JMIR Medical Education最新文献

{"title":"Experiential Course Learning, Wellness, and Higher Education: Qualitative Descriptive Study.","authors":"Adrianna Lorraine Watson, Neil E Peterson, Brandon Thatcher, Michael Thomas, Stacie Hunsaker, Cole Hooley, David Erekson, Adam Simpson, Gregory Snow, Rachel Detrick","doi":"10.2196/88642","DOIUrl":"10.2196/88642","url":null,"abstract":"<p><strong>Background: </strong>Undergraduate students, including those preparing for health professions, report high rates of psychological distress and underuse of traditional counseling services. Credit-bearing wellness courses that combine psychoeducation with experiential learning may offer a scalable, curriculum-based approach to supporting student well-being.</p><p><strong>Objective: </strong>This qualitative study explored how undergraduate students described personal growth, coping, and lifestyle changes following participation in experiential wellness courses.</p><p><strong>Methods: </strong>An anonymous postcourse online survey captured open-ended responses from students enrolled across 6 wellness course sections. The courses emphasized stress physiology, evidence-based coping strategies, and weekly experiential assignments. Narrative responses from 110 participants were analyzed inductively using the reflexive thematic analysis developed by Braun and Clarke within a constructivist-interpretivist paradigm.</p><p><strong>Results: </strong>A total of six themes were identified: (1) healthy habits and practical lifestyle change; (2) stress management skills and mental health techniques; (3) self-reflection, awareness, and personal growth; (4) relevance and immediate applicability; (5) peer connection and discussion-based learning; and (6) course structure and opportunities for improvement. Students described adopting new coping strategies, developing greater self-awareness, and perceiving course content as relevant and applicable to their daily lives.</p><p><strong>Conclusions: </strong>Students described experiential wellness courses as supportive of coping, self-awareness, and behavior change. These findings provide insight into how students engage with and interpret course-based wellness education. Curriculum-integrated approaches may represent a complementary strategy to support student well-being. Future research should examine these approaches across diverse populations and over time.</p>","PeriodicalId":36236,"journal":{"name":"JMIR Medical Education","volume":"12 ","pages":"e88642"},"PeriodicalIF":3.2,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13148762/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147843753","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":"Design and Evaluation of a Faculty Development Workshop Series on Integrating Generative Artificial Intelligence in Medical Education: Mixed Methods Pilot Study.","authors":"Rajalakshmi Anand, Nicole Bowers, Mange Festo Manyama","doi":"10.2196/89815","DOIUrl":"https://doi.org/10.2196/89815","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Generative artificial intelligence (GenAI) tools are being increasingly applied to teaching and learning in medical education creating both instructional opportunities and pedagogical challenges. While GenAI offers potential to enhance teaching, assessment, and curriculum design, many medical faculty lack structured guidance on how to integrate these tools ethically and pedagogically within discipline-specific, high-stakes educational contexts.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to design, implement, and evaluate a faculty development workshop series for ethical and pedagogical integration of GenAI in medical education teaching.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A mixed methods pilot study was conducted to design, implement, and evaluate a faculty development workshop series \"Professional Development in Generative Artificial Intelligence for Pedagogy\" at Weill Cornell Medicine-Qatar, a US medical school in Qatar. The program consisted of five 1-hour synchronous online workshops grounded in Experiential Learning Theory and the Technological Pedagogical Content Knowledge framework. Ten medical faculty from multiple disciplines participated. Quantitative data were collected through an online preintervention survey, an online postintervention survey with open-ended questions, and an online 2-week follow-up survey. Surveys consisted of 5-point Likert scale items capturing perceptions of workshop quality, confidence, and intended application. Qualitative data included full workshop transcripts, facilitator theoretical notes, and facilitator memos. Descriptive statistics summarized quantitative findings, while qualitative data were analyzed using a combination of deductive and inductive coding, alongside narrative analysis. Findings were integrated to generate convergent interpretations.