JMIR Research Protocols最新文献

{"title":"Extraction of Pain Severity and Functional Interference From Clinical Narratives Using Domain-Informed Large Language Models: Protocol for a Development and Validation Study.","authors":"Xiaoyi Zhang, Christopher R Wilson, Hannah Eyre, David E Reed Ii, Travis Y Hee Wai, Alexander Kloehn, Ethan W Rosser, Gang Luo, Steven B Zeliadt","doi":"10.2196/96346","DOIUrl":"10.2196/96346","url":null,"abstract":"<p><strong>Background: </strong>Chronic pain is a leading cause of disability and requires multidimensional assessment of pain intensity and functioning, yet electronic health records rarely capture these measures systematically. By contrast, surveys collecting patient-reported outcomes can assess pain over multiple dimensions but remain resource-intensive and difficult to scale for continuous population-level monitoring.</p><p><strong>Objective: </strong>The objective of this study is to develop and validate a domain-informed natural language processing framework to derive pain severity and functional interference outcomes from unstructured clinical narratives. We aim to demonstrate that natural language processing-derived outcomes can serve as a reliable, scalable surrogate for resource-intensive patient-reported surveys.</p><p><strong>Methods: </strong>This study uses a retrospective cohort of 3725 Veterans with chronic musculoskeletal pain initiating complementary and integrative health therapies across 18 Veterans Health Administration Whole Health Flagship sites (2021-2023). The dataset encompasses longitudinal patient-reported outcome surveys serving as the benchmark, linked with unstructured clinical narratives from the Veterans Health Administration electronic health record. Guided by established psychometric instruments and subject matter expert (SME) input, we developed a seed lexicon and annotation guidelines to identify language distinguishing 3 pain domains: pain severity, interference with enjoyment of life, and interference with general activities. Preliminary large language model (LLM) prompting was used to identify 600 candidate encounters (200 per domain) from 6747 notes across 260 patients for SME annotation, forming a ground truth validation sample. Two candidate LLMs will be evaluated on this sample; the best-performing LLM will generate a large library of span-level annotations to train a scalable, lightweight language model. The study uses a 3-stage validation process: (1) documentation completeness of pain interference in clinical narratives against SME-annotated references; (2) inference accuracy of the LLM-as-annotator and the fine-tuned lightweight model against SME annotations across note-level classification and span-level localization; and (3) concordance between the lightweight model's output and patient-reported pain, enjoyment, and general activity scores across a range of temporal windows.</p><p><strong>Results: </strong>As of July 2026, the cohort of 3725 Veterans has been identified and linked to clinical notes. The seed lexicon and annotation guidelines have been developed. Applying a developmental LLM to screen 6747 text notes in 6642 unique encounters over a 7-month period for 260 patients, at least 1 of the 3 pain domains was identified in 75% of notes and 99% of patients. SME validation at the encounter level is in progress. Final results from the subsequent knowledge distillation and validation stages ar","PeriodicalId":14755,"journal":{"name":"JMIR Research Protocols","volume":"15 ","pages":"e96346"},"PeriodicalIF":1.6,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13645315/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149127577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Intelligence, Machine Learning, and Deep Learning Approaches for Attention-Deficit/Hyperactivity Disorder Diagnosis: Protocol for a Scoping Review.","authors":"Benedict Onochie Ibe, Amir Aly, Shaymaa S Al-Juboori, Emmanuel Ifeachor, Rohit Shankar","doi":"10.2196/99551","DOIUrl":"10.2196/99551","url":null,"abstract":"<p><strong>Background: </strong>Attention-deficit/hyperactivity disorder (ADHD) affects over 366 million adults and 139 million children worldwide, yet diagnosis remains fundamentally subjective, relying on clinical interviews, behavioral observations, and rating scales that yield inconsistent results across practitioners and settings. Artificial intelligence (AI), machine learning (ML), and deep learning (DL) offer a paradigm shift toward objective, data-driven diagnosis by detecting complex patterns across neuroimaging, electrophysiology, and digital biomarkers that elude conventional assessment. Although AI-based ADHD research has grown exponentially, no comprehensive synthesis examines the full spectrum of data modalities, validation practices, and clinical translation readiness. This gap limits our understanding of which approaches are most promising for real-world implementation.