileptic seizures and the generation of a pre-seizure alert with a time window of a minimum of 1 minute. The sample size determined is an n=150 exposed individuals who meet the inclusion criteria. The sensitivity, specificity, positive predictive value, PPV and F-Score of the device will be analysed. Also, the degree of satisfaction of patients and their caregivers, including the impact on quality of life and the degree of health perceived by the caregiver when alarms are generated to assess the possibility of a new epileptic seizure. Finally, to describe possible improvements in indicators of social relationships in different areas of personal development. Results: This study is funded in 2022 by the EIT Health and European Union, under the programme EIT Health Amplifier n. 220445-230126. As of February 2025, we enrolled 76 patients in 6 clinical sites in Spain, UK and Germany. Data analysis is currently underway, and the first results are expected for June 2025. Conclusions: The mjn-SERAS device, an intra-aural EEG, aims to record brain activity and use artificial intelligence (AI) algorithms to anticipate seizures in previously diagnosed patients. By generating early alerts, it allows individuals to take preventive measures and enhance safety. Although participants may not experience direct benefits, validating or improving this technology could enhance future epilepsy management and treatment. Unlike previous research efforts, mjn-SERAS is the first device to systematically provide seizure alerts using an AI-based algorithm to detect early warning signs. Its real-world application could significantly improve the quality of life for epilepsy patients and advance medical understanding of seizure prediction. This study evaluates the device’s accuracy in predicting seizures in everyday settings and assesses its psychological, mental, and social impact on people with refractory epilepsy. Clinical Trial: ClinicalTrials.gov NCT05845255; https://clinicaltrials.gov/study/NCT05845255

  • Examining the Multi-Faceted Determinants influencing the Adoption of Diabetes Mobile Apps: Content Analysis and Regression Analysis

    From: JMIR Preprints

    Date Submitted: Mar 23, 2025

    Open Peer Review Period: Mar 23, 2025 - Mar 8, 2026

    This research paper presents a comprehensive analysis of the factors influencing the adoption and user satisfaction of diabetes mobile health apps. This work evaluates six (6) machine learning regress...

    This research paper presents a comprehensive analysis of the factors influencing the adoption and user satisfaction of diabetes mobile health apps. This work evaluates six (6) machine learning regressors and employs Ordinary Least Squares (OLS) multiple regression, including a polynomial regression extension, for hypothesis testing. It is important to note that this research is novel in its use of various machine learning regression models to explore the determinants influencing the adoption of diabetes mobile apps, while also considering the user experience journey. By employing machine learning algorithms, particularly a Stacked Model with Ridge Regression, the study identifies developer reputation, usability, update frequency, and cost as significant determinants of app downloads—a proxy for adoption rates. The Stacked Model's superior predictive accuracy is evidenced by its result of achieving the lowest RMSE (0.4212) and highest adjusted R² (0.9586) outperforming other models such as Random Forest and XG- Boost. Additionally, user feedback analysis sheds light on the varying levels of user dissatisfaction across different UX stages, with the highest discontent observed during the Churn stage, despite fewer reported pain points. The study's findings are supported by permutation feature importance analysis, F-statistics, and p-values. Key insights reveal that while update frequency may not greatly influence downloads, ease of use and developer reputation significantly impact user adoption rates. Furthermore, the research delves into business models, revealing that 'Free' and 'Freemium' models are particularly effective in the app market, while regional factors, such as those about Taiwan, also play a crucial role in adoption. Recommendations from the study stress the importance of addressing technical glitches, enhancing connectivity and integration with health devices, providing educational content, and focusing on user-centric design. Finally, the paper underlines the need for such a complex approach in app design that puts users’ requirements first and proposes to improve the predictive modeling for real-time solutions.

  • Comparative Efficacy of Tyrosine Kinase, MAPK, and PI3K/AKT/mTOR Inhibitors in Ovarian Cancer: A Meta-Analysis

    From: JMIR Preprints

    Date Submitted: Mar 23, 2025

    Open Peer Review Period: Mar 23, 2025 - Mar 8, 2026

    Background: Traditional treatments frequently have little effect on advanced stages of ovarian cancer, which continues to be a leading cause of cancer-related death among women. Tyrosine kinase inhibi...

    Background: Traditional treatments frequently have little effect on advanced stages of ovarian cancer, which continues to be a leading cause of cancer-related death among women. Tyrosine kinase inhibitors (TKIs), inhibitors of the MAPK pathway, and inhibitors of the PI3K/AKT/mTOR pathway are examples of targeted therapies that have become attractive therapeutic alternatives. Objective: The purpose of this meta-analysis is to evaluate how well these inhibitors work to treat ovarian cancer. Methods: A thorough search of the literature was conducted for studies published between January 2018 and September 2023 using PubMed, Embase, and the Cochrane Library. Trials that assessed TKIs, MAPK, or PI3K/AKT/mTOR inhibitors in patients with ovarian cancer and reported at least one of the following outcomes—clinical benefit rate (CBR), overall response rate (ORR), progression-free survival (PFS), or overall survival (OS)—were considered. I² statistics were used to assess heterogeneity, and random-effects models were used to synthesize data. Results: There were 23 studies total with 1,832 patients in the analysis. With a pooled CBR of 63% (P < 0.01), MAPK inhibitors displayed the best efficacy; in low-grade serous carcinoma (LGSC), their CBR raised to 85% (95% CI: 79–90%). Whereas PI3K/AKT/mTOR inhibitors had the lowest CBR at 32% (95% CI: 20–44%), TKIs attained a CBR of 52% (95% CI: 44–60%). A pooled ORR for TKIs was not available; the ORR for MAPK inhibitors was 13% and for PI3K/AKT/mTOR inhibitors was 3%. Limited PFS and OS data suggested possible advantages with TKIs and MAPK inhibitors. Conclusions: In ovarian cancer especially in LGSC, MAPK pathway inhibitors proved to be more effective than TKIs and PI3K/AKT/motor inhibitors. These results underline the need of histological and molecular profiling for customizing therapy. Nevertheless, considerable variation and insufficient long-term data emphasize the need of more study to maximize focused treatment plans in ovarian cancer.

  • Twelve tips for engaging medical educators to harness generative artificial intelligence (GenAI)

    From: JMIR Medical Education

    Date Submitted: Mar 22, 2025

    Open Peer Review Period: Mar 22, 2025 - May 17, 2025

    Generative artificial intelligence (GenAI) offers transformative potential for medical education, reshaping education, teaching, learning, research, administrative tasks, and patient care. This articl...

    Generative artificial intelligence (GenAI) offers transformative potential for medical education, reshaping education, teaching, learning, research, administrative tasks, and patient care. This article presents 12 actionable tips for medical educators to integrate GenAI into teaching practices effectively. After collecting own ideas and topics, the free versions of various GenAI providers like OpenAI (ChatGPT 4.o) Perplexity AI Inc. (Perplexity), and SuSea, Inc. (You.com) were used to get more creative input for the selection of possible tips and items, which should be discussed in the appropriate tip-section. All items were finally discussed and refined by all authors. As useful fields of application, we identified the following use cases: cultivating GenAI literacy, learning and teaching improvement, curriculum development, research, priming GenAI integration in healthcare, promote ethical awareness in the use of GenAI, use GenAI to support diversity and equity, spread the word about GenAI, promote transprofessional collaboration between healthcare professionals and experts, streamline administration with GenAI, and know GenAI limitations. Each tip includes challenges, practical examples with essential actions, and practices that educators should avoid. These guidelines aim to help educators leverage GenAI technologies to improve educational outcomes and better prepare future healthcare professionals. In addition, this article provides a blueprint to adapt the inverted classroom model as the new normal and suggests to found learning and teaching primarily on evidence-based methods.

  • Mobile phone access, usage patterns and perceptions of adolescents living with HIV on the use of gamified interventions to improve ART adherence in Eswatini: Qualitative study

    From: JMIR mHealth and uHealth

    Date Submitted: Mar 19, 2025

    Open Peer Review Period: Mar 21, 2025 - May 16, 2025

    Background: Adolescents living with HIV (ALHIV) often experience poor anti-retroviral therapy (ART) outcomes due to multiple barriers affecting medication adherence. Effective self-care interventions...

    Background: Adolescents living with HIV (ALHIV) often experience poor anti-retroviral therapy (ART) outcomes due to multiple barriers affecting medication adherence. Effective self-care interventions are needed to address these challenges. Mobile phones are widely used by the adolescent population, thus present an opportunity to be used as a tool to enhance ART adherence using mobile phones as a targeted intervention. However, research on ALHIV's mobile phone access, usage patterns, and perceptions of mobile phone-based interventions is limited in Eswatini. Objective: This study explored the mobile phone access, usage patterns, and perceptions of mobile phone-based interventions among ALHIV in Eswatini to inform effective mobile health strategies for enhancing ART adherence among ALHIV. Methods: We conducted a qualitative study using in-depth interviews in the month of December 2023. A total of 29 ALHIV aged 10 to 19 years and enrolled on ART were purposively sampled were interviewed from five Teen Clubs in the Hhohho region in Eswatini. Topic areas covered were “mobile phone accessibility, usage patterns, and perceptions on the use of mobile phones to facilitate ART adherence.” Results: The study findings indicated high mobile phone access among participants, with primary usage focused on making and receiving calls, as well as engaging with social media. Three themes emerged regarding the use of gamified interventions to support ART adherence. Firstly, the use of gamified interventions aimed at ART adherence among ALHIV was deemed feasible, based on mobile phone access and past experiences with mobile game. Secondly, three main qualities of successful gamified interventions were identified as: being supportive, educational, and ensuring privacy in the design of the game. Lastly, confidentiality and mobile phone access factors were highlighted as potential concerns when designing gamified ART adherence interventions. Conclusions: The findings suggest potentially high access and usage of mobile phones among ALHIV on ART in Eswatini. This provides an opportunity to leverage mobile technology to enhance ART adherence through gamified interventions. However, it is essential to carefully consider ALHIV-specific needs and concerns in the design of these interventions to ensure their successful uptake and sustainability.

  • Effects of the violence prevention intervention TERMA in forensic psychiatric inpatient care: protocol for an observational study

    From: JMIR Research Protocols

    Date Submitted: Mar 21, 2025

    Open Peer Review Period: Mar 21, 2025 - May 16, 2025

    Background: Aggression and violence are prevalent in forensic psychiatric inpatient care. These behaviours significantly impact treatment outcomes, work environments for staff, and strain relationship...

    Background: Aggression and violence are prevalent in forensic psychiatric inpatient care. These behaviours significantly impact treatment outcomes, work environments for staff, and strain relationships among patients and caregivers. Managing such behaviours poses a formidable challenge that necessitates innovative approaches and evidence-based interventions. Objective: The aim of this project is to evaluate the violence prevention method Therapeutic Meeting with Aggression (TERMA) regarding perceived safety by patients and staff and adverse events within forensic psychiatric inpatient care. Additionally, the project will investigate whether the organisational culture affect the implementation of the TERMA method. Methods: The project includes an observational study with a before and after design. Implementation of TERMA consists of an eight-seminar staff training program. Data sources include questionnaires, medical records, and registries. Quantitative data will be analysed with descriptive and comparative statistics. The project will also include qualitative interview studies. Results: Participant enrollment began in February 2024 and will continue through 2025. Data collection and analysis are expected to be completed by early 2026, after which the study findings will be submitted for publication in peer-reviewed scientific journals. Conclusions: Patients and staff at a forensic psychiatry inpatient facility in Western Sweden. Clinical Trial: NCT05932108

  • Translation and Cultural Adaptation of the MYCaW® Questionnaire into German (Project iSWOP): Protocol for the Questionnaire Translation and Validation

    From: JMIR Research Protocols

    Date Submitted: Mar 21, 2025

    Open Peer Review Period: Mar 21, 2025 - May 16, 2025

    Background: The growing population of cancer survivors faces persistent physical and emotional challenges that significantly impact health-related quality of life (HRQL). To address these multifaceted...

    Background: The growing population of cancer survivors faces persistent physical and emotional challenges that significantly impact health-related quality of life (HRQL). To address these multifaceted needs, robust and culturally adapted patient-reported outcome measures, such as the Measure Yourself Concerns and Wellbeing (MYCaW®) questionnaire, are essential for understanding and improving survivors’ subjective experiences. Objective: This protocol outlines the systematic translation and cultural adaptation of the Measure Yourself Concerns and Wellbeing (MYCaW®) questionnaire into German. The MYCaW® questionnaire, a patient-reported outcome measure, is designed to capture individualized concerns and assess overall well-being, particularly in cancer care settings. By adhering to common guidelines, this research will provide a tool for assessing individualized concerns and patient needs among German-speaking cancer patients. Methods: The present study is approved by the ethics committee of the Medical Association Berlin with the reference number Eth-27/10. Following International Society for Pharmacoeconomics and Outcomes Research (ISPOR) guidelines, this study will employ a structured methodology involving forward and backward translation, expert review, patient review process, and preliminary validation to ensure linguistic and cultural equivalence. A standardized coding framework will be developed for analyzing patient concerns, with inter-rater reliability assessed to ensure consistency. Results: The trial is ongoing, with recruitment expected to conclude in the second quarter 2025 and follow-up by year-end. Data analysis is planned for the third quarter 2025, with findings published in the fourth quarter 2025. Results will be presented at conferences, submitted to journals, and the study will conclude in December 2025. The final German MYCaW® version is expected to maintain the conceptual integrity of the original while being accessible and meaningful for German-speaking oncology patients. Conclusions: The translation and adaptation of MYCaW® into German will contribute to expanding the availability of validated patient-reported outcome measures for German-speaking populations. By following rigorous international guidelines, this study aims to produce a reliable and culturally appropriate tool for assessing patient concerns and well-being in oncology and supportive care settings. Future validation studies will be necessary to assess the psychometric properties of the adapted questionnaire and its applicability in clinical and research contexts. Potential challenges, such as maintaining conceptual equivalence in translation and ensuring broad representativeness in the validation process, will be addressed through iterative refinement. Once validated, the German MYCaW® will provide a valuable resource for patient-centered research and care, helping to capture individualized concerns that might be overlooked by standardized instruments. Clinical Trial: The study is registered at the German Register for Clinical Trials under DRKS00013335 on 27/11/2017.

  • End user and primary care physicians’ perspectives on digital innovations in dementia risk detection: A focus on a digital sleep biomarker

    From: JMIR Aging

    Date Submitted: Mar 21, 2025

    Open Peer Review Period: Mar 21, 2025 - May 16, 2025

    Background: Dementia is a global health priority. Early identification of dementia in asymptomatic or mildly symptomatic individuals (i.e. dementia risk detection) is proposed as a clinical solution f...

    Background: Dementia is a global health priority. Early identification of dementia in asymptomatic or mildly symptomatic individuals (i.e. dementia risk detection) is proposed as a clinical solution for early intervention and could support researchers to identify novel neuropathological targets and recruit to clinical trials. Digital biomarkers of behavioral or physiological markers, such as sleep, are cited as a potential low-cost, non-invasive, and objective methods for dementia risk detection. Understanding perspectives on digital biomarkers, particularly acceptability, from potential end users and clinical staff is required when considering implementation within any clinical service. With emerging evidence of sleep as a risk marker for dementia, efficacy of the Dementia Research Institute – Sleep Index (DRI-SI), based on continuous remote monitoring of sleep patterns detected by a digital sleep mat, for dementia risk detection is currently being explored by the InSleep46 study. Objective: This qualitative sub-study aimed to explore perspectives of potential end users and primary care physicians regarding the use of a digital sleep mat to measure the DRI-SI and its application towards dementia risk detection. Methods: 31 potential end users (age: 31-82 years, 11:20 female: males) from Newcastle and London, UK, with personal or caregiving experience related to dementia, took part in qualitative focus group workshops. They shared opinions on integrating the sleep mat into their homes, the DRI-SI’s potential for identifying dementia risk, and the necessary information for engagement with related clinical services. Seven primary care physicians from across England participated in semi-structured interviews regarding the potential application of the DRI-SI in dementia risk detection and its integration into current clinical practice. Inductive thematic analysis was conducted to identify key themes. Results: Four key themes emerged from end user focus groups: 1) Practical use, 2) Acceptability, 3) Clinical management, and 4) Data concerns. Three main themes came from the semi-structured interviews with physicians: 1) Acceptability, 2) Healthcare Provision, and 3) Practical considerations. Common themes were identified in both groups but held differing perspectives. End users were focused on practical aspects of integrating the digital sleep mat within their daily life, the effect of the DRI-SI on clinical care and privacy concerns regarding data use. Primary care physicians were concerned more broadly with how the DRI-SI and dementia risk detection service would integrate into current clinical practice, the impact on clinical resources and patient wellbeing, and need for clinical actionability and guidance on discussing results with patients. Conclusions: End users would find the DRI-SI acceptable as part of their clinical care, but primary care physicians require a more robust evidence base. Future research should explore integration of the DRI-SI into clinical care/research pathways to enhance clinical acceptability. Five key recommendations have been made for further development of digital biomarkers for dementia risk populations. Clinical Trial: n/a

  • Efficacy and safety of Ayurveda interventions for Primary Open-Angle Glaucoma and Ocular Hypertension in India over the last 40 years: A Systematic Review and Meta-Analysis Protocol

    From: JMIR Research Protocols

    Date Submitted: Mar 20, 2025

    Open Peer Review Period: Mar 21, 2025 - May 16, 2025

    Background: Primary Open-Angle Glaucoma (POAG) and Ocular Hypertension (OHT) are major causes of irreversible blindness globally, with a significant disease burden in India. Conventional treatments pr...