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Qualitative analysis of workshop transcripts suggested evolving engagement with GenAI, with participants describing movement from exploratory use toward more intentional pedagogical application. Postintervention survey results indicated high satisfaction with program content, organization, relevance, and overall quality. Two-week follow-up survey responses (n=5) suggested increased self-reported confidence in applying GenAI tools, and perceived shifts in how participants conceptualized teaching with GenAI. Faculty described intended strategies for integrating GenAI into lesson planning, assessment design, visualization of learning materials, and case-based instruction, while emphasizing the importance of human oversight, critical appraisal, and ethical judgment. Findings highlighted the perceived value of hands-on experimentation, reflective discussion, and adaptive facilitation in supporting early faculty engagement.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This pilot study provides early evidence that an experiential, theory-informed, and adaptively facilitated faculty development workshop series","PeriodicalId":36236,"journal":{"name":"JMIR Medical Education","volume":"12 ","pages":"e89815"},"PeriodicalIF":3.2,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13148327/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147843794","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":"The Effectiveness of Artificial Intelligence in Undergraduate Health Professions Education: Systematic Review and Meta-Analysis of Randomized Controlled Trials.","authors":"Nai Ming Lai, Yin Sear Lim, Min Thein Win, Prabal Bhargava, Paraidathathu Thomas, Qi Chwen Ong","doi":"10.2196/88933","DOIUrl":"10.2196/88933","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Health professions education faces increasing challenges from rising health care complexity, pedagogical shifts, and constrained curricular space, and rapidly expanding knowledge and technological advances. While artificial intelligence (AI) shows promise for transforming health professions education, evidence of its effectiveness remains unclear.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study synthesized evidence from randomized controlled trials (RCTs) on the effectiveness of AI in undergraduate health professions education.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We included RCTs, randomized crossover trials, and cluster RCTs comparing AI against standard educational interventions at the undergraduate level. We excluded quasi-experimental studies and those without clear AI components. We searched PubMed, Cochrane, Embase, Educational Resources Information Center, and Web of Science up to January 26, 2026. Outcomes were categorized according by Kirkpatrick levels; risk of bias was assessed using the Risk Of Bias Instrument for Use in Systematic Reviews for Randomised Controlled Trials tool; random-effects meta-analysis was conducted in RevMan (Cochrane); and certainty of evidence was rated using the Grading of Recommendations, Assessment, Development, and Evaluation approach. AI interventions were subcategorized by technology type and educational functions, yielding 13 subcategories.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Of 39,783 records identified, 66 RCTs (N=4911 participants; 2020-2026) were included. Subcategorized analyses across 7 outcome domains yielded 48 comparisons. Most studies had high risk of bias, mainly due to poor allocation concealment and blinding, and certainty of evidence ranged from low to very low. Large language model (LLM)-based personalized learning aids comprised the largest evidence base and showed positive effects for satisfaction (standardized mean difference [SMD] 0.93, 95% CI 0.40-1.46; 7 studies; 430 participants; I²=74%), confidence (SMD 0.91, 95% CI 0.54-1.29; 7 studies; 609 participants; I²=64%), and theoretical knowledge (SMD 0.53, 95% CI 0.13-0.94; 12 studies; 955 participants; I²=86%), all with very low certainty. Other AI subtypes, including LLM content generators, natural language processing (NLP) chatbots, and non-LLM adaptive learning platforms, showed generally favorable point estimates but substantial heterogeneity and wide CIs, often included no effect. Prediction intervals frequently crossed the null, indicating uncertainty across educational setting. No studies assessed Kirkpatrick levels 3 or 4.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This review synthesized RCT evidence on AI in undergraduate health professions education by technology type and function, incorporating evidence certainty. Despite the large number of included studies, evidence remains insufficient to inform educational practice. Some AI interventions may improve some learning outcomes, but effects are inconsistent and n","PeriodicalId":36236,"journal":{"name":"JMIR Medical Education","volume":"12 ","pages":"e88933"},"PeriodicalIF":3.2,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13151782/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147843818","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":"\"Optimizing Learning in Integrated Curriculum\"-Comparative Effectiveness of Online and Face-to-Face Formative Assessments: Mixed Methods Study.","authors":"Amira