</p><p><strong>Objective: </strong>This scoping review will visually map the current evidence on AI-based ADHD classification with respect to predictive accuracy, data forms, data features, generalizability, and interpretability of models.</p><p><strong>Methods: </strong>This scoping review will use the Joanna Briggs Institute approach to scoping reviews and follow the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. Five electronic databases (IEEE Xplore, Scopus, PubMed, Web of Science, and ACM Digital Library) will be systematically searched for peer-reviewed studies published between January 2019 and April 2026. Empirical studies in English involving the use of AI, ML, DL, or explainable AI to diagnose ADHD with a total sample size greater than 100 participants (ADHD and control groups combined) and a non-ADHD control group (individuals with typical development or healthy individuals) will be included. Two independent reviewers will screen the titles, abstracts, and full texts, and any conflicts will be resolved through either discussion or arbitration. A standardized Microsoft Excel template will be used to extract data that will include the following: bibliographic data, data modalities, data models, data validation approaches, performance metrics, and explainability approaches. Thematic and narrative analysis will be used to synthesize findings on 4 research questions that will address model performance, data modality contributions, data characteristics, and interpretability methods.</p><p><strong>Results: </strong>The scoping review began in December 2025. Analysis and screening are in progress, with the scoping review expected to be completed and submitted for publication in June 2026.</p><p><strong>Conclusions: </strong>This scoping review will provide the first comprehensive synthesis of AI-, ML-, and DL-based ADHD diagnostic classification studies, mapping the evidence across data modalities, validation practices, interpretability methods, and clinical translation readiness. Findings","PeriodicalId":14755,"journal":{"name":"JMIR Research Protocols","volume":"15 ","pages":"e99551"},"PeriodicalIF":1.6,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13645319/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149127544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A US-Based National Virtual Cohort of People Living With HIV at Risk for Viral Nonsuppression: Protocol for the EPI-LoVE Prospective Cohort Study.","authors":"Marjan Javanbakht, Lisa B Hightow-Weidman, Sean D Young, Nora E Rosenberg, Kathryn E Muessig, Sarah Schoetz Dean, Aimee Rochelle, Warren Scott Comulada, Pamina M Gorbach","doi":"10.2196/108764","DOIUrl":"10.2196/108764","url":null,"abstract":"<p><strong>Background: </strong>Despite advances in HIV treatment, many people living with HIV fail to achieve or maintain viral suppression. Individuals who experience interruptions in HIV care, adherence challenges, and viral nonsuppression are often underrepresented in clinic-based cohort studies. Virtual cohort methodologies offer opportunities to recruit, engage, and retain these populations while integrating longitudinal behavioral, biomarker, and digital engagement data needed to characterize dynamic changes in HIV care engagement and viral suppression.</p><p><strong>Objective: </strong>The Exploring, Predicting, and Intervening on Long-Term Viral Suppression Electronically (EPI-LoVE) study was developed to establish a national virtual cohort of people living with HIV with current viral nonsuppression or at an elevated risk of future viral nonsuppression. We describe the study design, recruitment, data collection methods, retention strategies, and baseline cohort characteristics.</p><p><strong>Methods: </strong>Participants were recruited through digital advertising, a national HIV care provider network, and referrals from previous research studies. Eligible participants were adults living with HIV who were currently virally unsuppressed or considered at elevated risk of future viral nonsuppression based on a history of detectable HIV viral load, recent missed HIV care appointments, or a qualifying mental health diagnosis. Following online screening, participant eligibility was confirmed through telephone verification and supporting documentation. Participants completed online surveys every 3 months and HIV viral load assessments every 6 months over 24 months. Data were collected through a study-specific mobile health platform integrating longitudinal behavioral surveys, remote biomarker collection, app engagement metrics, and frequent \"Speak Up\" microassessments of time-varying behavioral and psychosocial factors associated with HIV care engagement and viral suppression.