    Background: Primary Open-Angle Glaucoma (POAG) and Ocular Hypertension (OHT) are major causes of irreversible blindness globally, with a significant disease burden in India. Conventional treatments primarily aim at reducing intraocular pressure (IOP) through pharmacological agents, laser therapy, and surgery, but these approaches are often limited by side effects, poor adherence, and disease progression despite optimal IOP control. Ayurveda, the traditional medical system of India, offers therapeutic interventions such as Kriyakalpa (specialized ocular procedures), Panchakarma (purificatory therapies), and herbal or herbo-mineral formulations that may provide a neuroprotective and IOP-lowering effect in POAG and OHT. However, the clinical evidence supporting the efficacy and safety of these interventions remains fragmented and inconsistent. Objective: This systematic review and meta-analysis aim to evaluate and synthesize evidence on the efficacy and safety of Ayurveda interventions for the management of POAG and OHT in various institutes of India over the last 40 years (1984–2024). Methods: A comprehensive search will be conducted in electronic databases, including Cochrane Complementary Medicine Trial Register, Annotated Bibliography of Indian Medicine, Web of Science, MEDLINE via PubMed, PubMed Central, Cochrane Central Register of Controlled Trials, National Institute of Science Communication and Information Resources, Scopus, EMBASE, Directory of Open Access Journals, Google Scholar, and Digital Helpline for Ayurveda Research Abstracts. The search will cover clinical trials, including randomized controlled trials (RCTs), controlled clinical trials (CCTs), observational studies, and single-arm trials. The primary outcome measures will include reduction in IOP, visual field progression, and optic nerve head health. Secondary outcomes will include adverse events associated with Ayurveda interventions. Risk of bias will be assessed using the Cochrane Risk of Bias (RoB 2) tool for RCTs and the Risk of Bias in Non-Randomized Studies of Interventions (ROBINS-I) tool for non-randomized studies. A random-effects model will be used for quantitative synthesis, and a narrative synthesis will be conducted for heterogeneous data. Results: Protocol is developed. Since this is a systematic review protocol, no definitive results are available at this stage. Conclusions: This systematic review will provide comprehensive insights into the role of Ayurveda in managing POAG and OHT, including its therapeutic efficacy and safety. The findings will contribute to the development of clinical guidelines and inform future research on integrative approaches in glaucoma management. Clinical Trial: PROSPERO 2024 CRD42024592392 https://www.crd.york.ac.uk/PROSPERO/view/CRD42024592392

  • Development and Validation of a Large Language Model-Powered Chatbot for Neurosurgery: A Mixed-Methods Study on Enhancing Perioperative Patient Education

    From: Journal of Medical Internet Research

    Date Submitted: Mar 21, 2025

    Open Peer Review Period: Mar 21, 2025 - May 16, 2025

    Background: Perioperative education is crucial for optimizing outcomes in neuroendovascular procedures, where inadequate understanding can heighten patient anxiety and hinder care plan adherence. Curr...

    Background: Perioperative education is crucial for optimizing outcomes in neuroendovascular procedures, where inadequate understanding can heighten patient anxiety and hinder care plan adherence. Current education models, reliant on traditional consultations and printed materials, often lack scalability and personalization. AI-powered chatbots have demonstrated efficacy in various healthcare contexts, but their role in neuroendovascular perioperative support remains underexplored. Given the complexity of neuroendovascular procedures and the need for continuous, tailored patient education AI chatbots have the potential to offer tailored perioperative guidance to improve patient education within this specialty. Objective: The aim of this study is to develop, validate, and assess NeuroBot, an AI-driven system that utilizes large language models (LLMs) with Retrieval-Augmented Generation (RAG) to deliver timely, accurate, and evidence-based responses to patient inquiries in neurosurgery, ultimately improving the effectiveness of patient education. Methods: A mixed-methods approach was employed, consisting of three phases. In the first phase, internal validation, we compared the performance of Assistant API, ChatGPT, and Qwen by evaluating their responses to 306 bilingual neuroendovascular-related questions. The accuracy, relevance, and completeness of the responses were evaluated using a Likert scale, with statistical analyses, including ANOVA and paired t-tests. In the second phase of external validation, ten neurosurgical experts rated the responses generated by NeuroBot using the same evaluation metrics applied in the internal validation phase. The consistency of their ratings was measured using the Intraclass Correlation Coefficient (ICC). Finally, in the third phase, a qualitative study was conducted through interviews with 18 healthcare providers, which helped identify key themes related to the NeuroBot's usability and perceived benefits. Thematic analysis was performed using NVivo, and inter-rater reliability was confirmed through Cohen's Kappa. Results: The Assistant API outperformed both ChatGPT and Qwen, achieving a mean accuracy score of 5.28/6 (95% CI 5.21-5.35), with a statistically significant result (P <.001). External expert ratings for NeuroBot demonstrated significant improvements, with scores of 5.70/6 (95% CI: 5.46-5.94) for accuracy, 5.58/6 (95% CI: 5.45-5.94) for relevance, and 2.70/3 (95% CI: 2.73-2.97) for completeness. Qualitative insights highlighted NeuroBot's potential to reduce staff workload, enhance patient education, and deliver evidence-based responses. Conclusions: NeuroBot, leveraging LLMs with RAG technique, demonstrates the potential of LLMs-based chatbots in perioperative neuroendovascular care, offering scalable and continuous support. By integrating domain-specific knowledge, NeuroBot simplifies communication between professionals and patients, while ensuring patients have 24/7 access to reliable, evidence-based information. Further refinement and research will enhance NeuroBot’s ability to foster patient-centered communication, optimize clinical outcomes, and advance AI-driven innovations in healthcare delivery.

  • Stress and Well-Being Intervention and mHealth Delivery Adaptation for Latinx Millennial Caregivers: A Qualitative User-Centered Approach

    From: JMIR Nursing

    Date Submitted: Mar 14, 2025

    Open Peer Review Period: Mar 20, 2025 - May 15, 2025

    Background: The study aimed to adapt a stress and well-being intervention delivered via a mobile health (mHealth) app for Latinx Millennial caregivers. This demographic, born between 1981 and 1996, re...

    Background: The study aimed to adapt a stress and well-being intervention delivered via a mobile health (mHealth) app for Latinx Millennial caregivers. This demographic, born between 1981 and 1996, represents a significant portion of caregivers in the United States, with unique challenges due to higher mental distress and poorer physical health compared to non-caregivers. Latinx Millennial caregivers face additional barriers, including higher uninsured rates and increased caregiving burdens. Objective: We used a community-informed and user-centered design approach to tailor an existing mHealth app to better meet the stress and well-being needs of Latinx Millennial caregivers. Methods: We employed a two-step, multi-feedback approach. In step one, Latinx Millennial caregivers participated in focus groups to evaluate wireframes for the proposed mHealth app. In step two, participants engaged in usability testing for one week, concluding with short interviews for feedback. Participants were recruited through various channels, including social media and community clinics. Data were analyzed inductively using a rapid qualitative content analysis approach Results: A total of 29 caregivers (69% women, mean age 31) participated in the study. Participants had a mean age of 31 (SD=4.10), with most (n=28, 96%) caring for an adult and one (4%) caring for children with chronic conditions. All participants completed the step one focus groups, with a subset of 3 caregivers completing usability testing in step two. The most liked features included the: 1) stress rating scale because it helped them understand stress and mental health, 2) mindfulness options because it allowed for flexible timing of activities, 3) journaling prompts because it was a way to address daily challenges and contemplate positives, and 4) resource list for its employment and financial content. One concern was that the journaling prompts may take too much time or effort to complete after a long and hard day. Some suggestions for improvement included: a better tracking system, gamification, caregiving education, a checklist of emotions to use on the journal, tailored resources, and ways to connect with a community of similar caregivers. During step two, participants noted the app was user-friendly but had some glitches and unclear privacy policies. Participants liked the meditation options, resource variety, and daily stress log but wanted more journaling space, longer meditations, and additional relaxation activities. Conclusions: Caregivers highlighted the need for tailored resources and additional stress-relief activities. Future iterations should consider integrating more personalized and community-specific resources, leveraging platforms like podcasts for broader engagement, and the use of information-based videos to support caregiver skill acquisition. Caregivers expressed needs beyond the scope of the app, such as resource access, demonstrating the need for upstream and downstream interventions. The study underscores the importance of ongoing user feedback in developing effective mHealth interventions for diverse caregiver populations. Clinical Trial: N/A

  • The Role of Burnout and Health Beliefs in COVID-19 Vaccine Decisions Among Healthcare Workers: A Large Language Model-Based Text Analysis

    From: JMIR Nursing

    Date Submitted: Mar 9, 2025

    Open Peer Review Period: Mar 20, 2025 - May 15, 2025

    Background: Burnout among healthcare workers affects the well-being and decision making, influencing public health outcomes. Understanding the relationship between burnout, health beliefs and COVID-19...

    Background: Burnout among healthcare workers affects the well-being and decision making, influencing public health outcomes. Understanding the relationship between burnout, health beliefs and COVID-19 vaccine decisions among healthcare workers is essential for identifying at-risk staff, providing targeted support, and addressing workplace challenges to prevent further escalation of burnout related issues. Objective: This study examines how burnout, health beliefs, and COVID-19 vaccine decisions among healthcare workers. Building on our previously developed Health Belief Model (HBM) classifier, based on the HBM framework, which explains how individual perceptions of health risks and benefits influence behavior, we focused on key HBM constructs, including the perceived severity of COVID-19, perceived barriers to vaccination, and their relationship to burnout. Methods: We analyzed open-ended comments from 1,501 vaccine-hesitant nurses using data from the Nurses' Health Study surveys. Finetuning Llama3, an open-source Large Language Model with few-shot prompts, we further categorized these comments into burnout dimensions—Emotional Exhaustion, Depersonalization, and Inefficacy—based on the Maslach Burnout Inventory framework. Leveraging Annotation Guidelines-based Knowledge Augmentation and Reasoning-Aware Self-Consistency. Results: The model achieved a high weighted accuracy of 92% and an F1 Score of 91% for Depersonalization. Emotional Exhaustion accounted for 52% of comments, correlating strongly with perceived severity (59%) and barriers to vaccination (43%). Demographic analyses revealed significant variations in burnout prevalence, with older age groups reporting greater burnout. Conclusions: This study highlights the relationship between burnout and vaccine decisions among healthcare workers, uncovering areas for further exploration. By exploring the complex interplay between psychological strain and vaccine hesitancy, this study sets the stage for developing transformative interventions and policies that could redefine workforce resilience and public health strategies.

  • Guideline-based digital exercise interventions for body weight and fat reduction and physical activity promotion in adults with overweight and obesity: A systematic review

    From: JMIR mHealth and uHealth

    Date Submitted: Mar 9, 2025

    Open Peer Review Period: Mar 20, 2025 - May 15, 2025

    Background: Digital exercise interventions are increasingly popular in addressing the obesity epidemic. However, there remains uncertainty on the efficacy regarding the reduction of body weight (BW) a...

    Background: Digital exercise interventions are increasingly popular in addressing the obesity epidemic. However, there remains uncertainty on the efficacy regarding the reduction of body weight (BW) and body fat, which may, at least partly, be due to variations in study designs and inconsistent adherence to international physical activity (PA) guidelines. Objective: This systematic review aimed to evaluate the effectiveness of digital exercise interventions based on PA guidelines in reducing BW and fat in overweight/obese adults, as well as their impact on PA-related factors. Methods: This review was prospectively registered in PROSPERO (CRD42024620020) and conducted following PRISMA guidelines. A series of comprehensive searches was performed in October 2024 across PubMed, Cochrane Library, Web of Science, and OVID Medline. Eligible studies included adults (≥18 years) with objectively confirmed overweight or obesity who utilized digital interventions aligned with international PA guidelines. Risk of bias was evaluated using the Cochrane RoB 2 tool for randomized controlled trials and the ROBINS-I tool for non-randomized studies. Results: Out of 4,948 studies identified through the Boolean search strategy, 188 were retrieved for full-text screening, and 30 studies met the predefined eligibility criteria. Intervention durations ranged from eight weeks to 24 months (average: 6.6 months). Fourteen studies used structured exercise programs, while other studies incorporated flexible PA/exercise routines based on international guidelines. Digital exercise intervention programs resulted in significant reductions in BW (22/25 studies, range: -1.3 to -8.4 kg), body mass index (19/23 studies, range: -0.4 to -3.4 kg/m2), waist circumference (15/16 studies, range: -2.1 to -9.2 cm), body fat percentage (9/9 studies, range: -0.3% to -4.1%), and fat mass (7/7 studies, range: -0.4 to -6.5 kg). Results for waist-to-hip ratio and PA outcomes were inconsistent. Compared to passive controls, results revealed a clear pattern of digital exercise interventions significantly reducing weight- and fat-related outcomes, while results were inconsistent when measured against active or usual care controls. No clear trend was observed between the duration or type of interventions and improvements in the outcome variables. Conclusions: Guideline-based digital PA/exercise interventions show potential in reducing excess body weight and body fat in adults with overweight or obesity, although there remains uncertainty regarding their superiority over traditional methods. Substantial variations in study designs also contribute to challenges in drawing definitive conclusions on specific characteristics of effective digital exercise tools. Clinical Trial: PROSPERO (CRD42024620020)

  • How Medical Student Manage Depression, Anxiety, and Stress: A Cross-Sectional Study

    From: JMIR Formative Research

    Date Submitted: Mar 19, 2025

    Open Peer Review Period: Mar 20, 2025 - May 15, 2025

    This study examines the stress management behaviors of first-year (M1) and second-year (M2) students at an allopathic medical school in California and investigates which activities they employ to mana...

    This study examines the stress management behaviors of first-year (M1) and second-year (M2) students at an allopathic medical school in California and investigates which activities they employ to manage the feelings associated with this stressful period in their academic careers. A total of 120 M1 and 126 M2 students were contacted via email for this study, and 27 responses were collected. Results indicate that M2 students experience higher levels of stress, anxiety, and depression, potentially due to isolation and USMLE Step 1 preparation. Female participants were more likely to read to relax (H(1) = 4.994, p = .025), while M1s preferred socializing (H(1) = 5.081, p = .024) and M2s engaged in painting (H(1) = 4.000, p = .046). This study can thus better inform medical schools about creating multifaceted support systems for their students, which may improve their well-being and better prepare them for the demanding field of medicine.​

  • About EMAeHealth: What do women value in a Maternal Education app?. A sequential mixed-method study on user perspective

    From: JMIR Nursing

    Date Submitted: Mar 6, 2025

    Open Peer Review Period: Mar 19, 2025 - May 14, 2025

    Background: EHealth can help healthcare service users take a more active role in decision-making and help healthcare professionals guide the patient in this process. Even though usability and health l...

    Background: EHealth can help healthcare service users take a more active role in decision-making and help healthcare professionals guide the patient in this process. Even though usability and health literacy strategies should guide the development of mHealth apps, the number of digital health apps publishing their usability evaluation results is still small Objective: The aim of this study was to explore the perceptions of users of the EMAeHealth digital app about its acceptance, usability, strengths and weaknesses for its implementation. Methods: This is an exploratory sequential mixed-method research study, where a qualitative study was followed by a quantitative study. Qualitative results were collected through individual semi-structured interviews between January and March 2024. Participants were identified through purposive sampling. Saturation was reached once 10 interviews had been carried out. In the quantitative part, 106 out of 400 responded to an anonymous online survey created ad hoc in December 2024 based on the results of the qualitative study. Results: Two categories were drawn up during the analysis: (1) “The best thing about this app”, with accessibility, quantity, quality, good organization of the information and the credibility of the source among the reasons for this positive evaluation. (2) “What could be improved”: here, participants considered the app had the potential to become essential if new functions related to healthcare provision were incorporated by linking it to individual health records, as well as making the app more individualized in some different aspects such as receiving notifications. Women commented on the lack of opportunities to share experiences with other women in the same situation and consequently the opportunity to develop networks. The survey gave similar results, with both positive assessments and areas for improvement Conclusions: Although women value the accessibility and reliability of an app designed by the public healthcare service positively, areas for improvement were seen, such as the combination of digital intervention with face-to-face care and, above all, the individualization and adaptation of information, notifications or recommendations to the culture, health situation, or stage of each woman

  • The Effectiveness of Feedback-Integrated and Traditional Adult Basic Life Support Training Methods on Knowledge and Skills Retention Among Healthcare Providers in Clinical Settings: A Systematic Review

    From: JMIR Nursing

    Date Submitted: Mar 5, 2025

    Open Peer Review Period: Mar 19, 2025 - May 14, 2025

    Background: Cardiovascular diseases are the leading global cause of death, with sudden cardiac arrest contributing significantly. Traditional training methods often deteriorate, and feedback-based app...

    Background: Cardiovascular diseases are the leading global cause of death, with sudden cardiac arrest contributing significantly. Traditional training methods often deteriorate, and feedback-based approaches can improve long-term skill retention. Objective: This review assesses the effectiveness of feedback-integrated training compared to traditional Basic Life Support methods in promoting sustained retention of knowledge and skills among healthcare providers in clinical settings. Methods: This systematic review followed PRISMA guidelines, analyzing twelve quasi-experimental and randomized controlled trials published between 2014 and 2024. A comprehensive search was conducted in PubMed, Cochrane Library, Scopus, and Web of Science using keywords related to BLS training and skill retention. Studies were included if they involved healthcare providers, compared feedback-integrated and traditional BLS training, and assessed knowledge or skill retention over time. Excluded studies lacked retention assessments, did not involve healthcare professionals, or were not published in English. Study characteristics, interventions, and outcomes were systematically extracted and synthesized for analysis. Results: Database searches in PubMed, Cochrane Library, Scopus, and Web of Science identified 211 articles, with 98 remaining after removing 113 duplicates. After screening, 55 full-text articles were assessed, and 12 met the inclusion criteria. These studies showed that feedback-integrated training- automated, video-based, and simulation feedback—led to better long-term retention of CPR skills and knowledge among healthcare providers. While traditional methods improved performance initially, skills declined significantly after six months, whereas feedback-integrated training maintained competency for up to twelve months, enhancing compression depth, ventilation quality, and overall resuscitation outcomes. Conclusions: Feedback-integrated Basic Life Support training enhances skill retention and adaptability to diverse clinical settings, requiring future research to evaluate long-term impacts, cost-effectiveness, and comparison with other resuscitation techniques.

  • Interventions to Counter Health Misinformation Among Older People: Protocol for a Scoping Review

    From: JMIR Research Protocols

    Date Submitted: Mar 18, 2025

    Open Peer Review Period: Mar 19, 2025 - May 14, 2025

    Background: In contemporary society, misinformation and disinformation have emerged as significant challenges, impacting various aspects of public health and societal cohesion. Some authors argue that...

    Background: In contemporary society, misinformation and disinformation have emerged as significant challenges, impacting various aspects of public health and societal cohesion. Some authors argue that older adults are particularly vulnerable to the effects of misinformation due to potential digital health literacy challenges. A previous review identified pedagogical approaches most commonly adopted in interventions aiming to improve digital literacy of older adults but did not specifically address digital health literacy. Objective: This scoping review protocol aims to explore digital health literacy interventions targeting health misinformation and designed specifically for older adults. Methods: Following the methodology outlined by Arksey and O'Malley, this protocol delineates a systematic approach encompassing five stages: identification of research questions, identification of relevant studies, selection of studies, data charting, and collation of findings. Our scoping review will include peer-reviewed literature on interventions targeting misinformation for older adults. Research will be conducted on the MEDLINE (OVID), Embase (Elsevier), PsycINFO (OVID), CINAHL, and Web of Science databases. Gray literature will also be surveyed by carrying a Google search to identify interventions and tools employed by public or private organizations, institutes, groups or agencies. The databases and grey literature will be searched to identify relevant publications. 2 members of our team will independently select publications to include in the review using the review software Covidence (Veritas Health Innovation). Publications included will specifically address our research questions, be peer-reviewed, evidence-based, and published from January 1, 2005, in full-text English or French version. Data will be extracted from the included publications to mainly chart, the intervention’s objectives, types, target age groups, effectiveness and risks reported. A thematic analysis will be conducted to categorize the study findings. Results: The research questions were identified in January 2024. The databases and gray literature search strategies were developed in February 2024. Conclusions: This protocol will enable us to contribute to the advancement of knowledge in combating health misinformation among older adults. The results will also be utilized for the development of interventions targeting misinformation among older adults.