Salem Ismail, Sarah Mohamed Hussein, Mohamed El-Shafey, Ahmed Farid Al-Neklawy, Ahd A Mansour, Shatha Ghazi Felemban, Shimaa Elaraby","doi":"10.2196/84935","DOIUrl":"10.2196/84935","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Assessment is a critical component of teaching and learning and serves as the foundation for how learners demonstrate success in achieving learning objectives. Formative assessments (FAs) and timely feedback play a crucial role in integrated curricula, whereas basic and clinical sciences are taught in a coordinated manner. Feedback-based FA supports student learning, and teachers can determine learning gaps to monitor progress in learning. Based on existing evidence, limited literature compared the effect of online versus onsite FA on summative performance in a fully integrated curriculum.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to examine the effectiveness of online versus on-site FAs and feedback on summative assessment in the integrated medical curriculum.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This study used an exploratory mixed methods approach to delving into students' experiences with face-to-face versus online FA and feedback, and its effect on their summative performance in the integrated Bachelor of Medicine, Bachelor of Surgery program. This study was conducted at Fakeeh College for Medical Sciences in Jeddah, Saudi Arabia. A total of 143 consenting students were recruited into the study. The students in the study were distributed voluntarily into 2 groups regardless of age, sex, or academic performance. Group 1 (n=92) was assigned to receive online FAs and immediate online feedback throughout the module using the Speedwell system. However, Group 2 (n=51) was assigned to receive onsite FAs and face-to-face feedback throughout the module in the examination hall in the college. The quantitative part of the study involved analyzing student scores of summative assessments in 2 groups exposed to online and onsite FA and feedback. The qualitative part aimed to explore students' perceptions of FA and feedback.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The passing rate in summative examinations (quiz, midmodule, and final) was higher in the onsite group (61.2%, 51%, and 62.7%, respectively) compared with the online group (53.3%, 48.3%, and 45.7%, respectively). However, the difference was statistically significant only in the quiz examination. Four key themes were identified from the qualitative analyses regarding participants' different experiences of FA and feedback: the accessibility of the examination format facilitates flexibility in learning; FA is a means of recognizing learning opportunities; FAs help shift student attitudes toward learning; and the last theme is opportunities for discussion and personalized feedback.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;This research sheds light on the intricate interplay between assessment modalities and student learning outcomes by demonstrating that onsite FA followed by onsite feedback is more effective than online FA and feedback in fostering student engagement and promoting deep understanding and improving students' performance in summative examinations. Thereafter, thi","PeriodicalId":36236,"journal":{"name":"JMIR Medical Education","volume":"12 ","pages":"e84935"},"PeriodicalIF":3.2,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13143194/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147843837","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":"Use of 3D-Printed Models and Augmented Reality in Medical Student Education of Congenital Heart Disease: Randomized Controlled Trial.","authors":"Tyler Langenfeld, Gabriel N Bahrami, Yea-Lyn Pak, Susanne Wish-Baratz, Yuxi Zhu, Arpit Agarwal","doi":"10.2196/85967","DOIUrl":"https://doi.org/10.2196/85967","url":null,"abstract":"<p><strong>Background: </strong>Three-dimensional modalities are increasingly being used as adjuncts for medical trainees learning about complex anatomical concepts, such as congenital heart disease.</p><p><strong>Objective: </strong>This study aimed to evaluate the use of 2 such modalities, 3D-printed models, and augmented reality (AR), in improving medical students' understanding and knowledge retention of congenital heart disease when compared to traditional teaching methods.</p><p><strong>Methods: </strong>A prospective cohort pilot study was performed with 26 first-year medical students. Students were randomly assigned to receive a 30-minute teaching session using traditional slide-based lecture, 3D-printed model, or AR. Participants completed a 16-question pretest consisting of 4 basic general cardiology questions and 6 questions each regarding the anatomy and physiology of tetralogy of Fallot and hypoplastic left heart syndrome. Participants completed a posttest immediately following the teaching session, as well as a delayed posttest 3 weeks later.