Medical Teacher最新文献

Error-Based Learning (EBL) represents a paradigm shift in Health Professions Education (HPE), moving from punitive approaches to embracing errors as learning opportunities. This AMEE guide targets educators, curriculum designers, clinicians, and learners, bridging theory with practical strategies to optimize EBL in training and assessment. The guide contrasts Error Management Theory (EMT), which emphasizes learning from errors, with Error Avoidance Theory (EAT). Core EBL components including psychological safety, structured reflection, deliberate error exposure, and feedback are detailed alongside actionable implementation strategies, including simulation-based scenarios with debriefing, contrasting case-based reasoning, structured error-logging through reflective portfolios and assessment for learning. Looking ahead, we discuss emerging innovations in EBL, including the potential reconceptualization of educational tools such as the 'escape room' as an 'error room' and AI. This guide challenges traditional paradigms and calls for a deliberate focus on error-embracing in HPE.

Introduction: Advising is essential for student success in graduate health professions education (HPE). Advising does not happen in a vacuum, yet most research focuses narrowly on advisor-advisee relationships. To address this gap, this study examines how institutional structures, policies, and programmatic dynamics influence the effectiveness of advising in graduate HPE.

Methods: We conducted semi-structured interviews with 15 HPE program leaders across six WHO regions. Using framework analysis guided by Activity Theory and the concept of knotworking, we analyzed how institutional systems shape advising practices.

Results: Five institutional factors were identified: (1) strategic advisor recruitment, (2) supportive advising cultures, (3) bureaucratic and resource constraints, (4) advisor training and evaluation, and (5) recognition and support for advisors. Leaders described advising as an adaptive, cross-system process shaped by institutional complexity and evolving student needs.

Discussion: Advising in graduate HPE operates beyond dyadic relationships. It is embedded within institutional activity systems and requires ongoing negotiation across structural boundaries. Programs must adopt systemic strategies, such as faculty development, workload alignment, and policy reform, to support effective advising networks.

Introduction: The integration of artificial intelligence (AI) tools into medical education presents new opportunities for enhancing students' research skills and scientific writing. However, concerns remain about the potential for cognitive disengagement and the ethical use of AI when lacking appropriate educational supervision. This study aimed to evaluate a novel educational strategy combining structured AI assistance with mentor guidance to support narrative review writing among third-year medical students.

Methods: A structured framework was implemented during the endocrine module, involving AI-assisted objective formulation, mentor-guided objective refinement, literature search and summarization, review drafting followed by AI-assisted rephrasing. Students worked in groups, each supervised by a trained mentor. A validated questionnaire assessed student perceptions across four domains: framework and guidelines, AI-generated objectives, skills developed and mentor role, and overall satisfaction. Descriptive statistics were performed and chi-square tests evaluated associations between perceptions and AI tool usage (ChatGPT vs. DeepSeek).

Results: Eighty-seven students completed the survey. Perceived improvement in research readiness was observed; confidence in literature searching rose from 29.8% to 69%, while 75.8% reported increased familiarity with PubMed/Google Scholar. Most students (80.5%) expressed satisfaction with the AI mentor hybrid approach, and 82.8% agreed it prepared them for future research. There were no significant differences in perceived outcomes between AI tools used. Mentor involvement was deemed essential by 69% of students, and a minority believed AI alone could replicate the same outcomes. Common challenges included limited access to articles and peer collaboration difficulties, while key learning outcomes included improved summarization and ethical AI use.

Discussion: This study supports the integration of AI tools within a structured, mentor-guided educational framework to enhance critical evaluation and scientific writing in medical education. Human oversight and mentorship drive skill development and minimize the risk of unmoderated AI use in academic settings.

Health Professions Education (HPE) cannot rely on assumptions of stability. Fragile contexts - wars, disasters, political upheaval, and systemic weakness - disrupt teaching and learning, assessment, accreditation, and the well-being of learners and faculty. This AMEE Guide provides a framework for building resilient HPE that survive crises and use them as opportunities for reform. The Guide identifies three types of fragility and explores their impact on institutions, human capital, clinical training, and social accountability. To boost resilience, the guide recommended adaptive strategies that include creating crisis management committees, implementing modular and competency-based curricula, allowing credit transfers for displaced learners, and incorporating tailored training programs. For curriculum delivery innovations range from hybrid and low-tech methods to peer-assisted approaches, diaspora involvement, and community-based services. A practical model for fair and feasible assessment in disrupted environments is suggested, with a focus on outcomes, flexibility, and cross-border recognition for rethinking accreditation and quality assurance. Systems thinking underpins the Guide, highlighting how destructive cycles such as brain drain can erode capacity, while virtuous cycles - driven by technology adoption, partnerships, and community integration - can foster recovery and growth. The guide also calls on educators, institutional leaders, and policymakers to move from reactive responses to proactive preparedness.

Using Artificial Intelligence (AI) to review academic papers is happening and cannot be ignored by journals. There is a need to find a balance between outright banning and uncontrolled usage. Medical Teacher recognises this need, and this commentary views the problem within the general context of authorship, discusses some of the problems surrounding AI-reviewing, and offers a middle ground of practice and disclosure that will assist authors, reviewers, and the journal in ensuring that the review process is not compromised.

Purpose: Although racism has received growing attention in medical education in recent years, there remains a lack of clarity about the central recommendations for policy and practice. This study synthesises anti-racist recommendations from the literature to address this gap.