</p><p><strong>Results: </strong>The study was funded in May 2023. Participant recruitment occurred between February 2024 and June 2025, and longitudinal data collection is ongoing, with study findings anticipated in spring 2028. A total of 4789 individuals expressed interest in the study, 2739 completed screening, and 2262 met eligibility criteria. A total of 1109 consented, and 1051 enrolled. Among the 2262 eligible participants, 63.4% (n=1435) qualified based on a detectable viral load during the previous 12 months, whereas the remainder qualified based on recent missed HIV care appointments or a qualifying mental health diagnosis. Among the 1051 participants, the cohort was predominantly Black or African American (n=677, 64.4%), with a median age of 36 (IQR 31-43) years; 70.8% (n=744) reported recent substance use, and 63.7% (n=669) screened positive for moderate-to-severe depressive symptoms. Baseline HIV viral load data were obtained from 863 (82.1%) participants.</p","PeriodicalId":14755,"journal":{"name":"JMIR Research Protocols","volume":"15 ","pages":"e108764"},"PeriodicalIF":1.6,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13645198/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149127560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Codevelopment, Implementation, and Evaluation of an AI-powered Conversational Interface for Tobacco Cessation: Protocol for a Single-Group Pre-Post Study.","authors":"Monika Arora, Rajmohan Panda, Shalini Bassi, Kshitij Jadhav, Prabhat Chand, Monirujjaman Biswas, Mohai Menul Biswas, Tina Rawal, Navpreet Kaur, Sharmila Pimple, Srabana Misra Bhagabaty","doi":"10.2196/82264","DOIUrl":"10.2196/82264","url":null,"abstract":"<p><strong>Background: </strong>Despite several efforts to expand tobacco cessation services through tobacco cessation centers (TCCs) and quit lines, key operational challenges still persist. Recently, AI-based digital interventions have shown promise globally for smoking cessation; however, they remain underused in tobacco cessation strategy in the Indian context.</p><p><strong>Objective: </strong>This study aimed to (1) codevelop the conversational interface with beneficiaries and cessation providers; (2) assess its feasibility, acceptability, usability, and user engagement; and (3) evaluate its effectiveness in promoting attempts and intention to quit tobacco.</p><p><strong>Methods: </strong>The study consists of three phases: (1) codeveloping the comprehensive AI-powered Conversational Interface to Quit Tobacco (CARE) conversational interface through in-depth interviews with tobacco users, counselors, and health care professionals; (2) feasibility testing with tobacco users to assess engagement, usability, and acceptability; and (3) 6-month effectiveness testing using pre-post surveys. The CARE conversational interface will be developed using a retrieval-augmented generation-based large language model by the Indian Institute of Technology (Bombay, Maharashtra, India), delivering personalized, multilingual cessation support via a chatbot integrated into a mobile app. Key evaluation measures will use validated tools such as the Fagerström Test for Nicotine Dependence, Smoking Self-Efficacy Questionnaire, Decisional Balance Scale, and a Knowledge Score Questionnaire. Data will be analyzed using mixed methods, including thematic analysis for qualitative data and descriptive statistics and a multivariate logistic regression for quantitative data.</p><p><strong>Results: </strong>The CARE study was funded in March 2025 and is being implemented across 3 TCCs. Preparatory activities, including tool development, site engagement, ethics approval, and trial registration (CTRI/2024/11/076916), were completed in 2025. Phase 1 (codevelopment) is scheduled from February to August 2026, followed by phase 2 (feasibility testing) from September 2026 to August 2027, and phase 3 (effectiveness assessment) from September to November 2027. Data analyses are expected to be completed by late 2027, with key findings on feasibility, acceptability, usability, user engagement, and preliminary cessation outcomes targeted for peer-reviewed publication from 2027 onward.