</p><p><strong>Results: </strong>When comparing overall and subsection posttest scores, the AR group obtained perfect immediate posttest scores at a significantly increased rate compared to the lecture and 3D model groups (6/9, 67% vs 1/8, 13% and 1/9, 11%, respectively; large effect size Cramér V=0.57; P=.02). Participants in the lecture group reported difficulty understanding cardiac anatomy and physiology using only 2D diagrams, whereas those in the 3D-printed model and AR groups almost unanimously reported improved visualization of complex cardiac defects, which enhanced their understanding.</p><p><strong>Conclusions: </strong>Due to the visuospatial benefits of 3D-printed models and AR, there is potential for use in medical education to improve students' knowledge of complex anatomical and physiological concepts. Students who received teaching using 3D-printed models or AR overwhelmingly reported improved 3D visualization of congenital cardiac defects compared to those who were taught via lecture. Additionally, AR and 3D-printed models offer practical opportunities for implementation into medical education curricula as both adjunct and stand-alone teaching modalities.</p>","PeriodicalId":36236,"journal":{"name":"JMIR Medical Education","volume":"12 ","pages":"e85967"},"PeriodicalIF":3.2,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13143156/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147843792","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":"Medical Students' Acceptance of Digital Entrustable Professional Activities: Results of a Cohort Study.","authors":"Maximilian Domann, Constanze Richters, Matthias J Witti, Matthias Stadler","doi":"10.2196/87605","DOIUrl":"https://doi.org/10.2196/87605","url":null,"abstract":"<p><strong>Background: </strong>Digital entrustable professional activities (EPAs) in simulated environments may accelerate competency acquisition, but adoption depends on learner acceptance. The Technology Acceptance Model (TAM) posits that perceived usefulness (PU) and perceived ease of use (PEU) shape attitudes (AT) and, in turn, behavioral intention (BI).</p><p><strong>Objective: </strong>This study aimed to examine medical students' acceptance of digital EPAs and to test the hypothesized TAM relationships among PU, PEU, AT, and BI.</p><p><strong>Methods: </strong>Clinical-phase medical students at Ludwig Maximilian University of Munich completed a TAM-based survey (7-point Likert scales) after reading a canonical analog EPA and its digital counterpart. Confirmatory analyses comprised bivariate correlations and hierarchical regressions testing TAM paths. Exploratory analyses comprised paired-sample two-tailed t tests comparing analog versus digital ratings and path modeling to evaluate global TAM fit.</p><p><strong>Results: </strong>Between 70 and 72 medical students provided complete, usable responses, depending on the construct. Mean ratings were favorable (≈5/7). Internal consistency was acceptable (ω=.67-.80). Within the digital EPAs, PU strongly predicted AT (β=.59; P<.001), and AT predicted BI (β=.58; P<.001). For the analog EPAs, PU (β=.54; P<.001) and PEU (β=.28; P=.005) predicted AT; both AT (β=.42; P<.001) and PU (β=.36; P=.002) predicted BI. Attitudes were modestly higher for analog versus digital (M=5.18 vs 4.87; t71=-2.50, d=-0.30; P=.02), but PU, PEU, and BI did not differ significantly. The path models indicated excellent fit for both formats (comparative fit index=1; root mean square error of approximation=0; standardized root mean square residual ≤.01).</p><p><strong>Conclusions: </strong>Students reported high acceptance of digital EPAs. Acceptance was driven primarily by PU (via AT), whereas PEU contributed to AT only for analog EPAs. Implementation should emphasize demonstrable educational value and cultivate positive attitudes; subsequent work should link acceptance to actual use and learning outcomes.</p>","PeriodicalId":36236,"journal":{"name":"JMIR Medical Education","volume":"12 ","pages":"e87605"},"PeriodicalIF":3.2,"publicationDate":"2026-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13138705/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147843844","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":"Developing and Integrating Virtual Reality Courses in Medical Education: Tutorial and Implementation Guideline Informed by Best Practices From the National Project \"medical tr.AI.ning\".","authors":"Marvin Mergen, Anna Junga, Henriette Schulze, Philipp Bozdere, Pascal Kockwelp, Leon Pielage, Corbin Sassen, Tina Glückselig, Michael Schmitz, Kathrin Ungru, Norbert Graf, Benjamin Risse, Marcel Meyerheim","doi":"10.2196/80976","DOIUrl":"https://doi.org/10.2196/80976","url":null,"abstract":"&lt;p&gt;&lt;p&gt;The increasing adoption of virtual reality (VR) in medical education offers substantial opportunities for immersive, practice-oriented training that complements traditional teaching methods. In particular, VR enables repeated, risk-free exposure to complex clinical scenarios and supports the development of clinical reasoning, communication skills, and procedural competence. However, implementing VR-based courses remains challenging due to high development costs, technical complexity, and the need for close interdisciplinary