  • Feasibility, Safety, and Impact of Lactiplantibacillus plantarum and Bifidobacterium Probiotics In Papua New Guinean Infants: Protocol for a Randomised controlled Trial

    From: JMIR Research Protocols

    Date Submitted: Mar 17, 2025

    Open Peer Review Period: Mar 19, 2025 - May 14, 2025

    Background: Childhood mortality in low- and middle-income countries (LMICs) remains a major public health concern, with infections being a leading cause of infant death. Probiotics have shown promise...

    Background: Childhood mortality in low- and middle-income countries (LMICs) remains a major public health concern, with infections being a leading cause of infant death. Probiotics have shown promise in reducing infection-related morbidity and mortality in preterm infants, but their use in full-term newborns in LMICs requires further investigation. Objective: This study aims to assess the feasibility, safety, and initial outcomes of administering one of two synbiotic formulations or a placebo to newborns in Papua New Guinea's Eastern Highlands Province. Methods: Between November 2020 and June 2023, healthy neonates (< 72 hours old, n=244) were randomly assigned in a double-blinded manner (1:1:1) to receive an oral preparation containing Lactiplantibacillus plantarum, Bifidobacterium longum subspecies infantis, or placebo for 7 consecutive days. Follow-up continued for 6 months, with rectal swabs, stool, blood, saliva, and/or nasopharyngeal swabs collected pre-intervention, on day 7, at 2 weeks, and at 1, 3, 4 and 6 months of age. Ongoing analyses will assess probiotic gut colonisation, bacterial nasopharyngeal carriage, antibody responses to Hib, Hepatitis B, PCV-13, and dTP, as well as hospitalisation and infection rates among intervention groups. Results: Funding and ethical approvals were obtained in 2018 and 2019. Initial synbiotic preparations were received in August 2020, with participant recruitment beginning in November 2020. All follow-up visits concluded in December 2023. Of the enroled infants, 218/244 (89%) completed the full 7-day synbiotic/placebo course, and 169/244 (69%) completed the study. Disruptions due to the COVID-19 pandemic led to family relocations outside the study area, preventing some infants from completing the study. High rates of sample collection were achieved, with >90% of rectal swabs, nasopharyngeal swabs, saliva, and blood samples successfully obtained at multiple time points. Sample analysis is ongoing. Conclusions: This study demonstrates that probiotic supplementation is feasible in full-term infants in an LMIC setting. The findings from this study will inform the need for larger trials of probiotics and synbiotics to complement existing efforts to reduce infection-related infant mortality in LMICs while also providing insights into their clinical, immunological, and microbiological impacts in infants. Clinical Trial: ANZCTR.org.au Identifier: CTRN12620001369910

  • Evaluation of Endometriosis Risk Factors and Clinical Treatments in Bangladesh: A Cross-sectional Study.

    From: Interactive Journal of Medical Research

    Date Submitted: Mar 17, 2025

    Open Peer Review Period: Mar 19, 2025 - May 14, 2025

    Background: Endometriosis is a gynecological condition that involves the implantation of endometrial tissue outside the uterine cavity. About 1.2 million women are suffering from this disease in Bangl...

    Background: Endometriosis is a gynecological condition that involves the implantation of endometrial tissue outside the uterine cavity. About 1.2 million women are suffering from this disease in Bangladesh. Objective: The purpose of this study was to explore the risk factors, symptoms, and clinical treatment in Bangladesh Methods: In this cross-sectional study, out of 162 infertile women 82 had endometriosis confirmed with laparoscopy and 80 were included in the control group. All were asked to fill out a questionnaire containing demographics, reproductive, and menstrual status. Comparisons between the two groups were done using an Independent T-test, Chi-square test, and logistic regression model. Results: The prevalence of endometriosis was higher with, age, marital status, and BMI (P < 0.05). The most common symptoms were dysmenorrhea, excessive bleeding, cramping etc. Infertility (OR:2.21; %95CI: 1.07–4.53; P = 0.03), thyroid imbalance (OR:3.44; %95CI: 1.47–8.03; P = 0.004), irregular menstruation (OR:5.76; %95CI: 2.12–15.60; P = 0.001), age at menarche (OR:2.54; %95CI: 1.04–6.21; P = 0.04) and abortion (OR:2.75; %95CI: 1.31–5.74; P = 0.007) were associated with endometriosis risk. Endometriosis was diagnosed most frequently by TVS (transvaginal ultrasound) at 41.1%, NSAI (nonsteroidal aromatase inhibitors) at 22.8% was the most commonly utilized medicine, and 13.6% of patients undergo laparoscopy. Conclusions: Endometriosis is a considerable public health issue because it affects many women and is associated with significant morbidity. In this study, we developed a model that can be used to predict the risk of endometriosis in infertile women in Bangladesh Clinical Trial: BRAC university Institutional Review Board (IRB) under the IRB number BRACUIRB_220240006

  • Digital Smoking Cessation Preferences of Predominately Lower Income and Latino residents of the San Joaquin Valley in California: A Qualitative Study

    From: JMIR Formative Research

    Date Submitted: Mar 18, 2025

    Open Peer Review Period: Mar 18, 2025 - May 13, 2025

    Background: Although rates of tobacco use in California have declined overall, adults in the San Joaquin Valley (SJV), particularly Hispanic/Latinos (“Latinos”), have disproportionately high rates...

    Background: Although rates of tobacco use in California have declined overall, adults in the San Joaquin Valley (SJV), particularly Hispanic/Latinos (“Latinos”), have disproportionately high rates of tobacco use, tobacco-related illness, and mortality. Residents of the SJV also have limited access to cessation support services, and need accessible, non-clinical alternatives. Given high smartphone use rates among Latinos and residents of rural communities, digital health tools may present an accessible approach to expand cessation support. Objective: This study explored tobacco use behaviors, cessation experiences, and views about digital cessation tools for tobacco cessation among SJV residents. The secondary objective was to assess the appeal, usability, and necessary adaptations of two existing digital smoking cessation tools—a smoking cessation app and a social media-based intervention. Methods: Through a SJV-based academic-community partnership, we recruited 29 predominantly Latino adults who reported current smoking. We conducted four focus groups (two English, two Spanish) to explore tobacco use and cessation experiences, and preferences for smoking cessation tools. Nine participants subsequently completed in-depth interviews where they viewed videos describing two digital smoking cessation tools — a cessation app and a social media intervention — to assess their appeal and usability. Results: Most participants were motivated to quit despite experiencing barriers, emphasizing the need for culturally tailored digital cessation tools to enhance engagement. They preferred interventions that integrated culturally relevant content reflecting lived experiences, featured language-concordant communications, and provided social supports, such as chat rooms for peer connection. While participants appreciated the app’s private interface and comprehensive curriculum, the social-media based program was favored for its engaging design, despite privacy concerns. Preferences for specific interventions varied by age and digital literacy. Material rewards increased appeal to use both digital health tools to quit smoking. Conclusions: This sample of predominantly Latino adults from the SJV expressed favorable interest in digital cessation support, yet existing tools require adaptation to improve cultural relevance, accessibility, and usability. Participants emphasized language-concordant services, representation from people with lived experience, and community-building features. While digital interventions were well received, privacy concerns and digital literacy barriers must be addressed to enhance engagement.

  • Trajectories of Comorbidity between Chronic Physical Illnesses and Mental Health Disorders: a Retrospective Study of an urban population in South China

    From: JMIR Public Health and Surveillance

    Date Submitted: Mar 13, 2025

    Open Peer Review Period: Mar 18, 2025 - May 13, 2025

    Background: As yet the mechanisms that might drive such comorbidity between chronic physical illnesses and mental health disorders have not been fully clarified. Consequently, no effective prevention...

    Background: As yet the mechanisms that might drive such comorbidity between chronic physical illnesses and mental health disorders have not been fully clarified. Consequently, no effective prevention strategies been developed and put in place to reduce risk of complex co-morbidity trajectories. Objective: A clearer understanding of underlying aetio-pathogenic complexity that exists between chronic physical illness and mental health offers an opportunity for improving clinical care of both long-term health conditions and social wellbeing. Methods: In this retrospective study of mental health disorders in people living in the southern region of Guangdong, China, we have conducted an comprehensive analysis on the risk of comorbidity and constructed time-dependent trajectories between chronic physical illnesses and mental health disorders. Results: In this study, electronic health records containing F codes (ICD) from cases over a period of 7 years were included. This contained 268,588 hospital admissions and discharges for 46,649 patients. 26,572 trajectories containing four diagnoses and approximate time duration intervals were identified. In addition, We analyzed the trajectory progression patterns in patient groups of different age groups and gender. These trajectories involved mainly one or more of the three categories of cerebrovascular diseases, organic mental disorders, neurotic stress related and somatoform diseases. Conclusions: This study identified both the differences and commonalities in the disease trajectory and progression patterns of patient groups stratified by age and gender. This provided valuable insight and a preliminary basis for developing early prevention and control strategies of chronic physical illnesses and mental health disorders.

  • Parents’ Perspectives on the Use of Virtual Reality in Pediatric Chronic Pain Management: A Qualitative Study

    From: Journal of Medical Internet Research

    Date Submitted: Mar 17, 2025

    Open Peer Review Period: Mar 17, 2025 - May 12, 2025

    Background: Virtual reality (VR) technology holds significant potential for chronic pain management in children and adolescents by providing an alternative and complementary approach to traditional me...

    Background: Virtual reality (VR) technology holds significant potential for chronic pain management in children and adolescents by providing an alternative and complementary approach to traditional methods of alleviating pain and improving quality of life. Parents play an important role in the successful adoption of VR technologies for children, influencing how children accept, use, and benefit from it. However, little is known about parents’ views on integrating VR technology into pediatric and adolescent chronic pain management. Objective: This study aimed to better our understanding of parents’ perspectives regarding the integration of VR technology into pediatric and adolescent chronic pain management – including barriers, facilitators, and recommendations for future VR technologies. Methods: Semi-structured interviews were conducted with parents of children with chronic pain between March and November 2024. Key aspects of the discussion centered on the acceptability, barriers, and enablers of integrating VR technology into pediatric and adolescent chronic pain management. Interviews were audio-recorded, transcribed, and analyzed through inductive thematic analysis. Results: We conducted 12 interviews. We identified four broad themes from the interview data: (1) views towards integrating VR technology into chronic pain management (perceived benefits, distraction and redirection); (2) barriers to using VR technology for chronic pain management (accessibility, complexity, discomfort and symptom exacerbation); (3) facilitators of integrating VR technology into chronic pain management (addressing financial barriers, integrating VR technology into clinical care, establishing evidence of effectiveness, showcasing positive patient experiences); and 4) recommendations for program content and features (relaxation and mindfulness, physical activity, customization, social connection). Conclusions: Our findings underscore the perceived benefits of integrating VR technology into pediatric and adolescent chronic pain management to enhance physical, social, and mental health and well-being. However, there are several potential challenges that need to be addressed to improve the accessibility of VR technology for use in pediatric and adolescent chronic pain management. Our findings yielded several practical suggestions to guide the development of effective and equitable VR technology for chronic pain management in children and adolescents. Clinical Trial: N/A

  • Personalised interactive music systems for physical activity and exercise: An exploratory systematic review and meta-analysis

    From: JMIR Human Factors

    Date Submitted: Dec 20, 2024

    Open Peer Review Period: Mar 17, 2025 - May 17, 2025

    Background: Personalised Interactive Music Systems (PIMS) are emerging as promising devices for enhancing physical activity and exercise outcomes. By leveraging real-time data and adaptive technologie...

    Background: Personalised Interactive Music Systems (PIMS) are emerging as promising devices for enhancing physical activity and exercise outcomes. By leveraging real-time data and adaptive technologies, PIMS align musical features, such as tempo and genre with users’ physical activity patterns, including frequency and intensity, enhancing their overall experience. Objective: This exploratory systematic review and exploratory meta-analysis evaluates the effectiveness of PIMS across physical, psychophysical, and affective domains. Methods: Searches across nine databases identified 18 eligible studies, of which six (comprising 17 intervention arms) contained sufficient data for meta-analysis. Random-effects meta-analyses and meta-regression were performed to assess outcomes for physical activity levels, physical exertion, ratings of perceived exertion (RPE), and affective valence. Results: Results showed significant improvements in physical activity levels (g = 0.49, CI [0.07, 0.91], p = .02, k = 4) and affective valence (g = 1.68, CI [0.15, 3.20], p = .03, k = 4), with faster music tempo identified as a significant moderator (p = 0.04). No significant effects were observed for RPE (g = 0.72, CI [-0.14, 1.59], p = .10, k = 3) or physical exertion (g = 0.79, CI [-0.64, 2.10], p = .28, k = 5). Conclusions: Substantial heterogeneity and limited study quality indicate the need for more robust, randomised controlled trials to establish the efficacy of PIMS in diverse populations. Clinical Trial: Review registration (CRD42023465941)

  • Effectiveness of wearable device interventions for people with diabetes mellitus: An overview of systematic reviews and Meta-Analyses

    From: JMIR mHealth and uHealth

    Date Submitted: Mar 5, 2025

    Open Peer Review Period: Mar 17, 2025 - May 12, 2025

    Background: Diabetes has become a public health burden worldwide. With the rapid development of the Internet and digital technology, wearable devices play an important role in managing diabetic patien...

    Background: Diabetes has become a public health burden worldwide. With the rapid development of the Internet and digital technology, wearable devices play an important role in managing diabetic patients, and patient demand for them is also on the rise. Objective: This overview evaluates current efficacy evidence regarding wearable technology-driven therapeutic strategies in diabetes management, aiming to establish evidence-based recommendations for clinical practitioners. Methods: The systematic reviews (SRs)/meta-analyses (MAs) of randomized controlled trials of wearable device interventions for diabetic patients from 10 databases were searched from construction to December 21, 2024. Two researchers screened articles, extracted information according to the search formula, and graded the included literature using the Methodological Quality Assessment Tool (AMSTAR-2), the Reporting Quality Assessment Tool (PRISMA 2020), and the Quality of Evidence Assessment Tool (GRADE). Results: This study incorporated 34 SRs/MAs meeting predefined eligibility criteria through rigorous methodological appraisal. The results of the methodological quality evaluation showed that eight articles were of high quality, 13 were of low quality, and 13 were of very low quality. Regarding the assessment of reporting quality, the results of PRISMA 2020 showed that none of the SRs/MAs were fully documented. This methodological quality assessment of 108 evidence bodies across four outcome domains demonstrated evidence stratification: 1 (0.93%) achieving high-quality classification, 20 (18.52%) moderate-grade evidence, 64 (59.26%) meeting low-quality criteria, and 23 (21.30%) designated as critically limited evidence. Conclusions: Wearable device interventions contribute to patients' blood glucose control, exercise management, and prevention of diabetes complications, while their effectiveness in improving quality of life and patient satisfaction requires further validation. Clinical Trial: The review was registered at PROSPERO: CRD42025646643.

  • Time for clarity: Exploring the Evidence and Key Concepts of Human-Centered Design in Digital Healthcare - Scoping Review

    From: JMIR Research Protocols

    Date Submitted: Mar 17, 2025

    Open Peer Review Period: Mar 17, 2025 - May 12, 2025

    Background: Methods such as Human Centered Design (HCD), Design Thinking (DT), User Centered Design (UCD) co-creation, and participatory design (PD) have been adopted to facilitate user and stakeholde...

    Background: Methods such as Human Centered Design (HCD), Design Thinking (DT), User Centered Design (UCD) co-creation, and participatory design (PD) have been adopted to facilitate user and stakeholder involvement in the development of eHealth applications. However, there is frequent confusion around these methodologies leading to a fragmentation of the discourse and limiting integration opportunities. The absence of an empirically grounded framework for HCD limits research and theoretical consensus particularly in the highly regulated context of development of eHealth solutions. Objective: This scoping review aims to explore and analyse the scope, definitions, key concepts, and motivations reported in peer-reviewed studies that have applied stakeholder engagement methods like HCD, PD or DT in developing eHealth applications. Methods: The conduct of this scoping review follows the JBI methodology for scoping reviews and the guidelines for conducting systematic mapping studies in software engineering. The reporting of the results will be guided by the PRISMA-ScR extension. A single reviewer will conduct the initial screening and charting, with random quality checks by a second reviewer. Inclusion Criteria: This review will include only primary studies reporting on the experience, challenges and applicability of HCD for the design and development of eHealth applications, identified through PubMed, IEEE Xplore, and Web of Science, and limited to articles from the past 10 years. Results: This review is expected to summarize the current understanding, terms, definitions and methods of HCD in the development of eHealth tools. We identify research gaps, and trends that will inform the current and future development of mHealth technologies to enhance mHealth adoption and sustainability with special focus on vulnerable populations. A preliminary search applying the search strategy resulted in 3181 records. The search was initiated in July 2024 and the results are expected in 2025. Conclusions: This review will provide knowledge about what, how and why are HCD methods being applied in the development of eHealth tools. This knowledge will translate in consistency reducing confusion, facilitating collaboration and implementation of HCD methodologies. To our knowledge, this is the first scoping literature review aiming to shed light in how the HCD processes are specifically applied in complex and highly regulated environments such as digital healthcare. Furthermore, we aim to understand why the application of the HCD methodology within the eHealth sector is surprisingly limited, especially concerning solutions for vulnerable patient groups.

  • Factors Influencing Specialty Choice Among Medical Students in Korea; a Qualitative Study

    From: JMIR Medical Education

    Date Submitted: Mar 15, 2025

    Open Peer Review Period: Mar 17, 2025 - May 12, 2025

    Background: A decline in applications to vital medical specialties, particularly general surgery, obstetrics and gynecology, and pediatrics in Republic of Korea threatens the nation's healthcare infra...

    Background: A decline in applications to vital medical specialties, particularly general surgery, obstetrics and gynecology, and pediatrics in Republic of Korea threatens the nation's healthcare infrastructure. Despite multiple contributing factors, there is limited qualitative research exploring medical students' specialty choice decisions. Objective: This study aimed to examine the key factors influencing Korean medical students' specialty selection processes, identify how recent healthcare policy changes affect their career decisions, and understand their preferences for training. Methods: We conducted 24 semi-structured interviews with medical students at various educational stages, exploring their demographics, career plans, and specialty preferences. Questions covered motivations for specialization choices, preferred practice locations, and the impact of government policies. Interviews were conducted from March to April 2024, with data coded using ATLAS.ti. Results: Career decisions were influenced by three main categories: personal factors (academic interest, self-perceived competence, sense of calling), social factors (legal risk, remuneration, long-term outlook), and inherent factors of specialties (workload). Recent healthcare policy changes significantly impacted students' career prospects, with some considering practice abroad. Training location preferences were primarily influenced by hospital volume and residency possibilities. Conclusions: Medical students' specialty choices are shaped by personal, social, and inherent factors. Policy implementation should protect students from deterrents like legal risks, enabling choices based on aptitude and interest rather than external pressures, to maintain a well-balanced healthcare system.

