Medical Education最新文献

{"title":"Coping with generative AI's (GenAI) perpetuation of epistemic uncertainties.","authors":"Olivia Ng, Siew Ping Han, Minyang Chow","doi":"10.1111/medu.70068","DOIUrl":"https://doi.org/10.1111/medu.70068","url":null,"abstract":"","PeriodicalId":18370,"journal":{"name":"Medical Education","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145258569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Alternative analytic frameworks in transnational medical education.","authors":"Samantha Gallivan, Jack Haywood","doi":"10.1111/medu.70066","DOIUrl":"https://doi.org/10.1111/medu.70066","url":null,"abstract":"","PeriodicalId":18370,"journal":{"name":"Medical Education","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145251812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"When I say … workforce sustainability.","authors":"Megan E L Brown, Eleanor Hoverd, Anthony Montgomery, Bryan Burford, Gill Vance","doi":"10.1111/medu.70072","DOIUrl":"https://doi.org/10.1111/medu.70072","url":null,"abstract":"","PeriodicalId":18370,"journal":{"name":"Medical Education","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145251817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shifting the narrative: From Doctor as Hero to Doctor as Human.","authors":"Jessica Trier","doi":"10.1111/medu.70064","DOIUrl":"https://doi.org/10.1111/medu.70064","url":null,"abstract":"","PeriodicalId":18370,"journal":{"name":"Medical Education","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145251828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the impact of ethno-racial trauma on the well-being of US physicians: A scoping review.","authors":"Rakasa Pattanaik, Adam Cohen, Mary Ehlenbach, Kajal Khanna, Heidi Kloster, Laurel Scheinfeld, Uchechi Oddiri","doi":"10.1111/medu.70058","DOIUrl":"https://doi.org/10.1111/medu.70058","url":null,"abstract":"<p><strong>Background/purpose: </strong>Providers who identify as Underrepresented in Medicine (URiM) are disproportionately affected by the trauma resulting from systemic bigotry and injustice. This ethno-racial trauma (ERT) has been characterised by discrimination, obstacles to career advancement and leadership roles, and a lack of mentorship and representation. In this review, we sought to bring together the existing literature on ERT and its influence on the well-being of attending physicians in the USA, while also examining how different aspects of well-being are shaped using the PERMA (Positive emotions, Engagement, Relationships, Meaning and Accomplishment) conceptual framework for flourishing and well-being.</p><p><strong>Methods: </strong>This scoping review was conducted according to the JBI Manual for Evidence Synthesis: Scoping Reviews Chapter. A literature search of six bibliographic databases and one grey literature source was conducted in 2023 and updated in 2024, without time restriction applied. All English language studies conducted in the USA that assessed the impact of ERT on physicians and/or physician trainees were included.</p><p><strong>Results: </strong>Of the 4656 manuscripts identified for initial screening, 534 studies underwent full-text review, and 94 studies met inclusion criteria, with 29 studies focused on physicians alone and 18 focused on both physicians and physician trainees. Physicians most frequently described ERT in the form of devaluation of work, discrimination, explicit and implicit bias, inadequate support, professional isolation and microaggressions. Reported sources of ERT included patients, peers, other practitioners and institutional leadership. Also, ERT was consistently associated with heightened burnout, stress and isolation and was linked to diminished career advancement, reduced job satisfaction and impaired emotional well-being. Across studies in this review, all domains of the PERMA framework were adversely impacted.</p><p><strong>Conclusion: </strong>Current evidence demonstrates that ERT profoundly undermines physicians' well-being. Urgent interventional research is needed to identify, implement and evaluate strategies that mitigate ERT's effects and promote a more equitable professional environment.</p>","PeriodicalId":18370,"journal":{"name":"Medical Education","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145251834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Response to: GradeGPT-Generative AI for grading post-OSCE notes.","authors":"Florence Hurley, James Anthony Maye","doi":"10.1111/medu.70062","DOIUrl":"https://doi.org/10.1111/medu.70062","url":null,"abstract":"","PeriodicalId":18370,"journal":{"name":"Medical Education","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145206335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond 'use it or lose it': Retention of competence.","authors":"Sarah Blissett","doi":"10.1111/medu.70060","DOIUrl":"https://doi.org/10.1111/medu.70060","url":null,"abstract":"","PeriodicalId":18370,"journal":{"name":"Medical Education","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145199794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mental health longitudinal trajectories and predictors in medical students: Latent growth mixture model analysis.","authors":"Yinhai Chen, Xu Ran, Tong Zhou, Rong Huang, Lin Su, Xiong Ke","doi":"10.1111/medu.70047","DOIUrl":"https://doi.org/10.1111/medu.70047","url":null,"abstract":"<p><strong>Background: </strong>The high-pressure environment of medical education presents significant challenges to the long-term psychological well-being of medical students. Although anxiety and depression are well-documented among medical students, few studies have explored the developmental trajectories of these symptoms over time. This study aims to explore the two-year developmental trajectories of anxiety and depression symptoms in medical students and identify key predictors of these trajectories.