</p><p><strong>Conclusions: </strong>The CARE study will attempt to introduce a novel, culturally tailored conversational interface targeting both smokers and smokeless tobacco users in India by integrating AI-based solutions as an adjunct to conventional counseling at the TCCs. Given the single-group pre-post design without a control arm, feasibility and effectiveness findings will be interpreted as preliminary and hypothesis-generating rather than causal evidence of intervention impact. The intervention app","PeriodicalId":14755,"journal":{"name":"JMIR Research Protocols","volume":"15 ","pages":"e82264"},"PeriodicalIF":1.6,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13687822/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149127630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Remote Longitudinal Tracking of Sleep, Depression, and Cognition Across Early Adolescence: Protocol for a Longitudinal Observational Study.","authors":"Katharine C Simon, Lia Galut, Spencer Polk, Shun Iwata, Weining Shen, Mahyar Abbasian, Amir Rahmani, Uma Rao, Jessica L Borelli, Sara C Mednick","doi":"10.2196/86345","DOIUrl":"10.2196/86345","url":null,"abstract":"<p><strong>Background: </strong>Depression in adolescents is a growing public health concern, with 3.5 million youth in the United States experiencing a depressive episode each year. When symptoms emerge in early adolescence, they can have lasting psychological, physical, and cognitive consequences, highlighting the urgent need for proactive intervention. Insufficient sleep-characterized by short duration, irregular timing, and poor quality-is bidirectionally linked to depression and associated with impaired cognitive performance.</p><p><strong>Objective: </strong>This protocol provides the map for a study tracking sleep patterns and neurophysiology, as well as a range of depressive symptoms, and their dynamic interaction in shaping longitudinal cognitive trajectories.</p><p><strong>Methods: </strong>Fifty-six youth aged 9 to 13 (mean 11.01, SD 1.39) years were enrolled in a longitudinal measurement burst design comprising 4 assessment waves at baseline, 4, 8, and 12 months. We recruited a sample of youth with a range of depressive symptom severity. Each wave included 7 consecutive days of monitoring during which participants used a personalized mobile health (mHealth) platform, HowRU app, developed by the study team, to report daily sleep patterns, thrice-daily ecological momentary assessments (EMAs), and completed a series of cognitive tasks. Youth and parents also completed validated psychosocial questionnaires to assess mood, behavioral concerns, mental health, and sleep. Sleep and physical activity were monitored remotely using a Garmin VivoSmart 5 watch and Interaxon Muse S headbands. Sleep-dependent cognitive performance was assessed with 2 declarative memory tasks (Word-Pair Associates task [WPA] and Minecraft Memory and Navigation [MMN] task), a procedural memory task (Motor Sequence task), and 2 executive functioning tasks (Operation Span [OSpan] task and Rule Switch task [RST]). For the memory tasks, participants completed training and immediate testing in the evening, followed by a retention test the following morning. The OSpan task and Rule Switch were administered twice daily (morning and evening). For all tasks, stimuli were randomized and counterbalanced across participants and testing sessions.</p><p><strong>Results: </strong>Funding was obtained from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (grant K08 HD107161), with a budget period of August 1, 2022, to July 31, 2027. Participant enrollment occurred May 2023 through October 2024. Data collection began in July 2023 and was completed in October 2025. Study participant retention and adherence rates for sleep diaries, cognitive tasks, and questionnaires were high. Primary outcomes of the study are anticipated to be published in fall 2026.