  • Exploring Literature on Data Governance in the Healthcare of Older Persons: A Scoping Review

    From: JMIR Aging

    Date Submitted: Mar 7, 2025

    Open Peer Review Period: Mar 14, 2025 - May 9, 2025

    Background: Health data is growing rapidly and the processing of such data is evolving. Research on data governance in older persons’ healthcare is unexplored, providing little guidance for practice...

    Background: Health data is growing rapidly and the processing of such data is evolving. Research on data governance in older persons’ healthcare is unexplored, providing little guidance for practice and future studies. Objective: This scoping review aimed to synthesize available information on data governance in the context of older persons’ health based on evidence from literature. Methods: The study followed the methodological framework of Arksey and O’Malley and PRISMA extension for scoping reviews. Online databases namely PubMed, Cochrane, Ovid, ACM, IEEE Xplore, and Google Scholar were searched by two independent reviewers for studies on older persons’ health data governance published from January 2000 to April 2024. The independent reviewers performed the search, screening, data extraction, and review of full text articles. A third reviewer made the final decision for unresolved discrepancies between the first two reviewers. The framework by the WHO Pan American Health Organization, a high-level framework for planning and implementing data governance in public health, was utilized in the data extraction and analysis. Descriptive statistics were employed, and a descriptive approach was used to summarize the results of the scoping review. Results: A total of 9,847 titles were identified and 57 articles were included. Of these, 35 (61.4%) focused on technology, 19 (33.3%) on processes, and 3 (5.3%) on people. Data controller, processor, researchers, data subject/patient (including family/relatives), and relevant organizations are involved in older persons data governance. Data governance frameworks are designed and implemented by reviewing the current evidence, involving the stakeholders from planning to implementation and defining their roles, obligations, accountabilities, and the system, implementing specific processes, and testing and monitoring. Processes such as collection of older persons’ health data, aggregating these data to inform the assessment, diagnosis, and care management, and implementing such processes to address certain health issues, as well as the use of innovative approaches contribute to the improvement of older persons’ health. Conclusions: The review underscores the importance of the involvement of relevant stakeholders and the use of various innovative tools and approaches in governing data related to the health of older persons. Meanwhile, research specifically addressing data governance for older persons' health conditions is limited. To enhance health outcomes for older persons, effective data governance is essential, alongside further research on relevant policies and practices. Clinical Trial: Not applicable

  • The Strong Families Start at Home / Familias Fuertes Comienzan en Casa randomized controlled trial to improve child diet quality and parental feeding practices: rationale and protocol

    From: JMIR Research Protocols

    Date Submitted: Mar 13, 2025

    Open Peer Review Period: Mar 14, 2025 - May 9, 2025

    Background: Children in the US have poor diet quality increasing their risk for chronic disease burden later in life. Caregivers’ feeding behaviors are a critical factor in shaping lifelong dietary...

    Background: Children in the US have poor diet quality increasing their risk for chronic disease burden later in life. Caregivers’ feeding behaviors are a critical factor in shaping lifelong dietary habits. The Strong Families Start at Home / Familias Fuertes Comienzan en Casa (SFSH) was a 6-month, home-based, pilot randomized-controlled feasibility trial that aimed to improve the diet quality of 2-5-year-old children and promote positive parental feeding practices among a predominantly Hispanic/Latine sample. The pilot saw significant improvements in children’s Healthy Eating Index-2015 total and whole fruit scores as well as multiple food parenting practices, and it was received well by participants. Objective: Building on the success of the pilot study, this protocol paper describes the modifications, study design, and procedures for a fully powered randomized control trial. Methods: Caregiver-child dyads are randomized to a “healthy eating” intervention group or a “reading readiness” attention control group. In the intervention group, a trained community health worker (CHW) conducts monthly home visits or phone calls for six months that focus on age-appropriate nutrition recommendations and food parenting practices. There are three home visits that include tailored nutrition education materials that address their child’s appetitive traits and eating habits, an interactive cooking activity, and review of a family meal video with feedback. CHWs use motivational interviewing and goal setting, which are key components to the program. The control group is similarly structured, with content focusing on reading and language development. Caregivers complete in-person and over the phone baseline and 6-month follow measurements to capture diet quality (primary outcomes: Healthy Eating Index 2015 scores via 2-24-hour dietary recalls and dermal carotenoids) and selected parental feeding practices and availability of healthy foods in the home (secondary outcomes). Results: This protocol was approved by the Brown University Institutional Review Board (protocol number 2022003389). As of March 2025, 81 participants were randomized. Of these, 29 completed the study, and eight withdrew. Recruitment will continue until 257 participants have been randomized. Conclusions: Findings will determine the efficacy of the intervention to improve child diet quality and parental feeding practices, which will ultimately inform future effectiveness and real-world of home-based food parenting programs. Clinical Trial: ClinicalTrials.gov NCT06099288

  • Development and Evaluation of a Non-Motorized Electrical Stimulation Device for Tremor Reduction and Body Movement in Parkinson's Disease: A Pilot Study

    From: JMIR Biomedical Engineering

    Date Submitted: Mar 5, 2025

    Open Peer Review Period: Mar 14, 2025 - May 14, 2025

    Background: Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by motor impairments, including tremors, rigidity, and bradykinesia. These symptoms significantly affec...

    Background: Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by motor impairments, including tremors, rigidity, and bradykinesia. These symptoms significantly affect patients' daily activities and quality of life. Current treatment options, such as medication and deep brain stimulation (DBS), have limitations, including side effects and high costs. Therefore, there is a need for an alternative, non-invasive assistive solution to improve motor function in Parkinson’s patients. Objective: The objective of this study is to develop a brain-body interface that utilizes EEG, EMG, and FES to assist Parkinson’s patients in controlling their motor movements. By synchronizing neural and muscular signals, the system aims to facilitate voluntary movement and reduce tremors without invasive procedures. This research seeks to establish a theoretical model for signal processing and movement generation, forming the foundation for future prototype development and clinical validation. Methods: This section provides a detailed explanation of the methodology used in developing the Parkinson’s assistive device. The approach involves multiple components, each playing a crucial role in capturing, processing, and responding to neurological and muscular signals to facilitate controlled movement. i. EEG Sensor Electroencephalography (EEG) sensors are used to capture brain signals, specifically detecting neural activity associated with movement intention. The EEG data is processed using signal processing algorithms to extract relevant patterns that indicate the user's intent to move a specific muscle group. ii. EMG Sensor Electromyography (EMG) sensors detect electrical activity in muscles. These sensors help in monitoring voluntary and involuntary muscle contractions. By integrating EEG and EMG data, the system enhances the accuracy of movement prediction and stimulation. iii. Functional Electrical Stimulation (FES) FES is used to generate electrical impulses that stimulate specific muscles, facilitating movement in patients experiencing tremors or rigidity. The FES unit receives processed signals from the STM32 microcontroller, ensuring precise and controlled stimulation. iv. STM32 Microcontroller The STM32 microcontroller serves as the central processing unit, responsible for handling signals from EEG and EMG sensors, processing them using machine learning algorithms, and sending appropriate stimulation signals to the FES system. It ensures real-time synchronization between brain activity, muscle response, and electrical stimulation. v. Battery System The device is powered by a rechargeable battery system, providing a stable and efficient energy supply. Power management circuits are implemented to optimize energy consumption, ensuring long-term usability without frequent recharging. vi. Signal Processing and Data Flow  EEG signals are collected and filtered to remove noise.  EMG signals are simultaneously captured to correlate neural activity with muscle activity.  The STM32 microcontroller processes these signals and applies machine learning models to predict intended movement.  The microcontroller sends precise electrical stimulation commands to the FES unit.  The FES unit stimulates the target muscles, enabling controlled movement. vii. Synchronization and Feedback Mechanism To improve accuracy, a feedback loop is implemented where real-time responses from the muscles (EMG) are re-evaluated, and adjustments are made dynamically to the stimulation parameters. This ensures adaptive and efficient motor control. Results: In this study, a theoretical model was developed to integrate EEG, EBG, and EMG signals for effective control of Functional Electrical Stimulation (FES) in Parkinson’s patients. The preliminary analysis of signal synchronization and processing suggests that this approach has the potential to facilitate controlled motor movements. 1. Theoretical Validation: The signal processing framework was designed based on existing neurophysiological principles. The expected interactions between EEG and EMG signals indicate that FES can be triggered appropriately to induce movement. 2. Expected Outcomes: The anticipated result of this system is an improvement in motor function for Parkinson’s patients by translating neural intent into physical action. The model predicts that synchronized stimulation can assist in reducing tremors and enhancing voluntary movements. 3. Future Work: The next phase involves developing a prototype for real-world testing. Experimental validation through hardware implementation will be conducted to confirm the effectiveness of the proposed system. Conclusions: This research presents a significant advancement in assistive technology for individuals with Parkinson’s disease. By integrating EEG, EMG, and FES sensors with an STM32 microcontroller, the system effectively interprets neural and muscular signals to generate precise stimulation, aiding in movement control. The study highlights the potential of electrical stimulation and brain-computer interface technology in enhancing motor functions without invasive procedures. The development of this device marks a step forward in neuro-assistive solutions, providing a non-invasive, adaptive, and user-friendly system for patients. The integration of AI-driven signal processing and real-time data adaptation further enhances the system’s efficiency and accuracy. The miniaturization of components and transition to wearable technology will improve usability and accessibility for daily life applications. Future improvements will focus on optimizing the device’s performance, expanding its application to other neurological disorders, and conducting extensive clinical trials to validate its effectiveness. Through continuous innovation and collaboration with healthcare professionals, this technology has the potential to revolutionize treatment approaches for movement impairments, offering a better quality of life for affected individuals.

  • Development and Evaluation of a Virtual Patient-Based Serious Game for Diagnosis and Treatment Planning in Orthodontic Education

    From: JMIR Serious Games

    Date Submitted: Mar 14, 2025

    Open Peer Review Period: Mar 14, 2025 - May 9, 2025

    Background: Serious games are gaining momentum in dental education due to their positive educational impact. However, their application in orthodontic diagnosis and treatment planning training remains...

    Background: Serious games are gaining momentum in dental education due to their positive educational impact. However, their application in orthodontic diagnosis and treatment planning training remains unexplored. Objective: This study aimed to design and evaluate a serious game for orthodontic diagnosis and treatment planning, comparing its educational impact between gamer and non-gamer users. Methods: A serious game for orthodontic diagnosis and treatment planning in virtual patients (OrthoVirt) was developed using React. Thirty-two fourth-year dental undergraduates were recruited and categorized based on their video game playing habits into two groups: gamers (n=16), who reported playing video games for at least seven hours per week, and non-gamers (n=16), who played less frequently. Both groups used OrthoVirt following the same standardized protocol. Pre- and post-knowledge assessments and a satisfaction questionnaire were administered. Knowledge improvement was assessed using paired t-tests, while group comparisons were made using independent t-tests. Results: Both gamer and non-gamer groups showed significant knowledge improvement after using OrthoVirt (P<.001). The mean scores of the gamer group increased from 10.31 to 15.19, while those of the non-gamer group rose from 11.19 to 14.31. No significant differences were found between groups in pre- and post-knowledge assessments as well as improvement scores (P>.05). Both groups rated OrthoVirt favorably, with 'perceived ease of use' scoring highest and 'perceived enjoyment' lowest. Overall satisfaction was similar between groups (P>.05). Conclusions: OrthoVirt demonstrated potential as a supplementary tool for orthodontic diagnosis and treatment planning education, significantly improving students' knowledge regardless of their video game playing habits. While students provided positive feedback on its usefulness and ease of use, opportunities for enhancing user enjoyment were identified.

  • Towards a “pandemic-proof” methodology for outbreak detection: adapting to COVID-19’s impact on notifications of infectious diseases in the Netherlands

    From: JMIR Public Health and Surveillance

    Date Submitted: Mar 14, 2025

    Open Peer Review Period: Mar 14, 2025 - May 9, 2025

    Background: Reporting of notifiable infectious diseases was overall impacted by the COVID-19 pandemic. This could affect disease surveillance and thus outbreak detection. Objective: In this study, we...

    Background: Reporting of notifiable infectious diseases was overall impacted by the COVID-19 pandemic. This could affect disease surveillance and thus outbreak detection. Objective: In this study, we take the first steps in the development of a methodology that adjusts for the impact of the COVID-19 pandemic on the number of notification of notifiable infectious diseases and provides corrected alarm thresholds for outbreak detection. Methods: We analyzed cases of 25 notifiable infectious diseases reported from 2015 – 2023 in the Netherlands. Negative binomial regression was used to calculate the incidence rate ratios for each period: pre-COVID, COVID 2020, COVID 2021, COVID 2022 and post-COVID. To address the decrease in notifications during COVID, we tested three correction methods: 1) recoding COVID years as missing; 2) imputing with the last pre-COVID observation; and 3) imputing the historical moving average. Results: Malaria, typhoid fever, hepatitis A, meningococcal infection, paratyphoid fever, Q-fever, shigellosis, measles, mumps and pertussis had significantly lower notifications during the COVID-19 pandemic, but the duration and magnitude of the effect differed among the infections. Additionally, the newly calculated alarm thresholds showed a noticeable difference compared to the original unadjusted alarm thresholds. However, the variation among the three different corrected alarm thresholds was not substantial. Conclusions: During the COVID-19 pandemic, notifications of ten infectious diseases declined significantly. The duration of this decline varied among infections, highlighting the need for disease-specific adjustments. Our study demonstrates that accounting for the reduced notifications impacts alarm threshold calculations for outbreak detection. Further validation by communicable disease control professionals is essential to assess the applicability of the adjusted alarm thresholds for outbreak detection. Clinical Trial: N.A.

  • Facilitating the Implementation of Population-wide Genomic Screening across Diverse Populations and Settings (FOCUS): A Protocol for an Implementation Mapping Study to Identify Best Practices for Implementing Population-wide Genomic Screening Programs

    From: JMIR Research Protocols

    Date Submitted: Mar 11, 2025

    Open Peer Review Period: Mar 12, 2025 - May 7, 2025

    Background: Population-wide genomic screening (PGS) for genetic conditions such as Hereditary Breast and Ovarian Cancer Syndrome, Lynch Syndrome, and Familial Hypercholesterolemia presents opportuniti...

    Background: Population-wide genomic screening (PGS) for genetic conditions such as Hereditary Breast and Ovarian Cancer Syndrome, Lynch Syndrome, and Familial Hypercholesterolemia presents opportunities to reduce morbidity and mortality among the 1-2% of the population at elevated risk for these serious, preventable diseases. With decreasing sequencing costs and growing support from national bodies, there are increasing numbers of PGS programs in the US. However, guidelines and strategies to support implementation are limited, especially regarding equitable access to PGS. Contextual factors, such as organizational structures and processes impact PGS implementation, often failing to benefit underrepresented populations. Objective: To address these challenges, we are completing the FOCUS project, which will develop and test a freely available, equity-centered online implementation toolkit to guide best practices for implementing PGS. Methods: The FOCUS project aims to 1) examine barriers and facilitators of equitable PGS implementation at sites at various stages of implementation, 2) develop implementation strategies with input from a diverse advisory panel and package them into the FOCUS toolkit, and 3) evaluate the toolkit's impact on improving PGS reach, effectiveness, adoption, and maintenance using a hybrid stepped-wedge cluster randomized trial design. Results: Results: This project was funded in 8/2024 per the funding acknowledgement. Implementation Team Member (ITM) data collection began in 10/2024 and Patient (PAT) data collection began in 1/2025. As of 3/2025, we have enrolled 9 PAT subjects and 32 ITM subjects. Of these 32 ITM subjects, we have completed qualitative data analyses on 18 of them in accordance with our described methods for Study Aim 1. Conclusions: With a focus on health equity and stakeholder engagement, the FOCUS toolkit will establish a standardized approach to scaling PGS programs across diverse populations and settings, ensuring genomics benefits are accessible to all.

  • CONSTRUCTION, VALIDATION AND PSYCHOMETRIC ANALYSIS OF THE CuSAERS: A TOOL FOR MEASURING STUDENT SATISFACTION IN SOCIAL NETWORK-BASED LEARNING ENVIRONMENTS

    From: JMIR Medical Education

    Date Submitted: Mar 12, 2025

    Open Peer Review Period: Mar 12, 2025 - May 7, 2025

    Background: - Objective: This study investigated the use of social networks as educational tools in the university environment, with the aim of designing and validating the Questionnaire of Satisfacti...

    Background: - Objective: This study investigated the use of social networks as educational tools in the university environment, with the aim of designing and validating the Questionnaire of Satisfaction with Educational Activities Performed on Social Networks (CuSAERS). Methods: Employing a mixed and sequential methodology, we explored the perceptions of Bachelor’s and Master’s degree students in Physiotherapy who participated in teaching activities via X.com (formerly Twitter) and Instagram. The first phase of the project identified key dimensions of satisfaction from the literature, expert interviews and cognitive interviews. The second phase assessed the psychometric properties of the CuSAERS in a sample of 150 students, addressing construct validity, internal reliability, concurrent validity and discriminant validity. Results: Exploratory factorial analysis revealed 4 dimensions: Perception of Learning, Task Satisfaction, Self-Fulfilment and Motivation. Reliability was adequate, with the robustness of the Perception of Learning dimension standing out. Concurrent validity was confirmed by moderate correlations with the Academic Satisfaction Scale, which supports the usefulness of the CuSAERS in assessing the impact of social networks on student satisfaction. Significant differences were also observed between Bachelor’s and Master’s students, with the latter showing the highest level of satisfaction, possibly due to greater academic experience and digital competence. Conclusions: The results suggest that CuSAERS appears to be a valid and reliable tool for measuring student satisfaction with teaching activities on social networks. This instrument could guide teaching practice, optimize pedagogical strategies in digital environments and ultimately promote more meaningful and collaborative learning. Clinical Trial: No applicable.

  • Utilizing Smart TVs as Assistive Technology to Enhance Older Adults’ Communications and Social Lives: Systematic Review

    From: JMIR Rehabilitation and Assistive Technologies

    Date Submitted: Feb 24, 2025

    Open Peer Review Period: Mar 11, 2025 - May 6, 2025

    Background: Over the past decade, the proportion of the world's population aged 65 and above has grown exponentially, raising significant challenges such as social isolation and loneliness among this...