Methods: We searched twenty-four medical education journals to identify articles published in the year 2023 focusing primarily on race and racism. Policy and practice recommendations from these articles were analysed using content analysis.

Results: Across the 107 included articles, anti-racist recommendations were organised into seven themes: (1) Increasing cross-cultural and historical research; (2) Changing culture and mission of institutions; (3) Enhancing patient and community involvement; (4) Developing greater community solidarity; (5) Redesigning student and faculty recruitment; (6) Expanding antiracist content in curricula; (7) Reforming assessment and course evaluation.

Conclusions: Recommendations to tackle racism in medical education focus both on symbolic changes that send signals to stakeholders such as rewriting mission statements, and on structural changes that rewire existing systems to make them fairer, such as redefining recruitment criteria. Medical education leaders can consider whether their interventions align with these recommendation categories, and medical education researchers can critically interrogate whether they should be refined as geopolitical and sociocultural contexts rapidly shift.

Introduction: Future physicians must develop the necessary knowledge and skills to effectively manage challenging patient communication. To design linked meaningful learning activities, perspectives from students and teachers need to be taken into account as well as students' previous knowledge. Aiming to better understand how this knowledge can be acquired through patient simulation, we examined students' perceptions, mirrored in teachers' reflections, and how these relate to the medical curriculum.

Methods: Data were collected from students and teachers during the ninth semester of a medical program in Sweden. A narrative survey and individual interviews were conducted. Using thematic analysis, we analyzed nineteen student surveys, five student interviews, and four teacher interviews to explore perceptions of learning. The student themes were then used to identify corresponding subthemes in the teacher data through a mirroring process.

Results: Self-knowledge was identified as a crucial skill in order to effectively convey empathy in challenging patient communications. Patient simulation was described as a valuable learning activity which, however, lacked integration with adjacent learning activities in the medical program. Learning progression was hindered by a disconnect between communication-related learning activities and those focused on medical knowledge.

Conclusion: Both self-knowledge and medical knowledge are perceived as essential for learning how to manage challenging patient communication. Our findings suggest that the learning of patient communication and medical knowledge should be integrated in the curriculum and reinforced across various settings. Patient simulation is a valuable method for developing self-knowledge and communication skills.

The World Health Organization (WHO) defined 'social accountability for medical schools' in 1995; yet 30 years later, many remain concerned that medical schools are not living up to societal expectations. In this article, we first place the WHO's definition into historical context, then we contrast the WHO social 'contract', where schools are expected to demonstrate value for money, with the more altruistic 'code' that had been put forward previously by Abraham Flexner. We discuss contemporary barriers to advancing social accountability, including tacit assumptions about the semantics of the term accountability, the geographic communities schools should serve, how schools are financed, and expectations for school outcomes. We suggest that the future of social accountability for medical schools movesbeyond social codes and contracts to recognizing the varied ways that medical schools contribute to diverse individuals and groups within communities along a local to global spectrum. While it is unlikely that there will be universal consensus on what makes a medical school valuable to those whom it impacts, medical schools should make data available that allow others to render their own judgments and participate in conversations that help medical schools and medical education systems better align resources with needs.

Aim: Bedside rounds generate highly valuable spontaneous teaching, yet these moments are rarely preserved. Learners often struggle to document teaching points while participating in patient care, and teaching is easily forgotten once rounds move on. Existing tools-manual notes, post-rounds summaries, or static teaching cards do not capture the dynamic, real-time nature of bedside teaching.

Methods: We developed Rounds Copilot, an AI-supported system that automatically captures spoken bedside teaching and converts it into structured learning materials. The tool integrates automated speech transcription, extraction of discrete teaching points, classification of guideline-backed evidence versus clinical pearls, and generation of formative assessment questions.

Results: A simulated 15 min pericarditis teaching encounter was processed using the tool. Within three minutes, the system produced seven teaching kernels, evidence classification, and five multiple-choice questions. Informal feedback from four residents indicated the evidence-versus-pearl distinction clarified learning priorities and immediate assessment questions supported knowledge consolidation.

Discussion: The system costs less than USD $1 per typical session, requires minimal technical skills, and includes open-source components. Offline transcription supports use in low-bandwidth settings.

What are the next steps?: Planned work includes real-world testing, usability studies, and development of privacy-compliant clinical deployment pathways.

Purpose: The World Federation for Medical Education (WFME) established the Recognition Programme (RP) to improve the quality of medical education accreditation worldwide. This study aims to evaluate the impact of recognition from the perspective of recognised accreditation agencies.

Materials and methods: We emailed all WFME-recognised accrediting agencies with a survey containing five open-ended questions seeking their perspectives on recognition impact on agencies, medical education and health outcomes. Data was collected from July to August 2024. Open coding of results aggregated across questions followed by thematic analysis, generated themes organised under the three evaluated impact areas.

Results: 35 of 45 agencies responded. All experienced benefits of WFME recognition such as improved accreditation quality or enhanced national and international credibility. Challenges included tensions between the RP and the local context, and resource requirements. Early signs of improvement in the quality of medical education driven by recognition were observed.

Conclusion: This first study of the WFME RP indicates significant benefits of recognition to the agencies by improving accreditation quality and credibility as well as the establishment of a continuing quality improvement (CQI) culture within agencies and accredited medical schools.