</p><p><strong>Conclusions: </strong>This protocol provides a robust and reproducible framework to longitudinally track youth with a range of depressive symptoms in the real world using mHealth platforms ","PeriodicalId":14755,"journal":{"name":"JMIR Research Protocols","volume":"15 ","pages":"e86345"},"PeriodicalIF":1.6,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13641314/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149109437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative Efficacy and Acceptability of Transdiagnostic Psychotherapies for Emotional Disorders: Protocol for a Network Meta-Analysis of Randomized Controlled Trials.","authors":"Qiaosi Cai, Yihan Zeng, Noelia Jiménez-Orenga, Clara Miguel, Mathias Harrer, Pim Cuijpers, Amanda Díaz-García, Qun Ye","doi":"10.2196/104791","DOIUrl":"10.2196/104791","url":null,"abstract":"<p><strong>Background: </strong>Emotional disorders-primarily anxiety and unipolar depressive disorders-are highly prevalent, disabling, and frequently comorbid. Disorder‑specific cognitive behavioral therapy (DS‑CBT) is considered a gold standard treatment, yet it can be inefficient in the context of high comorbidity and service constraints. Transdiagnostic psychotherapies that target shared maintaining mechanisms (eg, emotion dysregulation and neuroticism) have been developed, including the Unified Protocol, transdiagnostic behavior therapy, emotion regulation therapy, and various transdiagnostic internet-delivered cognitive behavioral therapy protocols. Recent meta-analyses suggest that transdiagnostic interventions are effective or likely effective, but a comprehensive comparative evaluation across different transdiagnostic protocols, DS‑CBT, other evidence‑based psychotherapies, and control conditions is lacking.</p><p><strong>Objective: </strong>This study aims to conduct a network meta-analysis (NMA) to compare the efficacy and acceptability of various transdiagnostic therapies (eg, the Unified Protocol, transdiagnostic behavior therapy, and emotion regulation therapy), DS-CBT, other evidence-based active therapies (eg, acceptance and commitment therapy, behavioral activation, and mindfulness-based cognitive therapy), and control conditions (waitlist or care as usual) in improving symptoms in adults with anxiety and/or depressive disorders and generate a probabilistic ranking of their efficacy.</p><p><strong>Methods: </strong>This meta-analysis will include randomized controlled trials from PubMed, Embase, PsycInfo, and the Cochrane Library, complemented by existing meta‑analytic research domain databases for depression and anxiety. Eligible participants are adults (≥18 years) with a principal diagnosis of anxiety and/or unipolar depressive disorder according to established diagnostic classification systems (eg, any version of the Diagnostic and Statistical Manual of Mental Disorders or International Classification of Diseases, 10th or 11th revisions) or scoring above a validated cutoff on anxiety or depression scales. Primary outcomes are continuous measures of anxiety and depressive symptom severity at the posttreatment time point; secondary outcomes include study dropout (acceptability) and response or remission where available. We will perform random-effects network meta-analyses within a frequentist framework using the netmeta package in R to estimate relative treatment effects and P scores for treatment rankings and examine transitivity and consistency. We will conduct additional Bayesian NMAs as sensitivity analyses using the surface under the cumulative ranking curve for ranking.</p><p><strong>Results: </strong>As of September 2026, the literature search has been completed, and title and abstract screening is ongoing. Data analysis will be conducted in late 2026. We expect the meta-analysis to be completed and submitted for publica","PeriodicalId":14755,"journal":{"name":"JMIR Research Protocols","volume":"15 ","pages":"e104791"},"PeriodicalIF":1.6,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13684113/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149110042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of Immersion Level and Game Type on Virtual Reality Interventions for Upper Limb Function After Stroke: Protocol for a Systematic Review and Meta-Analysis.","authors":"Dayenne Jeneffer Souza da Silva, Vitor Leandro da Cunha, Luanna Barbara de Araújo Farias, Lara Cecília de Araújo Carlos, Candice Simões Pimenta de Medeiros, Edgar Ramos Vieira, Fabrícia Azevedo da Costa Cavalcanti","doi":"10.2196/95135","DOIUrl":"10.2196/95135","url":null,"abstract":"<p><strong>Background: </strong>Upper limb impairment is a common consequence of stroke, affecting independence and quality of life. Virtual reality (VR) interventions, including serious games designed for therapeutic purposes and commercial games developed primarily for entertainment, have been increasingly used for poststroke upper limb rehabilitation. Evidence comparing the effectiveness of these game types on functional outcomes remains unclear.