collaboration. This tutorial presents key insights and best practices from the medical tr.AI.ning project, a 3-year interdisciplinary initiative funded by the German Federal Ministry of Education and Research. The project's objective was to develop an artificial intelligence (AI)-supported, VR-based training platform that allows medical students to practice clinical decision-making in immersive, interactive scenarios. The paper is structured as a tutorial and offers recommendations for planning, developing, and integrating VR courses into medical curricula. Each recommendation is illustrated with concrete examples from our project, serving as a practical blueprint to guide educators and developers in applying these guidelines in their own contexts. Successful implementation of a VR project in medical education requires strategic planning and collaboration, starting with a thorough identification of curricular gaps that VR can address and a clear justification of its added educational value. An interdisciplinary consortium that combines expertise from medical didactics experts, computer science, and design is essential to ensure the development of high-quality, pedagogically sound simulations and intuitive user interfaces. Key factors for success include defining specific learning objectives aligned with competency-based frameworks; iterative development with continuous feedback from medical experts, educators, and students; and structured pilot testing with systematic collection of quantitative and qualitative data to assess usability, immersion, and learning outcomes. Early engagement and walkthroughs with end users help identify practical challenges and inform iterative improvements. A dedicated authoring tool within the project allows medical teachers to create and adapt VR scenarios without prior technical experience, supporting the scalability and sustainability of the approach. Effective project management frameworks facilitate collaboration, clear task allocation, and adaptive progress throughout development. Additionally, considerations for hardware selection, technical infrastructure, and sustainable dissemination strategies, including open-access publications, project websites, and professional networking, are crucial to ensure long-term viability and broad adoption across institutions. By combining a tutorial format with practical, step-by-step recommendations, this article provides a comprehensive guide for e","PeriodicalId":36236,"journal":{"name":"JMIR Medical Education","volume":"12 ","pages":"e80976"},"PeriodicalIF":3.2,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147821831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Value, Structure, and Curriculum in US Graduate Health Informatics Programs: Cross-Sectional Study.","authors":"Suhila Sawesi, Diane M Dolezel, Pranitha Presingu, Michael Irungu","doi":"10.2196/87479","DOIUrl":"https://doi.org/10.2196/87479","url":null,"abstract":"<p><strong>Background: </strong>Graduate health informatics programs in the United States differ widely in cost, curriculum, and program design. However, it is unclear how these differences influence affordability, accreditation signaling, and preparation for a data-driven workforce.</p><p><strong>Objective: </strong>This study aimed to evaluate the value (tuition and affordability), structure (delivery format, credit load, culminating experience, and accreditation), and curriculum (technology content emphasis) of US graduate health informatics programs. It examined how accreditation and modality relate to program design, and whether tuition-normalized curriculum breadth differed by accreditation status.</p><p><strong>Methods: </strong>A cross-sectional study of 107 US graduate health informatics programs was conducted using publicly available data collected between January and May 2025. Tuition was standardized to cost per credit. Curricular content was coded for technology density and mapped to the Commission on Accreditation for Health Informatics and Information Management Education domains. Comparative statistics, regression models, and exploratory cluster analyses were used to assess relationships between tuition, credit requirements, accreditation, delivery format, and curriculum characteristics.</p><p><strong>Results: </strong>Programs varied by delivery format, with 37 of 107 (34.6%) online, 32 of 107 (29.9%) hybrid, 23 of 107 (21.5%) in person, and 15 of 107 (14.0%) flexible. Credit requirements most commonly fell between 31 and 39 credits. Culminating experiences included capstone (54/107, 50.5%), internships (21/107, 19.6%), and thesis (7/107, 6.5%). Required credit hours showed modest variation by delivery format but not by accreditation status. Accreditation was not associated with differences in the tuition-normalized curriculum breadth structural proxy in this program-level analysis. Programs requiring internships had significantly higher mean credit loads than programs without internships (39.0 vs 31.3 credits; P=.005). Cluster analysis revealed 4 descriptive program configurations differentiated by cost, modality, credit requirements, and culminating experiences.