    Background: Over the past decade, the proportion of the world's population aged 65 and above has grown exponentially, raising significant challenges such as social isolation and loneliness among this population. Assistive technologies have shown potential in enhancing the quality of life of older adults by improving their physical, cognitive, communication, and so forth. Research has shown that smart televisions (TVs) are user-friendly and commonly used among older adults. However, smart TVs have been underutilized as assistive technologies. Objective: The aim of the study is to explore the state-of-the-art of utilizing smart TVs as assistive technologies for older adults in improving their communications and social lives. Methods: The search was conducted following the guidelines for performing systematic literature review, which included six databases, i.e., IEEE, ACM, Google Scholar, ScienceDirect, Engineering Village and Springer. A range of keywords were used in different combinations, including ‘smart TV’, ‘older adults’, ‘elderly’, ‘communication’, ‘messaging’, ‘video call’ and ‘application’. A set of inclusion and exclusion criteria were defined prior to the search and the screening was performed by three researchers. Based on the aim of the review, inclusion and exclusion criteria, we analyzed the included papers. None of the papers were subjected to quantitative synthesis due to the significant variations in the data measured. Results: After screening 2671 records, from the abstract level to full text, 30 papers were identified as relevant studies, demonstrating both direct and indirect impacts on the social lives of older adults through the use of smart TVs as assistive technology. Some papers were parts of the same and/or a larger study, which makes the number of actual projects even smaller. This indicates that smart TVs have been little utilized as assistive technologies for enhancing older adults’ communication and social lives. Most papers proposed their own prototype, and these prototypes were mostly targeted for use at home, while some at geriatric care units or nursing homes. User involvement among older adults was high among the included papers, and some also included other users such as healthcare personnel, administrative staff, and engineers. The included studies were mostly from Europe. Conclusions: This review highlights the potential of smart TVs as assistive technologies to enhance social connectivity among older adults but identifies several research gaps. Most studies focus on short-term usability and are geographically limited to Europe. Future research should include longitudinal studies, explore diverse cultural attitudes, and focus on adaptive solutions for various health conditions. We hope this review can inspire research on smart TVs as assistive technologies, enhancing social interactions and quality of life for older adults.

  • Using Artificial Intelligence ChatGPT to Access Medical Information About Chemical Eye Injuries : Compartive Study

    From: JMIR Formative Research

    Date Submitted: Mar 8, 2025

    Open Peer Review Period: Mar 11, 2025 - May 6, 2025

    Background: Chemical ocular injuries are a major public health issue, causing eye damage from harmful chemicals and potentially leading to severe vision loss or blindness if not treated promptly and e...

    Background: Chemical ocular injuries are a major public health issue, causing eye damage from harmful chemicals and potentially leading to severe vision loss or blindness if not treated promptly and effectively. Although medical knowledge has advanced, accessing reliable and understandable information on these injuries remains challenging due to unverified online content and complex terminology. Artificial Intelligence (AI) tools like ChatGPT provide a promising solution by simplifying medical information and making it more accessible to the general public. Objective: This study aims to assess the use of ChatGPT in providing reliable, accurate, and accessible medical information on chemical ocular injuries. It evaluates the correctness, thematic accuracy, and coherence of ChatGPT’s responses compared to established medical guidelines and explores its potential for patient education. Methods: Nine questions were entered to ChatGPT regarding various aspects of chemical ocular injuries, including : definition, prevalence, etiology, prevention, symptoms, diagnosis, treatment, follow- up, and complications. The responses provided by ChatGPT were compared to the ICD-9 and ICD-10 guidelines for chemical (alkali and acid) injuries of the conjunctiva and cornea. The evaluation focused on criteria such as correctness, thematic accuracy, coherence to assess the accuracy of ChatGPT’s answers. The inputs were categorized into three distinct groups, and statistical analyses, including Flesch–Kincaid readability tests, ANOVA, and trend analysis, were conducted to assess their readability, complexity and trends. Results: The results showed that ChatGPT provided accurate and coherent responses for most questions about chemical ocular injuries, demonstrating thematic relevance. However, the responses sometimes overlooked critical clinical details or guideline-specific elements, such as emphasizing the urgency of care, using precise classification systems, and addressing detailed diagnostic or management protocols. While the answers were generally valid, they occasionally included less relevant or overly generalized information, reducing their consistency with established medical guidelines. The average FRES was 33.84 ± 0.28, indicating a fairly challenging reading level, while the FKGL averaged 14.21 ± 0.22, suitable for readers with college-level proficiency. Passive voice was used in 7.22% ± 0.66% of sentences, indicating moderate reliance. Statistical analysis showed no significant differences in FRES (p =.385), FKGL (p =.555), or passive sentence usage (p =.601) across categories, as determined by one-way ANOVA. Readability remained relatively constant across the three categories as determined by trend analysis . Conclusions: ChatGPT shows strong potential in providing accurate and relevant information about chemical ocular injuries. However, Its language complexity may prevent accessibility for individuals with lower health literacy and sometimes miss critical aspects. Future improvements should focus on enhancing readability, increasing context-specific accuracy, and tailoring responses to person needs and literacy levels. While ChatGPT can be a helpful tool for patients and healthcare professionals, it shouldn’t replace professional medical advice, as some responses might not match clinical practice or address the needs of patients with different levels of education.

  • SPAN@DEM: A Pioneer in Department-Level Patient Advocacy

    From: Journal of Participatory Medicine

    Date Submitted: Feb 12, 2025

    Open Peer Review Period: Mar 11, 2025 - May 6, 2025

    Background: SPAN@DEM emerged from the recognition that existing cluster-level advocacy groups are inadequate to address the specific needs of the emergency department (ED). Moreover, the fast-paced, h...

    Background: SPAN@DEM emerged from the recognition that existing cluster-level advocacy groups are inadequate to address the specific needs of the emergency department (ED). Moreover, the fast-paced, high-pressure nature of emergency medicine presents distinct challenges for patient advocacy. As the first ED-specific advocacy group in Singapore, SPAN@DEM represents a significant step forward in local patient advocacy efforts because it uses a shared collaborative model to address patient needs and concerns within the unique context of the ED environment. Objective: In this article, we aim to share our journey in setting up our patient advocacy group, discuss the challenges and considerations and reflect on our lessons learnt throughout this process. Methods: A start-up committee comprising emergency physicians and patient advocates was formed to explore the processes required to create such an organisation. Some important features of SPAN@DEM include co-leadership between emergency physician and patient advocate, and diverse composition with equal representation from healthcare workers and advocates. SPAN@DEM conducts quarterly meetings with informal luncheons during meetings to foster open communication between advocates and healthcare staff. Membership is voluntary and based purely on altruism and members must participate in mandatory advocacy trainings to empower them to provide more actionable insights. Results: SPAN@DEM has initiated several projects thus far, such as PIKACHU (a quality improvement project which led to improved patient and next-of-kin satisfaction rates and decreased formal communication-related complaints) and Digital FAQ (a patient-friendly resource to explain ED processes) in addition to communication workshops for junior doctors and wayfinding projects. SPAN@DEM advocates have also actively contributed to the planning, design and transition to the new Emergency Medicine Building. More importantly, SPAN@DEM has fostered a cultural shift towards patient-centric care within the department as the department now works closely with patient advocates on day-to-day decisions for matters concerning patient and next-of-kin experience. Conclusions: SPAN@DEM demonstrates the value of specialised department-specific advocacy groups in shaping the future of patient-centred emergency care. This model may serve as an exemplar for other healthcare institutions seeking to promote patient advocacy efforts. Clinical Trial: N/A

  • Moderated Online Social Therapy (MOST) In Help-Seeking Young People: A Pilot Randomised Controlled Study.

    From: Journal of Medical Internet Research

    Date Submitted: Mar 10, 2025

    Open Peer Review Period: Mar 10, 2025 - May 5, 2025

    Background: In the context of a sharp rise in help-seeking in youth mental health, digital mental health interventions offer enormous potential to improve outcomes, facilitate access, and meet the inc...

    Background: In the context of a sharp rise in help-seeking in youth mental health, digital mental health interventions offer enormous potential to improve outcomes, facilitate access, and meet the increasing demand on mental health services. For young adults attending third level education, for example, digital mental health interventions may support help-seeking students while either waiting to attend student counselling, or to sustain gains or once a brief course of face-to-face counselling sessions have completed. Objective: This trial investigated the feasibility of using a Moderated Online Social Therapy (MOST) intervention comprising of tailored mental health content and therapist, peer, and online community support in third-level students who recently attended a student counselling service. Methods: We conducted a pilot randomised controlled study of third-level students who had recently completed ~4 sessions of counselling. Students were randomly assigned to the intervention or control arm at a rate of 2:1. In the intervention arm, students had access to MOST for 26 weeks and both groups were assessed at baseline, 12 weeks, and 26 weeks with effect sizes calculated between groups. Results: A total of N = 74 were recruited, meeting the recruitment target of ~3.1 participants per semester month. Retention in the trial was 70.3% at 12 weeks, reducing to 66.2% at 26 weeks. For the intervention group, when engagement was measured in terms of participation in at least one component of the intervention, 80.9% of the intervention group engaged for 5 or more weeks of the trial (~20% of the maximum 26 weeks). Based on the effect sizes observed, the intervention arm was associated with modest gains in social function and cognitive function, and reduced clinical symptom severity at 12 weeks. Conclusions: Based on the recruitment, retention, and engagement rates observed, a full randomised controlled trial of MOST with young adults is feasible. Moreover, the effect sizes favouring the intervention arm are consistent with previous studies, and support a full trial of MOST as a potentially beneficial support for youth mental health in further education settings.

  • AI Approaches for Grading and Assessing Hydronephrosis Severity in Pediatric Patients: Protocol for a Systematic Review and Meta-Analysis

    From: JMIR Research Protocols

    Date Submitted: Mar 8, 2025

    Open Peer Review Period: Mar 10, 2025 - May 5, 2025

    Background: Hydronephrosis is a condition characterized by the swelling of one or both kidneys due to urine buildup, often resulting from an obstruction in the urinary tract. In pediatric patients, gr...

    Background: Hydronephrosis is a condition characterized by the swelling of one or both kidneys due to urine buildup, often resulting from an obstruction in the urinary tract. In pediatric patients, grading and assessing the severity of hydronephrosis are crucial for determining appropriate treatment and predicting outcomes. Objective: The objective of this study is to systematically review and analyze the use of AI-based models for grading and assessing hydronephrosis severity in pediatric patients, evaluating their methodologies, diagnostic performance, and potential for clinical integration. Methods: This systematic review and meta-analysis will systematically search for studies published up to 1 March 2025 in databases including MEDLINE, Cochrane, IEEE Xplore, Scopus, Google Scholar, and Taylor & Francis, as well as grey literature sources like ProQuest, OpenGrey, and conference proceedings. Eligible studies must involve AI-based models for segmentation, classification, or prediction of hydronephrosis severity in patients aged 0–18 years, utilizing imaging modalities such as ultrasound, CT, or MRI. Studies will be assessed for risk of bias using a modified version of QUADAS-2, and a narrative synthesis will be conducted. If sufficient data homogeneity exists, a meta-analysis will be performed using random-effects models. Results: The study began in March 2025 with completion expected by July 2025. Conclusions: This systematic review and meta-analysis will be the first review to provide insights into the potential of AI in pediatric hydronephrosis assessment, supporting its integration into clinical practice or identifying limitations in its application.

  • Privacy Policy Compliance of Mobile Sports and Health Apps in China:Scale Development, Data Analysis, and Prospects for Regulatory Reform

    From: JMIR mHealth and uHealth

    Date Submitted: Mar 9, 2025

    Open Peer Review Period: Mar 8, 2025 - May 3, 2025

    Background: Driven by technological advancements, the proliferation of mobile sports and health applications (apps) has revolutionized health management by improving efficiency, cost-effectiveness, an...

    Background: Driven by technological advancements, the proliferation of mobile sports and health applications (apps) has revolutionized health management by improving efficiency, cost-effectiveness, and accessibility. While the widespread adoption of these platforms has transformed public health practices and social well-being in China, emerging evidence suggests that inadequacies in their privacy policies may compromise personal information (PI) protection. Objective: This study conducts a systematic evaluation of privacy policy compliance among 100 leading mobile sports and health apps in mainland China, benchmarking them against the Personal Information Protection Law (PIPL) and associated regulatory guidelines. Methods: This study develops a privacy policy compliance indicator scale based on the information life cycle and the legal framework for PI protection in the Mainland of China. This scale consists of 5 level 1 indicators and 37 level 2 indicators that assess the privacy policy compliance. Results: The mean compliance score of the 100 sports and health apps is 58.375. 42% of the 100 apps score below the average, with 57.14% (n=24) scoring less than 40 points and 20% (n=20) scoring more than 80 points. The 5 level 1 indicators have the following scores: 75.22% for the collection of PI, 52% for the storage of PI, 52.21% for the use of PI, 61% for the entrusted processing, the sharing, the transfer, and the disclosure of PI, and 60.6% for the consultation and feedback on PI. The compliance level among Apple system apps surpasses that of Android system apps. Despite identical qualified rates for Apple and Android apps, both at 17 out of 50, the proportion of Apple apps rated as excellent (12%) and good (12%) markedly surpasses that of Android apps, which stand at 6% for excellent and 10% for good. The compliance evaluations for these 37 level 2 indicators, 18 show a mean compliance rate below 60%. Three indicators exhibit compliance rates below 20%: de-identified display and use of PI at 16%, storage of sensitive PI at 13%, and processing rules of deceased users at 11%. While the majority of 100 apps indicate that the collected PI will be retained in the Mainland of China for a reasonably necessary duration (mean 71%[SD 45.60%]), and that separate authorization will be required otherwise (mean 80%[SD 40.20%]), in accordance with the principle of necessity outlined in Article 19 and the principle of domestic storage in Article 39 of the PIPL, fewer than half (mean 44%[SD 49.89%]) of the evaluated apps will de-identify the data promptly through security measures after PI collection. Conclusions: Although some apps establish commendable policies, there are some shortcomings that compromise the efficacy of PI protection. In light of this, this paper puts forward suggestions from the perspective of privacy policy formulation, regulatory reform, and legislative improvement.

  • Unlocking the Secrets Beneath: Utilizing the Water Quality Index (WQI) to Assess Groundwater Contamination Near Dumpsites – A Case Study of Port Harcourt

    From: JMIR Preprints

    Date Submitted: Mar 8, 2025

    Open Peer Review Period: Mar 8, 2025 - Feb 21, 2026

    Background: Groundwater contamination poses a significant public health risk, particularly in urban areas with inadequate waste management. Dumpsites serve as major sources of pollutants, including he...

    Background: Groundwater contamination poses a significant public health risk, particularly in urban areas with inadequate waste management. Dumpsites serve as major sources of pollutants, including heavy metals, which infiltrate aquifers through leachate migration. Port Harcourt, Nigeria, faces increasing groundwater quality concerns due to the proliferation of uncontrolled waste disposal sites. Objective: This study aims to evaluate the spatial and seasonal variations in groundwater quality around dumpsites in Port Harcourt and determine the suitability of groundwater for drinking based on WQI values. It also seeks to identify contamination patterns and assess the influence of rainfall on pollutant dispersion. Furthermore, the study compares findings with global research to establish broader implications for waste management and public health. By doing so, it provides a scientific basis for policy recommendations aimed at mitigating groundwater pollution. Methods: Groundwater samples were collected from various locations around major dumpsites in Port Harcourt during dry and rainy seasons. Physicochemical parameters, including heavy metal concentrations, were analyzed to compute WQI values. Comparative analysis with previous studies was conducted to validate observed contamination trends. The impact of leachate migration on water quality was assessed using seasonal variations in WQI values. Results: Findings reveal significant spatial and seasonal fluctuations in groundwater quality. While Choba exhibited excellent water quality, Sasun, Olumeni, and Epirikom recorded dangerously high WQI values, indicating unsuitability for drinking. Seasonal variations showed that rainfall exacerbated contamination levels, as seen in Eleme, where WQI increased from 56.362 in the dry season to 140.928 in the rainy season. The study aligns with previous research from India, China, and Ghana, demonstrating that landfill leachates and surface runoff are key contributors to groundwater degradation. Conclusions: The study confirms that dumpsite leachates significantly impact groundwater quality, posing a major risk to public health. The high WQI values in several locations highlight the need for urgent interventions. Findings align with global research on groundwater contamination, emphasizing the critical role of effective waste management in reducing environmental pollution. To mitigate groundwater pollution from dumpsite leachates, it is essential to implement stringent waste management policies that regulate landfill operations and prevent leachate infiltration into aquifers. Establishing continuous groundwater monitoring programs can help detect contamination trends early and guide timely intervention measures. Additionally, promoting alternative potable water sources in highly contaminated areas is crucial to reducing health risks for affected communities. The adoption of modern landfill technologies, such as leachate treatment and containment systems, should be prioritized to minimize pollution and safeguard water resources for future generations. This study contributes to the growing body of research on groundwater contamination by providing empirical evidence of the impact of dumpsites in an urban African setting. The findings underscore the urgent need for improved waste management policies and public health interventions. By aligning with global research, this study reinforces the importance of sustainable environmental practices to safeguard water resources and protect communities from the adverse effects of pollution.

  • Quality Assessment of Radiotherapy Health Information on Short-Form Video Platforms: A Comparative Analysis of TikTok and Bilibili

    From: JMIR Cancer

    Date Submitted: Mar 4, 2025

    Open Peer Review Period: Mar 7, 2025 - May 2, 2025

    Background: Radiotherapy is a crucial modality in cancer treatment. In recent years, the rise of short-form video platforms has transformed how the public accesses medical information. TikTok and Bili...

    Background: Radiotherapy is a crucial modality in cancer treatment. In recent years, the rise of short-form video platforms has transformed how the public accesses medical information. TikTok and Bilibili, as leading short-video platforms, have emerged as significant channels for disseminating health information. However, there is an urgent need to evaluate the quality and reliability of the information related to radiotherapy available on these platforms. Objective: This study aims to systematically assess the information quality and reliability of radiotherapy-related short-form videos on TikTok and Bilibili platforms using the Global Quality Score (GQS) and a modified DISCERN evaluation tool, thereby elucidating the current landscape and challenges of digital health communication. Methods: This study systematically retrieved the top 100 radiotherapy-related videos on TikTok and Bilibili as of February 25, 2025. The quality of the videos was assessed using the Global Quality Score (GQS, 1-5 points) and a modified DISCERN scoring system (1-5 points). Statistical analyses were conducted using the Mann-Whitney U test, as well as Spearman and Pearson correlation analyses, to ensure the reliability and validity of the results. Results: A total of 200 short-form videos related to radiotherapy were analyzed, revealing that the overall quality of videos on TikTok and Bilibili is unsatisfactory. Specifically, the median Global Quality Score (GQS) for TikTok was 4 (interquartile range [IQR] 3-4), while for Bilibili it was 3 (IQR 3-4). The median modified DISCERN scores for both platforms were 3 (IQR 2-4 and IQR 3-4, respectively).On TikTok, 53% (53/100) of the videos were rated as "good" or higher, whereas 45% (45/100) of the videos on Bilibili were considered "relatively reliable." Videos produced by professionals, institutions, and non-professional organizations had significantly higher DISCERN scores compared to those produced by non-professional individuals, with statistical significance (P<.0001, P<.0001, and P<.01, respectively).Furthermore, the correlations between the number of bookmarks and video duration with DISCERN scores were 0.172 (p = 0.015) and 0.192 (p = 0.007), respectively. However, no video variables were found to effectively predict the overall quality and reliability of the videos. Conclusions: This study revealed that the overall quality of radiotherapy-related videos on TikTok and Bilibili is generally low. However, videos uploaded by professionals demonstrate higher information quality and reliability, providing valuable support for patients seeking guidance on healthcare management and treatment options for tumors. Therefore, improving the quality and reliability of video content, particularly those produced by non-professionals, is crucial for ensuring the public has access to accurate medical information.