</p><p><strong>Objective: </strong>This systematic review protocol aims to determine whether serious and commercial VR games differentially impact upper limb function, measured by the Action Research Arm Test, in adults after stroke. Secondary outcomes will include upper limb motor function assessed using the Fugl-Meyer Assessment-Upper Extremity, Box and Block Test, Motor Activity Log, Jebsen-Taylor Hand Function Test, and Wolf Motor Function Test; functional independence assessed using the Functional Independence Measure and Barthel index; and adherence indicators, including dropout rates and session completion. Secondary objectives include evaluating pooled VR effects vs conventional therapy (CT) and exploring potential moderators, such as VR immersion level and stroke chronicity.</p><p><strong>Methods: </strong>Parallel randomized controlled trials involving adults (aged ≥18 years) with ischemic or hemorrhagic stroke in the acute, subacute, or chronic phases will be included. Interventions using serious or commercial VR games (nonimmersive, semi-immersive, or fully immersive) delivered alone or combined with CT will be considered. Studies using nongamified VR, digital technologies without VR, or augmented reality not integrated into VR will be excluded. Eligible comparators include conventional physiotherapy, occupational therapy, usual care, educational interventions, or no therapy. This protocol was developed in accordance with the PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Protocols) guidelines. Systematic searches will be conducted in the PubMed (MEDLINE), Web of Science, Embase, Scopus, Virtual Health Library, ScienceDirect, Physiotherapy Evidence Database, Cochrane Central Register of Controlled Trials, ClinicalTrials.gov, Brazilian Clinical Trials Registry, World Health Organization (WHO) International Clinical Trial Registry Platform, and ISRCTN Registry databases from inception to February 2026. Data extraction will be performed independently by 2 reviewers, and risk of bias will be assessed using the Cochrane risk of bias 2.0 tool. Meta-analyses will be conducted when clinical and methodological homogeneity permits. A random-effects model is planned; however, the final choice of model will be based on the level of heterogeneity observed at the time of analysis. Subgroup analyses will explore stroke phase, immersion level, intervention dosage, and concomitant therapy.</p><p><strong>Results: </strong>Data collection is planned from inception to February 202","PeriodicalId":14755,"journal":{"name":"JMIR Research Protocols","volume":"15 ","pages":"e95135"},"PeriodicalIF":1.6,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13684114/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149110193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effectiveness of Immersive and Embodied Enhancement via \"Virtual Reality\" on the Sustainability of Hand Hygiene Compliance:Protocol for a Randomized Controlled Trial of a School-Based Training Program.","authors":"Siu-Lun Chow, King-Wa Fu, Isaac Chun-Hai Fung, Patrick Ip, Mike Yat-Wah Kwan, Hai Liang, Frank Reichert, Zion Tsz Ho Tse","doi":"10.2196/107264","DOIUrl":"10.2196/107264","url":null,"abstract":"<p><strong>Background: </strong>Regular and sustained handwashing is a key preventive measure for reducing the transmission of infectious diseases among school-aged children. Virtual reality (VR) interventions have demonstrated potential to facilitate behavioral change by creating immersive environments in which behavioral and environmental variables can be systematically manipulated. Compared with conventional verbal or video-based instruction, VR-based handwashing education may provide students with more interactive and experiential learning opportunities, and may improve cleaning of commonly missed areas, such as the wrists. However, evidence on school-based VR interventions for handwashing education in Hong Kong remains limited.</p><p><strong>Objective: </strong>This study aims to evaluate the effectiveness of a customized VR intervention for teaching handwashing skills to secondary school students in Hong Kong. The intervention teaches the 7-step handwashing technique recommended by the Centre for Health Protection, Department of Health, Hong Kong Special Administrative Region. The study will assess changes in handwashing performance and examine the longer-term effects of the intervention on handwashing habits, behavioral determinants, and hand hygiene.