</p><p><strong>Conclusions: </strong>In this program-level descriptive analysis, accreditation status was not associated with differences in tuition-normalized curriculum breadth structural proxy. Instead, delivery format and internship requirements were descriptively associated with variation in credit load and cost. Improving transparency in tuition models and aligning program structure with curricular scope may support efforts to enhance equity and value in graduate health informatics education.</p>","PeriodicalId":36236,"journal":{"name":"JMIR Medical Education","volume":"12 ","pages":"e87479"},"PeriodicalIF":3.2,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13134824/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147821825","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":"\"<i>AAC</i>HEN\" e-Learning Tool in Augmentative and Alternative Communication for Medical Students in Germany: Cross-Sectional Evaluation Study.","authors":"Jessica Büchs, Christiane Neuschaefer-Rube","doi":"10.2196/88173","DOIUrl":"10.2196/88173","url":null,"abstract":"<p><strong>Unlabelled: </strong>We developed an e-learning tool in augmentative and alternative communication (AAC) for medical students in Germany and tested it at Rhenish-Westphalian Technical University, Aachen. Our cross-sectional evaluation study is an innovative approach since the topic is yet to be implemented in medical education. Other AAC tools do not target medical students. Our study underlines the importance of AAC for medical doctors. Universities should include AAC in their lectures to prepare medical students for their clinical practice. The \"AACHEN\" tool is a first step.</p>","PeriodicalId":36236,"journal":{"name":"JMIR Medical Education","volume":"12 ","pages":"e88173"},"PeriodicalIF":3.2,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13127592/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147783856","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":"Ambient AI Scribes to Create Educational Feedback Notes for Medical Students: A Randomized Trial.","authors":"Jaideep S Talwalkar, David Chartash, Lisa Zhang, Michael Makutonin, Conrad W Safranek, Anne Elizabeth Sidamon-Eristoff, Lee H Schwamm, Donald S Wright","doi":"10.2196/89996","DOIUrl":"https://doi.org/10.2196/89996","url":null,"abstract":"<p><strong>Background: </strong>High-quality observation and feedback contribute to the development of clinical competence and professional growth in medical education. Faculty often struggle to translate verbal observations into written feedback because of documentation burden and competing demands. Ambient artificial intelligence (AI) scribes, already adopted in clinical practice, may address this challenge by capturing verbal exchanges and generating structured notes.</p><p><strong>Objective: </strong>The purpose of this study was to examine the use of ambient AI scribes to generate educational feedback notes during a formative medical interviewing workshop for first-year medical students in spring 2025.</p><p><strong>Methods: </strong>Thirteen instructors were randomized to control (human-only) or intervention (AI scribe-assisted) workflows to complete narrative feedback forms. The intervention group used an AI scribe to generate transcripts of student-instructor encounters, which were then summarized into feedback notes using a large language model, and edited by instructors before submission. All narratives were scored using the Evaluation of Feedback Captured Tool (EFeCT). Factual accuracy of a subsample of unedited AI feedback summaries was reviewed against source transcripts. Task load and usability were measured using NASA Task Load Index and System Usability Scale respectively.</p><p><strong>Results: </strong>Instructors submitted feedback on 94 of 102 students (92.2%). Median EFeCT scores on the zero-to-five scale were higher for human-edited AI narratives (3.00) and unedited AI summaries (3.00) compared to human-only narratives (2.00; P<.001). Human narratives were shorter than AI-assisted outputs (P<.001). Review of 117 AI-generated feedback elements showed a 6.8% mischaracterization and 1.7% hallucination rate, with most errors corrected during editing. Task load was high and usability marginal in both control and intervention groups, with no significant differences.</p><p><strong>Conclusions: </strong>An ambient AI scribe-assisted workflow improved the quality of written narrative feedback with no observed increase in instructor effort compared to human-only documentation. Although occasional inaccuracies required review, this innovation has the potential to transform feedback documentation.</p><p><strong>Clinicaltrial: </strong>This study received exemption from review by the Yale University Institutional Review Board due to its educational nature on January 23, 2025 (IRB Protocol ID 2000039478).</p>","PeriodicalId":36236,"journal":{"name":"JMIR Medical Education","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147783859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}