  • Association between parental smoking status and adolescent mental health: A population-based study

    From: Asian/Pacific Island Nursing Journal

    Date Submitted: Mar 7, 2025

    Open Peer Review Period: Mar 7, 2025 - May 2, 2025

    Background: Adolescents’ mental health problems significantly affect their long-term psychological and physical health. Although peer influence grows during adolescence, parental influence remains c...

    Background: Adolescents’ mental health problems significantly affect their long-term psychological and physical health. Although peer influence grows during adolescence, parental influence remains critical. Parental smoking is associated with behavioral problems in adolescents. Objective: As research in this area is limited, this study investigated the impact of parental smoking, particularly maternal smoking, on 2,761 adolescents’ mental health outcomes in South Korea. Methods: We analyzed data from a nationwide Korea National Health and Nutrition Examination Survey from 2012 to 2017. We employed analysis of variance and χ2 tests to compare adolescents’ and parents’ baseline characteristics and mental health. Results: Our logistic regression analyses revealed that mothers’ current smoking habits were significantly associated with their adolescents’ cognitive stress (odds ratio [OR] = 1.65 (95% CI: 1.06–2.56)), experiences of melancholy (OR = 2.09 (95% CI: 1.20–3.65)), and suicidal ideation (OR = 2.39 (95% CI: 1.17–4.88)). Furthermore, adolescents whose mothers were current smokers and had cognitive stress demonstrated higher cognitive stress (OR = 2.09), melancholy (OR = 2.27), and suicidal ideation (OR = 2.74) than those whose mothers were not smokers and had no cognitive stress. Conclusions: Efforts to improve adolescents’ mental health require considering their mothers’ smoking status and stress levels. This highlights the need to develop programs to enhance adolescent mental health, manage maternal stress, and promote smoking cessation.

  • Validation and acceptability of the mobile app version of the Control of Allergic Rhinitis and Asthma Test for Children (CARATKids): a cross-sectional study

    From: JMIR Pediatrics and Parenting

    Date Submitted: Mar 6, 2025

    Open Peer Review Period: Mar 6, 2025 - May 1, 2025

    Background: The electronic version of the Control of Allergic Rhinitis and Asthma Test for Children (CARATKids) has the potential to enhance pediatric telemonitoring but has not yet been validated. Ob...

    Background: The electronic version of the Control of Allergic Rhinitis and Asthma Test for Children (CARATKids) has the potential to enhance pediatric telemonitoring but has not yet been validated. Objective: This study aimed to validate the electronic version of CARATKids against the paper-based version. Methods: A cross-sectional study was conducted between April and December 2024 in a tertiary hospital in northern Portugal. Children with asthma and/or allergic rhinitis and their caregivers were recruited during pulmonology outpatient appointments. CARATKids comprises 13 yes/no questions, 8 addressed to the child and 5 to the caregiver, and the total score ranges from 0 to 13. The electronic CARATKids was made available through a mobile app. Both paper and electronic versions were administered in a randomized order before and after the appointment. Additionally, participants’ preferences between the two administration versions were assessed. Internal consistency (Cronbach’s alpha), reliability (intraclass correlation coefficient-ICC, Bland- Altman analysis) and convergent validity (Spearman’s coefficient) were analyzed following COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) guidelines. Results: Fifty-one children (median 9 [1 st quartil 8–3 rd quartil 11] years; 57% male) and respective caregivers (41 [37-45] years) were included. The median CARATKids total score was similar across the paper (5 [3–8]) and electronic (5 [3–7]) versions. The internal consistency was 0.79 for the paper version and 0.83 for the electronic version. The reliability between the two versions was excellent (ICC 0.95, 95% CI: 0.91–0.97). The Bland-Altman analysis showed strong agreement between the two versions, with a mean difference of 0.04 (95% limits of agreement: -1.99-2.07). The Spearman’s correlation between the two versions was 0.95 (p<0.001). In total, 63% of children and 61% of caregivers were indifferent to the version used, while 33% and 35%, respectively, preferred the electronic version. Conclusions: The electronic version of CARATKids appears to be equivalent to the paper-based version of the questionnaire, with good acceptance by children and caregivers. CARATKids implementation in mHealth technologies has the potential to enhance remote child monitoring and optimize the management of asthma and allergic rhinitis.

  • The Relationship Between Medical Student Neuroticism and Preferred Medical Specialty: A Cross-Sectional Study

    From: JMIR Formative Research

    Date Submitted: Mar 5, 2025

    Open Peer Review Period: Mar 5, 2025 - Apr 30, 2025

    Choosing and matching into one's preferred specialty is one of the most important and potentially stressful concerns medical students face. Many factors play a role in specialty chose such as prior li...

    Choosing and matching into one's preferred specialty is one of the most important and potentially stressful concerns medical students face. Many factors play a role in specialty chose such as prior life experiences, lifestyle, and how well a medical student feels they fit in with the personalities of said specialty. This study examines the relationship between neuroticism and specialty choice among medical students at a single U.S. allopathic medical school using the Big Five Inventory and proprietary questions to quantify neurotic personality traits and specialty perceptions in current US medical students. Respondents interested in surgical specialties believed that surgical specialties were more competitive than medical specialties, but were not found to be more neurotic than their medicine counterparts. Additionally, those whose interested included both surgical and medical specialties were found to be less neurotic than their peers. The results of this study indicate that medical students are already cognizant and concerned about matching into their desired specialties in their preclinical potion of their medical education.

  • Perceived Benefits and Challenges of Virtual Laboratory Implementation in Chemistry Education: A Mixed-Methods Study

    From: JMIR Medical Education

    Date Submitted: Feb 26, 2025

    Open Peer Review Period: Mar 5, 2025 - Apr 30, 2025

    Background: Chemistry education relies heavily on experimentation to bridge theoretical concepts with practical applications. However, universities often face challenges in providing real laboratory e...

    Background: Chemistry education relies heavily on experimentation to bridge theoretical concepts with practical applications. However, universities often face challenges in providing real laboratory experiences due to resource limitations, equipment shortages, and logistical constraints. Virtual laboratories have emerged as a promising alternative, offering interactive, computer-based simulations that replicate real lab experiments and enhance learning. Objective: This study investigates the perceived benefits and challenges of implementing virtual laboratories in chemistry education at selected universities in Southern Ethiopia, assessing their effectiveness as a teaching and learning tool. Methods: An explanatory sequential mixed-method design was employed to provide a comprehensive analysis. Quantitative data were collected from 63 chemistry instructors and 143 undergraduate students using structured questionnaires, while qualitative insights were obtained through interviews. Descriptive statistics were used to analyze numerical data, and thematic coding was applied to categorize qualitative responses. Results: The findings indicate that virtual laboratories significantly enhance chemistry education by improving academic achievement and conceptual understanding, particularly in grasping key concepts and complex topics (average mean score: 3.9). They also contribute to the development of essential scientific skills, such as hypothesis formulation, problem-solving abilities, and effective lab report writing (average mean score: 3.8). Additionally, virtual labs offer flexibility in learning by supporting self-paced education and serving as viable alternatives when access to real laboratories is limited (average mean score: 3.8). However, despite these advantages, several challenges were identified. Limited technical expertise (kappa = 0.63), high software costs (kappa = 0.61), difficulties in understanding specific concepts required for virtual experiments (kappa = 0.61), and the absence of engaging virtual lab software (kappa = 0.51) were among the primary obstacles. Furthermore, a lack of preparedness to address real laboratory challenges (kappa = 0.23) and infrastructural limitations, such as insufficient computer facilities (kappa = 0.25), further hinder the effective implementation of virtual laboratories. Conclusions: The study underscores the transformative potential of virtual laboratories in chemistry education, serving as viable alternatives to traditional lab instruction. However, their successful implementation requires addressing existing challenges, such as improving digital infrastructure, providing instructor training, and enhancing accessibility. Universities should consider integrating virtual laboratories alongside real labs to optimize learning outcomes and foster technologically advanced educational environments.

  • More than just a Saturday morning cartoon: Utilizing participatory animation for digital health intervention promotion

    From: Journal of Participatory Medicine

    Date Submitted: Feb 17, 2025

    Open Peer Review Period: Mar 5, 2025 - Apr 30, 2025

    Digital-based health interventions (DHIs), defined as health services delivered electronically, have proven to be effective tools for health promotion. However, user retention remains low, an outcome...

    Digital-based health interventions (DHIs), defined as health services delivered electronically, have proven to be effective tools for health promotion. However, user retention remains low, an outcome predicted by insufficient integration of socio-cultural determinants and limited user engagement. This study explores participatory animation (PA), a methodology involving community partnerships in creating animated content as a strategy to mitigate retention rates. PA is a multi-step production process capable of creating engaging and efficacious multimedia deployable stimuli while leveraging a co-creation process through participants’ oral and visual design assessment. However, this method has been historically underutilized in health scholarship. The urgent need to develop effective DHIs emphasizes the promise of PA as a methodological frontier. This paper offers a perspective on PA’s practical and theoretical potential to improve digital intervention design and function from existing literature.

  • Enhancing LLMs for Identifying and Prioritizing Important Medical Jargons from Electronic Health Record Notes Utilizing Data Augmentation

    From: JMIR Preprints

    Date Submitted: Mar 7, 2025

    Open Peer Review Period: Mar 4, 2025 - Feb 17, 2026

    Background: OpenNotes allows patients to access their electronic health record (EHR) notes through online patient portals. However, EHR notes contain abundant medical jargon, which can be difficult fo...

    Background: OpenNotes allows patients to access their electronic health record (EHR) notes through online patient portals. However, EHR notes contain abundant medical jargon, which can be difficult for patients to comprehend. One way to improve comprehension is by reducing information overload and helping patients focus on the medical terms that matter most to them. Objective: In this study, we evaluated both closed-source and open-source Large Language Models (LLMs) for extracting and prioritizing medical jargon from EHR notes relevant to individual patients, leveraging prompting techniques, fine-tuning, and data augmentation. Methods: We evaluated the performance of closed-source and open-source LLMs on a dataset of 106 expert-annotated EHR notes. We tested various combinations of settings, including: i) general and structured prompts, ii) zero-shot and few-shot prompting, iii) fine-tuning, and iv) data augmentation. To enhance the extraction and prioritization capabilities of open-source models in low-resource settings, we applied data augmentation using ChatGPT and integrated a ranking technique to refine the training process. Additionally, to measure the impact of dataset size, we fine-tuned the models by incrementally increasing the size of the augmented dataset from 10 to 10,000 and tested their performance. The effectiveness of the models was assessed using 5-fold cross-validation, providing a comprehensive evaluation across various settings. We report the F1 score and Mean Reciprocal Rank (MRR) for performance evaluation. Results: Among the compared strategies, fine-tuning and data augmentation generally demonstrated higher performance than other approaches. Although the highest F1 score of 0.433 was achieved by GPT-4 Turbo, the highest MRR score of 0.746 was observed with Mistral7B when data augmentation was applied. Notably, by using f ine-tuning or data augmentation, open-source models were able to outperform closed-source models. Additionally, achieving the highest F1 score did not always correspond to the highest MRR score. We analyzed our experiment from several perspectives. First, few-shot prompting showed an advantage over zero-shot prompting in vanilla models. Second, when comparing general and structured prompts, each model exhibited different preferences. Third, finetuning improved zero-shot performance but sometimes degraded few-shot performance. Lastly, data augmentation yielded performance comparable to or even surpassing that of other strategies. Conclusions: The evaluation of both closed-source and open-source LLMs highlighted the effectiveness of prompting strategies, fine-tuning, and data augmentation in enhancing model performance in low-resource scenarios.

  • Feasibility of a Guided Web-Based Procrastination Intervention for College Students: an Open Trial

    From: JMIR Formative Research

    Date Submitted: Feb 20, 2025

    Open Peer Review Period: Mar 4, 2025 - Apr 29, 2025

    Background: College students commonly struggle with procrastination, which is linked to mental health complaints and poor academic performance. Guided e-health interventions can be effective in reduci...

    Background: College students commonly struggle with procrastination, which is linked to mental health complaints and poor academic performance. Guided e-health interventions can be effective in reducing procrastination. Objective: This study aims to examine the feasibility and acceptability of a new e-health intervention targeting procrastination for college students ('GetStarted') with guidance by student e-coaches. Methods: We conducted a single-arm study. Primary outcomes are satisfaction (CSQ-8), usability, (SUS-10) and adherence (completion rate). Secondary outcomes are changes to procrastination (IPS), depression (PHQ-9), stress (PSS-10), quality of life (MHQoL) and e-coaching satisfaction (WAI-I). Results: Of 734 participants that started the intervention, 335 (45.6%) completed the post-test. Students report being satisfied with the intervention (CSQ-8 M= 23.48; SD = 3,.23) and find it very usable (SUS-10 M = 34.39; SD = 4.52). Regarding adherence, 36.65% participants completed the intervention. On average participants completed 68.95% of the intervention. Participants showed a significant decrease in procrastination, depression and stress as well as an increase in quality of life from baseline to post-test to follow-up. Conclusions: The internet-based, student-guided intervention 'GetStarted' targeting procrastination appears to be acceptable and feasible for college students in the Netherlands.

  • Examining the Relationship Between Assertiveness and Anxiety in 1st and 2nd Year US Medical Students

    From: JMIR Formative Research

    Date Submitted: Mar 3, 2025

    Open Peer Review Period: Mar 4, 2025 - Apr 29, 2025

    The development of confident and assertiveness physicians through the process of medical education is essential for effective patient care. Through medical training, future physicians obtain the knowl...

    The development of confident and assertiveness physicians through the process of medical education is essential for effective patient care. Through medical training, future physicians obtain the knowledge and skillset necessary to accomplish this, but they may face stressors that negatively impact their mental health. This study aims to provide insights into the relationship between US medical student assertiveness and anxiety in the current pass/fail USMLE Step 1 medical education landscape. This was achieved by surveying 30 US MD student at a single Californian institution using the Simple Rathus Assertiveness Scale-Short Form and the General Anxiety Disorder Assessment 7. It was found that M1 participants were more likely to feel uncomfortable returning purchases than their M2 counterparts and that female participants were more likely to ask a loud theater couple to be quiet compared to males. These differences in responses by academic year and gender indicate areas of future study, particularly regarding the personality characteristics of current medical students and whether there are changing trends in medical student assertiveness and its association with medical student well-being.

  • Self-drawing after flipped classroom effectively improves electrocardiogram (ECG) reading skills of residents

    From: JMIR Medical Education

    Date Submitted: Mar 2, 2025

    Open Peer Review Period: Mar 3, 2025 - Apr 28, 2025

    Background: Although the training course of electrocardiogram (ECG) interpretation was started early in medical school, the accuracy in interpretation of 12-lead ECG is always a challenge issue. We co...

    Background: Although the training course of electrocardiogram (ECG) interpretation was started early in medical school, the accuracy in interpretation of 12-lead ECG is always a challenge issue. We conducted a pilot teaching program for comparing the effectiveness of conventional didactic lecture and self- drawing after flipped classroom (SDFC). Objective: The purpose of this study is to evaluate the effectiveness of self-drawing electrocardiograms and the impact of incorporating a flipped classroom approach in optimizing ECG teaching Methods: This study was conducted by postgraduate-year (PGY)-I residents at MacKay Memorial Hospital over three years. The study enrolled 76 PGY-I residents, who were randomized into three groups: conventional control group (group 1), self-drawing group (group 2) and SDFC group (group 3). All participants were provided with the same learning material and didactic lectures. Knowledge evaluation was performed using pre-tests and post-tests, and self-evaluation of competence and behavior change and program evaluations were conducted using questionnaires. Results: The feedback was positive, emphasizing the benefits of SDFC in combining theory and practical steps to approach ECG reading. The results of the written summative examination item were better and excellent in the SDFC group. Conclusions: Our study demonstrated the promising effects of SDFC on the recognition of ECG presentations, which could make up for the inadequacies of traditional classroom teaching. It can be incorporated into routine teaching if proven successful in a larger cohort. Clinical Trial: N/A

  • Addressing Ethical, Legal, and Social Implications of HealthTech in Education: Insights from Japan

    From: JMIR Formative Research

    Date Submitted: Feb 18, 2025

    Open Peer Review Period: Mar 3, 2025 - Apr 28, 2025

    The increasing application of Health Technology (HealthTech) in educational settings, particularly for monitoring students’ mental health, has garnered significant attention. These technologies, whi...

    The increasing application of Health Technology (HealthTech) in educational settings, particularly for monitoring students’ mental health, has garnered significant attention. These technologies, which range from wearable devices to digital mental health screenings, offer new opportunities for enhancing student well-being and strengthening support systems. Numerous studies have explored the ethical, legal, and social implications (ELSI) of HealthTech in the field of psychiatry, highlighting its potential benefits while also acknowledging the inherent complexities and risks that demand careful consideration. However, the ELSI related to the use of HealthTech in educational settings remains largely overlooked and insufficiently addressed. This study provides an overview of items that should be considered by researchers, teachers, and education boards or committees to promote HealthTech in the educational context. By adapting existing ELSI frameworks from educational technology and digital health, this study systematically reviews ethical concerns surrounding HealthTech in schools. Expert consultations were conducted through a project consisting of members with expertise related to HealthTech, including developers, a teacher, a school counselor, and university researchers, leading to the identification of 52 ELSI concerns categorized into eight domains: consent, rights and privacy, algorithms, information management, evaluation, utilization, role of public institutions, and relationships with private companies. Using Japan as a case study, we examine regulatory and cultural factors affecting HealthTech adoption in schools. The findings reveal critical challenges such as ensuring informed consent for minors, protecting student privacy, preventing biased algorithmic decision-making, and maintaining transparency in data management. Additionally, institutional factors, including the role of public education policies and private sector involvement, shape the ethical landscape of HealthTech implementation. The study underscores the need for a multi-faceted approach to mitigate risks such as data misuse, inequitable access, and algorithmic bias, ensuring the ethical and effective use of HealthTech in education. The fundamental ELSI framework for HealthTech, including privacy, consent, and algorithmic, can be applied to educational systems worldwide, while aspects related to public education policies should be considered in accordance with the specific context of each country and culture. Incorporating HealthTech into educational system helps address the barriers associated with traditional approaches, including limited resources, cost constraints, and logistical challenges. University and HealthTech company researchers, educators, and stakeholders should ensure that HealthTech projects consider diverse ELSI concerns at every stage before and during implementation.