</p><p><strong>Methods: </strong>This longitudinal study involved 810 medical students from a Chinese medical school, with data collected over four waves spanning two years. A total of 730 students completed the baseline survey and were included in the analysis, yielding a valid response rate of 90.1%. Participants completed the Patient Health Questionnaire-9 (PHQ-9) for depression and the Generalized Anxiety Disorder-7 (GAD-7) scale for anxiety. Latent Growth Mixture Modelling (LGMM) was used to identify the latent trajectories of depression and anxiety symptoms, with full information maximum likelihood estimation applied to handle missing follow-up data. Regression analysis was conducted to determine predictors of these trajectories.</p><p><strong>Results: </strong>The four waves of data for both depression and anxiety symptoms fit the model well. Depression followed two trajectories: a slowly decreasing group (92.0%) and a significantly increasing group (8.0%). Anxiety exhibited three trajectories: a low level-slow decreasing group (72.7%), a high level-significantly decreasing group (21.2%) and a low level-significantly increasing group (6.1%). Significant predictors of these trajectories included family structure, quality of relationships with parents and roommates, social support, past suicidal ideation and self-harming behaviour. Higher levels of social support were associated with decreasing symptom trajectories, whereas poor family relationships and past suicidal ideation predicted increasing symptoms.</p><p><strong>Conclusions: </strong>Depression and anxiety symptoms in medical students follow distinct developmental trajectories, providing a basis for targeted psychological interventions. Strengthening social support should be a priority for educational institutions and policymakers.</p>","PeriodicalId":18370,"journal":{"name":"Medical Education","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145199854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"When I say autonomy.","authors":"Adam Neufeld","doi":"10.1111/medu.70051","DOIUrl":"https://doi.org/10.1111/medu.70051","url":null,"abstract":"","PeriodicalId":18370,"journal":{"name":"Medical Education","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145149463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"'ChatGPT can make mistakes' warnings fail: A randomized controlled trial.","authors":"Yavuz Selim Kıyak, Özlem Coşkun, Işıl İrem Budakoğlu","doi":"10.1111/medu.70056","DOIUrl":"https://doi.org/10.1111/medu.70056","url":null,"abstract":"<p><strong>Background: </strong>Warnings are commonly used to signal the fallibility of AI systems like ChatGPT in clinical decision-making. Yet, little is known about whether such disclaimers influence medical students' diagnostic behaviour. Drawing on the Judge-Advisor System (JAS) theory, we investigated whether the warning alters advice-taking behaviour by modifying perceived advisor credibility.</p><p><strong>Method: </strong>In this randomized controlled trial, 186 fourth-year medical students evaluated three clinical vignettes with two diagnostic options. Each case was specifically designed to include the presentations of both diagnoses to make the case ambiguous. Students were randomly assigned to receive feedback either with (warning arm) or without (no-warning arm) a prominently displayed warning ('ChatGPT can make mistakes. Check important info'.). After submitting their initial response, students received ChatGPT-attributed disagreeing diagnostic feedback explaining why the alternate diagnosis was correct. Then they were given the opportunity to revise their original choice. Advice-taking was measured by whether students changed their diagnosis after viewing AI input. We analysed change rates, weight-of-advice (WoA) and used mixed-effects models to assess intervention effects.</p><p><strong>Results: </strong>The warning did not influence diagnostic changes (15.3% no-warning vs. 15.9% warning; OR = 1.09, 95% CI: 0.46-2.59, p = 0.84). The WoA was 0.15 (SD = 0.36), significantly lower than the 0.30 average in prior JAS meta-analysis (p < 0.001). Among students who retained their original diagnosis, the warning group showed a tendency toward providing explanations on why they disagree with the AI advisor (60% vs. 51%, p = 0.059).</p><p><strong>Conclusions: </strong>The students underweight AI's diagnostic advice. The disclaimer did not alter students' use of AI advice, suggesting that their perceived credibility of ChatGPT was already near a behavioural floor. This finding supports the existence of a credibility threshold, beyond which additional cautionary cues have limited effect. Our results refine advice-taking theory and signal that simple warnings may be insufficient to ensure calibrated trust in AI-supported learning.</p>","PeriodicalId":18370,"journal":{"name":"Medical Education","volume":" ","pages":""},"PeriodicalIF":5.2,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145149801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}