</p><p><strong>Methods: </strong>A 3-arm randomized controlled trial will be conducted with approximately 500 students allocated to 3 groups on a school-class basis. Each group will receive 2 educational sessions with different interventions over 1 school year (10 months). The first intervention group will receive 2 VR game sessions focusing on handwashing skills. The second intervention group will receive 1 VR game session followed by 1 video session reviewing participants' gameplay from the first session. The control group will receive 2 video-based handwashing education sessions. Pre- and postintervention UV fluorescence imaging of participants' hands will serve as the primary outcome measure. The secondary outcomes will be assessed through surveys administered before the intervention, immediately after the intervention, and at a 4-month follow-up. The survey will measure self-efficacy, hand hygiene knowledge, handwashing habits and intentions, attitudes, subjective norms, perceived behavioral control, VR embodiment, and VR experience.</p><p><strong>Results: </strong>The project was funded in March 2026, and recruitment was conducted from May to August 2026. As of August 2026, 9 schools had confirmed participation, with approximately 500 students expected to be recruited. Data collection is scheduled from September 2026 to June 2027. Data analysis is planned for August 2027, and the study findings are expected to be released in September 2027.</p><p><strong>Conclusions: </strong>This study will contribute to the development of VR-assisted infection prevention strategies. It addresses several research gaps by developing an evidence-based and feasible VR hand hygiene program for school settin","PeriodicalId":14755,"journal":{"name":"JMIR Research Protocols","volume":"15 ","pages":"e107264"},"PeriodicalIF":1.6,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13642894/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149110070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reproducibility of Published Randomized Controlled Trial Results in Cardiovascular Surgery: Protocol for a Meta-Epidemiological Umbrella Review.","authors":"Allen Li, Arshia P Javidan, Daniel J Niven, Henry T Stelfox, Dean A Fergusson, Mamas A Mamas, Prasad Jetty, Charles de Mestral, Risa Shorr, Subodh Verma, Munir Boodhwani, Derek J Roberts","doi":"10.2196/93997","DOIUrl":"10.2196/93997","url":null,"abstract":"<p><strong>Background: </strong>Reproducible study findings are those that are shown to be identical or nearly identical when an original study is repeated using similar methods. Findings from many randomized controlled trials (RCTs) in cardiovascular surgery have not been reproduced or are small, statistically fragile, and potentially influenced by funding source. They also demonstrate variable end point selection and protocol adherence, all of which may influence reproducibility of their reported results.</p><p><strong>Objective: </strong>This study aims to assess the reproducibility of RCTs conducted in the most commonly studied disease states in cardiovascular surgery that compared at least one open surgical procedure to an alternative open, interventional catheter-based, or sham procedure or medical therapy.</p><p><strong>Methods: </strong>We will conduct a meta-epidemiological study of the reproducibility of RCTs using umbrella review methodology. We designed the study protocol using the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) statement and published recommendations on conducting umbrella reviews. We will search MEDLINE, Embase, and the CENTRAL from their inception for systematic reviews published in the English language that included data from phase 3 RCTs or those with a clinically important primary outcome and compared an open cardiovascular surgery (performed in the most commonly studied disease states across these specialties) to either an alternative open, catheter-based, or sham procedure or medical therapy. Two investigators will independently review the individual RCTs from these systematic reviews and extract data and assess risk of bias (using the Cochrane Risk of Bias-2 tool), the fragility or reverse fragility indices (which provide a measurement of the statistical robustness of the trials), and the authors' interpretation of the results (also referred to as spin). RCTs will be classified as the original study if it was the first chronological study (based on participant enrollment date) to evaluate the compared interventions and as reproduction attempts if they reevaluate the compared interventions in a different set of participants. The interpretation of a study's results will be based on the findings of its primary end point and be used to assess reproducibility. We will also create multivariable regression models to determine whether the adjusted odds of reproducibility are independently predicted by 12 different variables.