  • Treatment of Gender in Research on Intervention Programs Targeting Social Isolation and Loneliness: A Scoping Review

    From: Interactive Journal of Medical Research

    Date Submitted: Feb 7, 2025

    Open Peer Review Period: Mar 3, 2025 - Apr 28, 2025

    Background: Social isolation and loneliness have considerable implications for health. In particular, gender is the most important factor contributing to social isolation and loneliness, with differen...

    Background: Social isolation and loneliness have considerable implications for health. In particular, gender is the most important factor contributing to social isolation and loneliness, with different genders adopting different strategies for coping with stress and participating in social interactions. However, because researchers tend to adopt different approaches when examining gender in the field of social isolation, mixed findings have been achieved. Objective: This study conducts a review of intervention programs for social isolation and loneliness, focusing on their consideration of gender. Methods: A scoping review was conducted as per the JBI Manual for the Synthesis of Evidence. A comprehensive literature search, including hand searching, was conducted across six English-language databases for articles and reports published in 2013–2023, with the papers retrieved by three co-authors. The study’s search strategy was developed in consultation with the librarian at X University. Results: The comprehensive search identified 1,282 relevant articles and reports. Among these, 11 articles were selected for analysis. Women were the majority of the participants in 10 of these studies. In particular, exercise workshops proved to be effective in alleviating social isolation and loneliness, and meditation and laughter therapy programs effectively mitigated loneliness. However, none of the studies considered gender-specific issues when devising their research objectives and outcomes. Conclusions: The study’s findings indicate that in the future, gender should be considered in the planning and execution of intervention programs for individuals experiencing social isolation and loneliness. Crucially, interventions that seek to encourage social interactions or promote social participation without considering gender-specific issues are unlikely to be effective.

  • The Impact of Social Media on Consumer Behavior, Audience Engagement, and Reputation Management in Hotel Selection and Booking Decisions

    From: JMIR Preprints

    Date Submitted: Mar 2, 2025

    Open Peer Review Period: Mar 2, 2025 - Feb 15, 2026

    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.

  • Mobile App Rating Scale (User Version) for the Assessment Community Health Worker Mobile Medical Application: a Qualitative Study

    From: JMIR Preprints

    Date Submitted: Feb 28, 2025

    Open Peer Review Period: Feb 28, 2025 - Feb 13, 2026

    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

  • Advancing Signaling Theory in Online Health Communities: Navigating Medical Asymmetry with a Holistic Approach

    From: Journal of Medical Internet Research

    Date Submitted: Feb 27, 2025

    Open Peer Review Period: Feb 27, 2025 - Apr 24, 2025

    Background: In online health communities, signaling theory has been widely applied to address information asymmetry and reduce uncertainty. Specifically, various signals are evaluated to convey the qu...

    Background: In online health communities, signaling theory has been widely applied to address information asymmetry and reduce uncertainty. Specifically, various signals are evaluated to convey the quality of healthcare services and influence patients' decision-making. However, the literature on signals in online health communities faces challenges, including arbitrary and fragmented classifications of signals and the lack of a common framework. Objective: To establish a common foundation for understanding the role of signals in online health communities, this study aims to provide a comprehensive framework for the signals conveyed in these communities and their influence on managing information asymmetry between physicians and patients. Methods: A systematic literature review using Narrative Analysis was conducted, summarizing 80 articles on signals in online health communities. The review aimed to classify, clarify, and explore the nature of these signals, their relationships, and the underlying mechanisms in the context of OHCs. Results: Among the 80 studies analyzed, 96.3% focused on the effects of one or more signals. However, only 2.5% examined the characteristics of signalers or their moderating effects, such as age, gender, and competence. Additionally, 31.3% explored signal interactions, including comparisons between online and offline signals and bundled services, while 30% investigated how environmental factors, such as uncertainty and consistency, affect signal transmission. Most studies (75%) concentrated on informative signals, with a notable increase in research on affective signals. Lastly, research on the interaction between affective signals and the environment remains limited. Conclusions: This framework provides a more comprehensive understanding of how signals in online health communities manage information asymmetry. It clarifies the construct of signals, explores their relationships, and outlines their mechanisms. Additionally, the study identifies gaps in the existing literature and offers recommendations for future research directions to enhance the role of online health communities in addressing medical asymmetry.

  • Patient-Centered Lupus Erythematosus Mobile Apps: Systematic Search and Evaluation by Patients and Physicians

    From: JMIR mHealth and uHealth

    Date Submitted: Feb 23, 2025

    Open Peer Review Period: Feb 27, 2025 - Apr 24, 2025

    Background: Lupus erythematosus (LE) is a chronic autoimmune disease that significantly impacts patients' quality of life. Photosensitivity is a key impairment that severely limits the quality of life...

    Background: Lupus erythematosus (LE) is a chronic autoimmune disease that significantly impacts patients' quality of life. Photosensitivity is a key impairment that severely limits the quality of life, especially in cutaneous lupus erythematosus (CLE), where exposure to sunlight can lead to rashes, exacerbations, and pain. In systemic lupus erythematosus (SLE), other manifestations such as joint pain, fatigue, and organ damage may contribute to decreased physical function and emotional distress. Mobile health applications (MHA) offer potential support for comprehensive disease management for the symptoms mentioned above. However, there is a lack of systematic analysis of available lupus management apps. Objective: This study aims to systematically identify publicly available German or English MHA for lupus management as well as to assess their quality by surveying both patients and physicians. Methods: A systematic search and assessment of German or English mobile apps for patients with lupus available in the Google Play Store and Apple App Store was conducted independently by two reviewers. The two apps that met all relevant criteria were then reviewed independently by seven physicians using the German Mobile Application Rating Scale (MARS) and the System Usability Scale (SUS). Subsequently, they were reviewed by five patients (three with SLE and two with CLE), using the user version of MARS (uMARS) and SUS. Additionally, the affinity for technology interaction (ATI) scale was collected from both patients and physicians to evaluate the technical affinity in both groups. Results: In total, 29 apps were available on the Apple Store and 26 on the Google Store, with 18 apps being present and downloadable on both platforms. Of the 18 apps, 16 were excluded because they did not meet the inclusion and exclusion criteria. Only two apps, Lupus Log and Lupus Minder met all the required criteria and were included in the study. The mean MARS scores varied from 2.61/5 to 4.17/5 and mean SUS from 17.5/100 to 100/100 between physicians. The app with the highest mean overall MARS score was Lupus Log, which was rated with 3.91/5 on average by the physicians. Patients evaluated the app with a comparably mean uMARS score (3.95/5). Technical affinity, objectified by ATI, was higher in patients than physicians (3.9 vs 3.68). Conclusions: Systematic identification and evaluation showed high-quality apps for patient-centered lupus MHA as indicated by MARS and uMARS scores greater than 3 for both Lupus Log and Lupus Minder.

  • Hidradenitis Suppurativa: An Analysis of Online Resources for Patient Use

    From: JMIR Dermatology

    Date Submitted: Feb 17, 2025

    Open Peer Review Period: Feb 27, 2025 - Apr 24, 2025

    Background: Diagnosis of Hidradenitis Suppurativa (HS) can take seven to ten years and has a long and complicated disease course. Many individuals may turn to online resources to gather information ab...

    Background: Diagnosis of Hidradenitis Suppurativa (HS) can take seven to ten years and has a long and complicated disease course. Many individuals may turn to online resources to gather information about their condition. While online resources can promote greater shared decision making and improve communication between patients and physicians, poor quality and low readability of websites can mislead patients with incorrect information. Objective: This study’s aim was to evaluate the quality and readability of HS websites found on Google and Bing in order to identify reliable, well-written resources that could help patients better understand their condition. Methods: The DISCERN Instrument and Flesch-Kincaid Readability metrics were used to evaluate the quality and readability of HS websites. Results: Google and Bing had average DISCERN scores of 54.05 and 59.83, respectively. Ten of the websites were either written or reviewed by a physician. Websites written or reviewed by physicians had statistically significant higher DISCERN scores (p = .018). The average reading grade level for Google was 10.78 ± 2.40, while the average for Bing was 10.48 ± 1.87. The NIH recommends that medical information be written at a 6th to 7th grade reading level. Of the ten articles written or reviewed by physicians, half of those articles met this criterion (Table 5). Conclusions: This study highlights the variable quality and readability of HS websites available on Google and Bing. Additionally, it provides websites that meet both high-quality standards and the NIH-recommended reading grade level.

  • Exploring the Impact of Online Coaching and Therapy on Adolescent Stress: A Retrospective Analysis of Bend Health

    From: JMIR Pediatrics and Parenting

    Date Submitted: Feb 6, 2025

    Open Peer Review Period: Feb 26, 2025 - Apr 23, 2025

    Background: Adolescence is a critical period for stress vulnerability, with high levels of stress linked to anxiety, depression, ADHD, and sleep problems. While digital mental health interventions (DM...

    Background: Adolescence is a critical period for stress vulnerability, with high levels of stress linked to anxiety, depression, ADHD, and sleep problems. While digital mental health interventions (DMHIs) are increasingly used to support adolescent mental health, little is known about their effectiveness in managing stress. Measurement-based collaborative care models (CoCM) in DMHIs may provide a structured approach to addressing adolescent stress, but research on their impact remains limited. Objective: The purpose of this study is to explore the effectiveness of a CoCM DMHI in managing stress among adolescents. We aimed to (1) quantify self-reported stress levels and identify factors associated with elevated stress, (2) assess changes in stress during care, and (3) explore key factors influencing stress reduction. Methods: Adolescents (ages 13-17 years) who receive coaching and therapy through a CoCM DMHI (Bend Health Inc.) completed mental health assessments at enrollment and monthly throughout care. Associations between stress levels and demographic factors, co-occurring mental health symptoms, and caregiver well-being were used to identify predictors of stress, and mixed-effects models were used to assess changes in stress during care. Results: At enrollment, 91.5% of adolescents reported elevated stress. Higher stress levels were associated with co-occurring mental health and sleep problems, as well as female sex (P’s<0.05). Caregiver stress (t2152=3.90, P<.001) and sleep problems (t2152=3.82, P<.001) were linked to adolescent stress, but caregiver burnout was not (t2152=1.02, P=.31). During care, 80.9% of adolescents experienced stress reductions, with improvements emerging after one month. In adolescents with a caregiver reporting co-occurring stress at enrollment, non-elevated caregiver stress during care was associated with larger improvements in adolescent stress (t248.73=-2.27, P=.024). Adolescents with elevated anxiety showed larger stress reductions compared to those with non-elevated anxiety (t3369=-2.77, P=.006). Conclusions: Stress levels were closely linked to co-occurring mental health symptoms and caregiver stress and sleep problems. A CoCM DMHI was effective in reducing adolescent stress, with reductions in caregiver stress and co-occurring elevated anxiety associated with larger improvements, demonstrating its potential for broader stress management. These findings underscore the need for DMHIs to incorporate family-centered approaches, and future research should explore ways to optimize DMHIs for long-term stress reduction and assess their impact on broader mental health outcomes.

  • Free-living Motor Symptoms Evaluation in Parkinson's patients through Smartwatches: Protocol for defining digital biomarkers

    From: JMIR Research Protocols

    Date Submitted: Feb 26, 2025

    Open Peer Review Period: Feb 26, 2025 - Apr 23, 2025

    Background: Monitoring motor symptoms in patients with Parkinson’s disease (PD) presents significant challenges due to the complex nature of symptom progression, variations in medication responses,...

    Background: Monitoring motor symptoms in patients with Parkinson’s disease (PD) presents significant challenges due to the complex nature of symptom progression, variations in medication responses, and the fluctuations that can occur throughout the day. Traditional neurological visits provide only a limited perspective of a patient’s overall condition, with challenges in achieving accurate and objective assessments of symptoms. To bridge this gap, extended monitoring in non-clinical settings could play a critical role in personalizing treatments and improving their efficacy. Wearable devices have emerged as potential tools for assessing PD symptom severity; however, studies integrating both in-clinic and free-living conditions, as well as multi-day monitoring, remain scarce. Defining digital biomarkers that provide valuable insights into motor symptoms could enable comprehensive monitoring and tracking of PD in various contexts, facilitating more precise medication adjustments and the implementation of advanced therapeutic strategies. Objective: The objective of this study is to collect a dataset for the proposal and definition of digital biomarkers of PD motor symptoms using wearable devices. Data will be gathered in a supervised setting and continuously in a remote free-living context during their normal daily activities, including PD patients and healthy controls. The goal is to identify reliable digital biomarkers that can effectively distinguish PD patients from healthy controls and classify disease severity in both supervised and unsupervised free-living environments. Methods: This article outlines a protocol for an observational case-control study aimed at assessing motor symptoms in PD patients using a smartwatch. The smartwatch will record accelerometer, gyroscope, and physical activity data. Participants will be instructed to perform a series of exercises guided via an smartphone. Measurements will be collected in two settings: a supervised clinical environment, with motor symptoms assessments conducted at the beginning and end of the study, and in an unsupervised free-living context for one week. In both settings, participants will be required to wear the smartwatch while performing the same set of exercises. In their daily routine, participants will be required to wear the smartwatch continuously throughout the day, removing it only at night for charging. Results: Subject recruitment and data collection started in December 2024 and will proceed until the spring of 2025. The planned sample size includes 15 participants with PD and 15 healthy controls. Conclusions: This study aims to generate a dataset of accelerometer and gyroscope signal data recorded from PD patients at various stages of the disease, alongside data from a control group, enabling robust comparative and impactful analyses. Additionally, the study seeks to develop analytical techniques capable of tracking PD symptoms in real-life scenarios, both in everyday settings and clinical environments. Clinical Trial: ClinicalTrials.gov NCT06817772; https://clinicaltrials.gov/ct2/show/NCT06817772

  • The Family and Friend Support Program: A Pilot Study Examining Usability, Acceptability, and Feasibility

    From: JMIR Formative Research

    Date Submitted: Feb 11, 2025

    Open Peer Review Period: Feb 20, 2025 - Apr 17, 2025

    Background: Despite the known psychosocial challenges associated with supporting a loved one using alcohol and other drugs (AOD), there is a scarcity of mental health and wellbeing interventions for a...

    Background: Despite the known psychosocial challenges associated with supporting a loved one using alcohol and other drugs (AOD), there is a scarcity of mental health and wellbeing interventions for affected family members and friends (AFFMs). Objective: This pilot study examines the usability, acceptability, and feasibility of the Family and Friend Support Program (FFSP; ffsp.com.au), a world-first, evidence-based online resilience and wellbeing program designed with and for people caring for someone using AOD. Methods: In 2021 (November-December), participants across Australia completed a baseline online cross-sectional survey that assessed impact of caring for a loved one using AOD (adapted Short Questionnaire for Family Members (Affected by Addiction)), and distress levels (Kessler-10 Psychological Distress Scale). Following baseline, participants were invited to interact with FFSP over 10 weeks. Post program and follow up surveys (10 and 14 weeks post-baseline, respectively) and semi-structured interviews assessed usability and acceptability of the program as well as help-seeking barriers. Results: Baseline surveys were completed by 131 AFFMs, with 37% completing the post-program survey and 24% completing the follow-up survey. On average, K-10 scores fell in the moderate to severe range at baseline. Overall, participants found FFSP easy to use and provided them with relevant, helpful, and validating information. Limitations included low program engagement and high attrition. Conclusions: Overall, FFSP appears to be a promising mental health intervention for AFFMs. This study builds on existing research finding high levels of distress among AFFMs, whilst highlighting the ongoing barriers to help-seeking. Limitations and future directions for refinements and efficacy evaluation of FFSP are discussed.

  • Assessing the Feasibility of Sequential Voice Input for Nursing Records in Clinical Settings

    From: Asian/Pacific Island Nursing Journal

    Date Submitted: Jan 21, 2025

    Open Peer Review Period: Feb 18, 2025 - Apr 15, 2025

    Background: Nursing records are crucial for maintaining patient care quality but impose a significant workload on nurses, diverting attention from direct care. Speech input technology offers hands-fre...

    Background: Nursing records are crucial for maintaining patient care quality but impose a significant workload on nurses, diverting attention from direct care. Speech input technology offers hands-free documentation, enabling simultaneous patient care and record-keeping. Despite its advantages, adoption has been slow due to concerns about patient privacy, technical challenges, and integration complexity with electronic medical records. Variability in nursing workflows and system adaptability further hinder implementation. These challenges have resulted in few successful cases being reported. This study examines the application of speech input technology in angiography rooms, which offers controlled environments conducive to testing due to their highly standardized workflows, patient privacy, and screen-free interaction requirements. Objective: This study is aimed to assess the feasibility of speech input technology in real-world clinical settings, focusing on its usability, effectiveness, and adaptability. Additionally, we seek to identify barriers to broader adoption and propose actionable strategies to overcome these challenges, enabling its integration into routine nursing practices. By addressing these barriers, we aim to pave the way for more efficient and accurate nursing documentation. Methods: This study was carried out at a Japanese university hospital, investigating intraoperative documentation in eight cases of PTCD and TACE. Events were recorded using both an existing voice dialogue system and traditional handwritten methods. Comparative analysis was performed to evaluate the number of events captured by each method. Surveys and structured interviews were conducted with nurses to gather qualitative insights into the system’s usability, practicality, and encountered challenges. To ensure patient safety and minimize workflow disruptions, the experimental setup was carefully designed to integrate devices seamlessly into the clinical environment while respecting existing protocols. Results: Speech input demonstrated effectiveness in capturing 50% to 100% of preoperative events and 40% to 100% of intraoperative events. However, its application in the postoperative phase was less effective, recording only 0% to 12% of events. Postoperative challenges were attributed to increased workload, technical issues, the need for repeated clarifications, and communication difficulties with both patients and staff while using the system. Despite these limitations, speech input showed potential for improving documentation efficiency when appropriately implemented. Conclusions: Key factors for successful application of speech input include ensuring patient privacy, starting with simple records, and incorporating backup documentation methods. Experiments conducted in real clinical settings, rather than simulations, emphasized the importance of designs that consider nurse-system interaction and the surrounding environment. While significant challenges remain, the findings highlight the potential of speech input technology to enhance nursing documentation efficiency and accuracy through optimized system designs and task selection. With continued refinement, this technology could reduce nurse workload and improve care quality.

  • A Phenomenological Study on Patient Experience with Extraction Retraction Orthodontic Regret

    From: Interactive Journal of Medical Research

    Date Submitted: Jan 28, 2025

    Open Peer Review Period: Feb 14, 2025 - Apr 11, 2025

    Background: Extraction retraction orthodontic (ERO) practices are commonly used to treat every malocclusion. Occasionally, patients express dissatisfaction over previous ERO treatment. Objective: This...

    Background: Extraction retraction orthodontic (ERO) practices are commonly used to treat every malocclusion. Occasionally, patients express dissatisfaction over previous ERO treatment. Objective: This study investigates patient experience who have had ERO intervention and expressed regret or dissatisfaction with this treatment. Methods: Semi-structured interviews were conducted with patients who have expressed regret over past ERO treatment. Interpretive phenomenological analysis (IPA) was used to derive themes from transcripts. Results: Eleven participants were recruited, gave ongoing informed consent, and participated in the semi-structured interview process. Six major themes were identified through IPA: “ERO Treatment Course”, “Lack of Informed Consent”, “Ocean of Grief and Trauma”, “Multifaceted Health Complaints”, “Finding Solutions and Coping Strategies”, and “Wishing There Was a Better Way”. Participants felt like they were not able to give informed consent for ERO due to a number of different reasons such as being too young, not being given accurate information on the risks, or being influenced parentally, culturally, or by the provider. Participants regret ERO due to a number of multifaceted health complaints including but not limited to sleep breathing disorders, craniofacial pain patterns, neuropsychobehavioural symptoms, and negative aesthetic outcomes, that they believe results from ERO. Conclusions: Patient regret following extraction retraction orthodontics is due to a lack of informed consent and negative health effects. Clinical Trial: CSREB 2022-12-001

  • Design of a System for Managing Complex Shift Patterns and Related Stress Levels for Blue Light Forces in the UK

    From: JMIR Formative Research

    Date Submitted: Dec 22, 2024

    Open Peer Review Period: Feb 11, 2025 - Apr 8, 2025

    Background: Blue Light services, such as police, paramedics, firefighters and other emergency responders, work under challenging conditions commonly associated with unpredictable schedules, complex sh...

    Background: Blue Light services, such as police, paramedics, firefighters and other emergency responders, work under challenging conditions commonly associated with unpredictable schedules, complex shift patterns, and high stress levels. These challenges negatively impact their mental wellbeing, physical health, and job performance, leading to potential health concerns such as fatigue, poor sleep, long-term physical disabilities, anxiety, and poor work-life balance. Existing digital interventions fail to address the challenging needs of these shift workers due to focusing solely on conventional 9-to-5 schedules. This gap highlights the need for tailored interventions that integrates shift management with health and wellbeing support for professionals with shift schedules. Objective: The objective of the study is to design and develop a co-created digital wellbeing application that integrates a shift management system. The designed solution aims to address the unique scheduling challenging and associated health concerns faced by Blue Light personnel, so has improve their wellbeing, organisation’s operational efficiency, and job satisfaction. Methods: A qualitative approach was employed for this research by incorporating Design Science Research Methodology (DSRM) with co-creation and user-centred design (UCD) principles. Five co-creation sessions, each lasting two hours, were conducted with key stakeholders, including police officers and shift management experts. Data from these sessions were analysed using thematic analysis to identify recurring patterns, user needs, and design functionalities. Results: The thematic analysis of data collected identified stressors such as inconsistent shift scheduling, limited flexibility, and inadequate support for work-life balance. Participant highlighted the need for a system capable of managing high volume schedule with real-time adaptability. A prototype was developed that included functionalities such bulk creation and modification of schedules, customisation of individual shift times, visualisation tools for monitoring and identifying shift trends and reusable base patterns for efficiency. The research demonstrated that integrating schedule management into a wellbeing app could provide personalised support, such as hydration reminders and relaxation techniques, based on users’ shift schedules. The prototype showed significant potential to reduce stress, enhance scheduling adaptability, and support the health and wellbeing of personnel in high stress profession. Conclusions: The co-created digital wellbeing intervention addresses major gaps in existing digital interventions by combining detailed shift management with health and wellbeing support tailored to the needs of Blue Light personnel. The study shows the importance of shareholder collaboration in designing robust and effective solutions for high-stress professions. Future work will expand the sample size, explore scalability to other emergency services, and incorporate longitudinal assessments to evaluate the system’s impact on reducing stress and improving overall wellbeing. By bridging the gap between operational needs and health requirements, this study offers a framework for developing digital solutions that enhance the quality of life and productivity of essential workers.

  • Predictive Modeling of Social Frailty in Older Adults through Digital Biomarkers: Insights from Fitbit-Derived Data on Circadian Rhythm and Heart Rate Changes

    From: JMIR mHealth and uHealth

    Date Submitted: Feb 8, 2025

    Open Peer Review Period: Feb 11, 2025 - Apr 8, 2025

    Background: Social frailty poses a potential risk even for relatively healthy older adults, necessitating development of early detection and prevention strategies. Recently, consumer-grade wearable de...

    Background: Social frailty poses a potential risk even for relatively healthy older adults, necessitating development of early detection and prevention strategies. Recently, consumer-grade wearable devices have gained attention for their ability to provide accurate sensor data, and digital biomarkers for social frailty screening could be calculated from these data. Objective: The objective of this study was to explore digital biomarkers associated with social frailty using sensor data recorded by Fitbit devices and to evaluate their relationship with health outcomes in older adults. Methods: This cross-sectional study was conducted in 102 community-dwelling older adults. Participants attending frailty prevention programs wore devices of the Fitbit Inspire series on their non-dominant wrist for at least seven consecutive days, during which step count and heart rate data were collected. Standardized questionnaires were used to assess the physical functions, cognitive functions, and social frailty, and based on the scores, the participants were categorized into three groups: robust, social pre-frailty, and social frailty. The sensor data were analyzed to calculate nonparametric and extended cosinor rhythm metrics, along with heart rate-related metrics. Results: The final sample included 86 participants who were categorized as robust (n = 28), social pre-frailty (n = 39), and social frailty (n = 19). The mean age of the participants was 77.14 years (SD 5.70), and 90.6% were women (n = 78). Multinomial logistic regression analysis revealed that the step-based rhythm metric, Intradaily Coefficient of Variation (ICV.st), was significantly associated with social pre-frailty. The heart rate metrics, including the delta resting heart rate (dRHR) and UpMesor.hr, showed significant associations with both social frailty and social pre-frailty. Furthermore, the standard deviation of the heart rate (HR.sd) and alpha.hr were significant predictors of social pre-frailty. Specifically, dRHR, defined as the difference between the overall average heart rate and resting heart rate (RHR), exhibited significant negative associations with social pre-frailty (odds ratio [OR] = 0.82, 95% confidence interval [CI] 0.68-0.97, p = 0.024) and social frailty (OR = 0.74, 95% CI 0.58-0.94, p = 0.015). Furthermore, analysis using a linear regression model revealed a significant association of the ICV.st with the Word List Memory (WM) score, a measure of cognitive decline (β = -0.04, p = 0.024). Conclusions: This study identified associations of novel rhythm and heart rate metrics calculated from the step count and heart rate recorded by Fitbit devices with social frailty. These findings suggest that consumer-grade wearable devices, which are low-cost and accessible, hold promise as tools for evaluating social frailty and its risk factors through enabling calculation of digital biomarkers. Future research should include larger sample sizes and focus on the clinical applications of these findings. Clinical Trial: UMIN-CTR

  • Sitting Baduanjin Combined with Acupoint Massage on Frailty in Maintenance Hemodialysis Patients: Study protocol of a randomized controlled trial

    From: JMIR Research Protocols

    Date Submitted: Feb 8, 2025

    Open Peer Review Period: Feb 10, 2025 - Apr 7, 2025

    Background: Patients with maintenance hemodialysis suffer from weakness due to prolonged dialysis treatment, such as the continuous decline of muscle strength in patients, which will have varying degr...

    Background: Patients with maintenance hemodialysis suffer from weakness due to prolonged dialysis treatment, such as the continuous decline of muscle strength in patients, which will have varying degrees of impact on human physiological, psychological and social functions. Effective non-pharmacological interventions can improve their mental health and quality of life. Objective: This study aimed to investigate the effects of sitting Baduanjin combined with acupoint massage on improving the frailty status of patients undergoing maintenance hemodialysis (MHD) and evaluate whether it can significantly improve their physical activity, alleviate depressive emotions, and comprehensively improve their quality of life. Methods: This study included 114 patients treated using MHD at the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine between March 2024 and October 2024. A randomized controlled study design was used. Patients who met the inclusion and exclusion criteria were randomly divided into three groups: the control group received only conventional hemodialysis and care, the acupoint massage group received acupoint massage treatment in addition to the control group treatment, and the sitting Baduanjin combined with acupoint massage group that received sitting Baduanjin combined with acupoint massage and the control group treatment. The clinical efficacy was comprehensively evaluated by comparing the FRAIL scale scores, grip strength, 10 times sit-to-stand test, Self-Rating Depression Scale scores, and quality of life (SF-36) scores before and after eight weeks of treatment among the three groups. Statistical analysis was conducted using the Statistical Package for the Social Sciences software (version 25.0). Results: The study began enrollment in September 2024. To date, 114 participants have finished the baseline questionnaires. Conclusions: The results of this study can provide scientific basis for the future treatment of patients with asthenia in hemodialysis. Clinical Trial: This study was registered under the registration number ITMCTR2024000798 on November 12, 2024,

  • The utility of measuring behavioral variability as a marker of provider uncertainty in clinical scenarios

    From: JMIR Preprints

    Date Submitted: Feb 2, 2025

    Open Peer Review Period: Jan 31, 2025 - Jan 16, 2026

    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.

  • Monkeypox Pandemic in Africa: Human Dissection Protocols, Precautions and Recommendations for Medical Education

    From: JMIR Preprints

    Date Submitted: Jan 28, 2025

    Open Peer Review Period: Jan 28, 2025 - Jan 13, 2026

    The management of human dissection labs and medical education are significantly impacted by the resurgence and spread of monkeypox (Mpox) as a global health issue, especially in Africa. Human dissecti...

    The management of human dissection labs and medical education are significantly impacted by the resurgence and spread of monkeypox (Mpox) as a global health issue, especially in Africa. Human dissection, a crucial part of anatomical education, requires strict procedures to protect medical students and instructors from the spread of infectious diseases. This article highlights important hazards and biohazard concerns while examining the difficulties presented by the Mpox pandemic in the context of cadaveric dissection. Through a review of literature, institutional protocols and epidemiological data, we propose improved personal protective equipment (PPE) regulations and disinfection guidelines tailored for African medical facilities. This article highlights the need for capacity-building programs to equip educators and students with skills to manage infectious disease risks effectively. By tackling these challenges, we aim to advance medical education safely while contributing to discussions on public health emergency adaptations and fostering pandemic resilience.

  • Innovative Water Purification for Hemodialysis: TiO₂ Nanoparticle-Based Microporous Filter Development and Analysis

    From: JMIR Preprints

    Date Submitted: Jan 27, 2025

    Open Peer Review Period: Jan 27, 2025 - Jan 12, 2026

    Background: Endotoxin contamination in conventionally purified water poses serious risks to hemodialysis patients, leading to complications such as inflammation and sepsis. Addressing these risks is e...

    Background: Endotoxin contamination in conventionally purified water poses serious risks to hemodialysis patients, leading to complications such as inflammation and sepsis. Addressing these risks is essential for enhancing patient safety and meeting global dialysis water quality standards. Advanced filtration technologies, such as titanium dioxide (TiO₂)-based nanoparticle filters, offer a promising approach to improve water purification processes in renal care. Objective: This study aimed to develop and evaluate the effectiveness of a TiO₂-based nanoparticle microporous filtration system for hemodialysis water purification. The objectives included analyzing the system's performance in reducing chemical contaminants (calcium, magnesium, aluminum, and lead) and microbiological contaminants (total viable count [TVC] and endotoxin units [EU]) across multiple renal centers. Methods: Water samples from three renal centers (RC1, RC2, and RC3) were analyzed pre- and post-filtration. TiO₂ nanoparticles were synthesized using the sol-gel method and characterized via Fourier Transform Infrared (FTIR) spectroscopy and Scanning Electron Microscopy with Energy Dispersive X-ray analysis (SEM/EDX). The microporous filter, fabricated with TiO₂ nanoparticles, silicon dioxide, and polyethylene glycol (PEG), was tested for its ability to remove contaminants. Analytical techniques included spectroscopy for chemical analysis and microbiological assays for contaminant quantification. Results: Post-treatment analysis revealed significant reductions in chemical contaminants, with removal efficiencies averaging 78% for calcium, 80% for magnesium, 81% for aluminum, and 76.6% for lead across all centers. Microbiological contamination was also substantially reduced, with 78–80% removal of TVC and 76–84.6% reduction in EU levels. FTIR analysis confirmed the presence of hydroxyl groups critical for adsorption, while SEM/EDX characterization revealed a crystalline structure with a particle size of 1.45 nm, pore size of 4.11 μm, filter height of 2.56 mm, and bulk density of 0.58 g/cm³. Conclusions: The TiO₂-based nanoparticle filtration system demonstrated high efficacy in removing chemical and microbiological contaminants, significantly improving water quality for hemodialysis. These results highlight its potential as a practical solution for renal centers, especially in resource-constrained settings. Further studies are needed to evaluate its long-term performance and feasibility for widespread adoption. Renal centers should consider adopting TiO₂-based nanoparticle filters to address persistent water quality challenges. Pilot implementations across diverse settings can provide insights into operational feasibility. Additional research should explore scalability, maintenance requirements, and cost-effectiveness to optimize integration into healthcare systems. This study introduces a practical and innovative solution to improve hemodialysis water purification. By effectively reducing both chemical and microbiological contaminants, the TiO₂-based filtration system has the potential to enhance patient safety and outcomes, particularly in settings where maintaining high water quality standards remains challenging.

  • From Glibness to Aggressiveness: The Dual Facets of Sociopathic Manipulation

    From: JMIR Preprints

    Date Submitted: Jan 27, 2025

    Open Peer Review Period: Jan 27, 2025 - Jan 12, 2026

    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.

  • Primary Care Services use as a Factor in Glycemic and Cholesterol Management in Type 2 Diabetes: A Retrospective Study

    From: JMIR Preprints

    Date Submitted: Dec 11, 2024

    Open Peer Review Period: Dec 11, 2024 - Nov 26, 2025

    Background: The early detection of pre-symptomatic individuals and the proactive implementation of health guidance through regular primary care visits are essential strategies for the secondary and te...

    Background: The early detection of pre-symptomatic individuals and the proactive implementation of health guidance through regular primary care visits are essential strategies for the secondary and tertiary prevention of diabetic complications. An interdisciplinary team approach significantly enhances the care of patients with diabetes, integrating the expertise of physicians, dietitians, clinical navigators, pharmacists, and mental health professionals. Central to this collaborative model is the active participation of patients, who play a vital role in managing their health outcomes. This integrated approach facilitates comprehensive care, promoting better health management and improved quality of life for individuals with diabetes. Objective: We aimed to evaluate the association among regular primary care visits, hemoglobin A1C (HbA1C) and low-density lipoprotein (LDL) levels in patients with type 2 diabetes mellitus. Methods: We randomly sampled data from 200 patients’ electronic medical records. Mann–Whitney and chi-square tests were used to investigate the association between glycemic control lipid profile and the number of patient visits. Results: The mean age of the participants was 61.78 years and the average body mass index was 34.5 kg/m2. Females constituted 61.79% of participants. The predominant race seen at the clinic was Black (43.8%), followed by White (42.69%). Patient adherence to scheduled visits was not statistically significantly associated with either HbA1C or LDL (chi-square = 1.1, p-value = 0.29 for HbA1c and chi-square = 1.12, p-value = 0.99 for LDL). Conclusions: In the sample studied, no statistically significant association existed between adherence to primary care visits and either HbA1C or LDL levels. This data can guide physicians to invest on favoring high-quality primary care contact rather than high frequency of visits. Clinical Trial: IRB approved

  • Hidden Danger of Internet: Exploring the Influence of Socioeconomic Factors on Internet Health Information Seeking Among Academic Staff in Bayelsa State, Nigeria

    From: JMIR Preprints

    Date Submitted: Oct 1, 2024

    Open Peer Review Period: Oct 1, 2024 - Sep 16, 2025

    Background: The increasing reliance on the internet for health information necessitates understanding various factors influencing health information-seeking behaviors and satisfaction levels among use...

    Background: The increasing reliance on the internet for health information necessitates understanding various factors influencing health information-seeking behaviors and satisfaction levels among users. These insights can inform strategies to improve the quality and accessibility of health information. Objective: This study aimed to investigate the socio-demographic factors affecting internet health information-seeking behaviors, the types of health information sought, the timeliness and trust associated with information sources, and user satisfaction regarding online health information. Methods: A quantitative cross-sectional survey was conducted among 376 participants, utilizing structured questionnaires to collect data on various aspects of health information-seeking behavior. Statistical analyses, including Chi-square tests and frequency distributions, were performed to evaluate the relationships between socio-demographic factors and health information-seeking behaviors. Results: The findings revealed significant associations between the duration of teaching, health insurance status, estimated income, and the duration of employment with health information-seeking behaviors (p < 0.05). The most sought-after health information types included specific medical conditions and treatment methods. Satisfaction levels varied across categories, with a majority of respondents expressing positive sentiments toward online searches, website information sources, and the usefulness of the information received. Conclusions: The study underscores the importance of socio-demographic factors in shaping health information-seeking behaviors and highlights the need for improved credibility and trust in online health information sources. Stakeholders in health communication should prioritize the development of reliable online health information platforms and enhance user education on navigating these resources effectively. This study contributes valuable insights into the dynamics of health information-seeking behaviors, emphasizing the critical role of socio-demographic factors and the need for high-quality, trustworthy health information in promoting informed health decisions.

  • Artifacts of Glory and Pain: Evolving Cultural Narratives on Confederate Symbolism and Commemoration in a New Era of Social Justice, a Personal Perspective

    From: JMIR Preprints

    Date Submitted: Jul 6, 2024

    Open Peer Review Period: Jul 6, 2024 - Jun 21, 2025

    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.

  • Transport mobility restrictions as a pandemic response: a case study Germany

    From: JMIR Preprints

    Date Submitted: Jun 22, 2024

    Open Peer Review Period: Jun 22, 2024 - Jun 7, 2025

    Background: The COVID19 pandemic has caused a large number of infections and fatalities, causing administrations at various levels to limit public mobility. This paper analyzes the complex associatio...

    Background: The COVID19 pandemic has caused a large number of infections and fatalities, causing administrations at various levels to limit public mobility. This paper analyzes the complex association between the stringency of restrictions, public mobility, and reproduction rate (R-value) on a national level for Germany. Objective: The goals were to analyze; a) the correlation between government restrictions and public mobility and b) the association between public mobilities and virus reproduction. Methods: In addition to correlations, a Gaussian Process Regression Technique is used to fit the interaction between mobility and R-value. Results: The main findings are that: (i) Government restrictions has a high association with reduced public mobilities, especially for non-food stores and public transport, (ii) Out of six measured public mobilities, retail, recreation, and transit station activities have the most significant impact on COVID19 reproduction rates. Conclusions: A mobility reduction of 30% is required to have a critical negative impact on case number dynamics, preventing further spread.