</p><p><strong>Results: </strong>We registered the study protocol but have not yet conducted the search. We aim to complete the study by the end of 2026 and submit for peer review by the summer of 2027.</p><p><strong>Conclusions: </strong>This study protocol may be used as a framework for future reproducibility research. The results will help guide which cardiovascular surgery practices warrant careful interpretation and which are in need of reproduction stud","PeriodicalId":14755,"journal":{"name":"JMIR Research Protocols","volume":"15 ","pages":"e93997"},"PeriodicalIF":1.6,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13641308/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149109533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Immersive 3D vs Physical Simulation in Training Novices for Laser-Based Endourological Procedures: Protocol for a Randomized Controlled Trial.","authors":"Joséphine-Charlotte Coleman, Matthias J Witti, Natalia Wirtz, Maximilian Aumiller, Adrian Rühm, Ronald Sroka, Tamira Büttner, Benedikt Duckworth-Mothes, Matthias Stadler","doi":"10.2196/94628","DOIUrl":"10.2196/94628","url":null,"abstract":"<p><strong>Background: </strong>Simulation-based learning constitutes a valuable component of medical training, with immersive 3D simulations and physical simulations being commonly used. Immersive 3D simulation training has been proven to enhance procedural skills and their transfer, whereas physical simulators allow for haptic feedback. However, direct comparative evidence between these 2 simulation modalities is scarce and often does not address cognitive, motivational, and perceived learning outcomes, which also have an effect on actual learning outcomes.</p><p><strong>Objective: </strong>The objective of this study is to evaluate whether immersive 3D simulation (a primarily screen-based, PC- or tablet-delivered simulator with optional virtual reality elements) can serve as a complementary or preparatory modality to physical simulator training when teaching novice trainees endourological laser-based procedures. Specifically, we investigate whether pretraining on an immersive 3D simulator facilitates the transfer of procedural knowledge and technical skills to the physical simulator, alongside its effects on cognitive load, motivation, and perceived learning.</p><p><strong>Methods: </strong>We will conduct a single-center, 2-group randomized controlled trial with 70 medical students who are currently in the clinical phase of their undergraduate medical studies. Each participant will complete one training session on either the immersive 3D simulation or the physical simulator, followed by one posttraining test on the physical simulator. Technical performance will be assessed by 2 experts using an objective structured assessment of technical skills-based composites, a critical error checklist as an indicator of safety, and time to task completion as an indicator of efficiency. Furthermore, we will measure motivation, cognitive load, and perceived learning. To analyze group differences in the primary and secondary outcomes, we will use independent-sample <i>t</i> tests (1-tailed), with nonparametric or Welch-corrected alternatives in cases in which assumptions are violated, and regression analyses to examine associations between the secondary outcomes and technical performance.</p><p><strong>Results: </strong>Recruitment will start in September 2026. We will begin with the training sessions and posttraining tests in November 2026. We expect to complete data collection by December 2026 and finish analyzing by February 2027. Consequently, we expect to publish the results in April 2027.</p><p><strong>Conclusions: </strong>By integrating technical performance with cognitive, motivational, and perceived learning outcomes, this study will clarify not only whether but also how immersive 3D simulation can support and prepare novice trainees for physical simulator training in endourological laser-based procedures. Furthermore, it aims to inform the evidence-based development of hybrid, simulation-based curricula in medical education.</p>","PeriodicalId":14755,"journal":{"name":"JMIR Research Protocols","volume":"15 ","pages":"e94628"},"PeriodicalIF":1.6,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13641755/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149110044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}