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Purpose: This study evaluated the efficiency and effectiveness of using Generative Artificial Intelligence (GenAI) to draft Medical Student Performance Evaluation (MSPE) summary paragraphs for medical students.

Materials and methods: Evaluations on the pediatrics clerkship were used to develop MSPE summary paragraphs. Time to completion was noted for paragraphs drafted by GenAI, created using Microsoft 365 Copilot, and compared to human-generated. Undergraduate Medical Education (UME) leaders were recruited to evaluate 10 randomized pairs of paragraphs through a blinded survey.

Results: Copilot-drafted paragraphs required significantly less time to completion compared to human-generated paragraphs (median 6 vs. 12.5 min, p = 0.002). UME leaders showed no significant preference and were unable to consistently identify Copilot vs human authorship. When stratified by perception of authorship, human-generated paragraphs were significantly less likely to be preferred if they were perceived as being Copilot-drafted than if they were perceived as being human-generated (p = 0.017), suggesting an element of anti-AI bias. Competencies were highlighted to a similar degree, and Copilot-drafted paragraphs were perceived as having significantly less biased language by both UME leaders (p = 0.004) and an independent analysis using a validated gender bias calculator (p = 0.029).

Conclusions: Copilot-drafted MSPE summaries are efficient, comparable in quality, and may reduce the introduction of bias.

Generative Artificial Intelligence (GenAI) tools are increasingly integrated into research and academic writing, offering opportunities to streamline workflows and increase productivity. However, these tools also introduce risks when used uncritically, unethically, or without transparency. In particular, the undisclosed use of GenAI, now widely documented, may compromise research integrity. The aim of this AMEE Guide is to provide researchers with practical guidance on when and how to disclose the use of GenAI in scholarly writing. Specifically, we propose a clear framework to promote ethical GenAI use and reporting practices in health professions education research. We start with an exploration of key aspects of responsible use of GenAI in publishing (e.g. authorship, verification and responsibility, plagiarism and bias, data privacy and confidentiality, journal requirements). We then address the importance of transparency about GenAI use in research production, both within research teams (internal disclosure) and to journals and readers (external disclosure). With respect to the latter, we highlight the need to be aware of journal-specific guidance and offer guiding principles for effective disclosure. Central to these principles is the call for scholars to provide a candid description of how GenAI was used, allowing readers to understand how the model shaped the research and writing processes. We also briefly consider the use and disclosure of GenAI in peer review. Given that, at the time of writing this Guide (November 2025), many questions remain regarding AI use and disclosure for publishing, we conclude with reflections on future developments and directions for research.

Purpose: Sexual and gender minority (SGM) patients face wide-ranging health disparities. One potential source of these disparities is anti-SGM bias perpetuated in undergraduate medical education, including in United States Medical Licensing Exams (USMLEs) and preparatory materials for these exams.

Materials and methods: We screened 8,449 USMLE-style questions in the UWorld Step 2 Question Bank, the AMBOSS Step 2 Question Bank, and NBME Self-Assessment forms, and included those that identified a patient's sexual or gender identity in our analysis. We first determined the overall representation of SGM and non-SGM-identified patients, and then compared methods of identifying sexuality or gender identity, representations of sexual behavior, and rates of different medical conditions between SGM and non-SGM patients.

Results and conclusions: We identified 801 questions that referenced a patient's sexual or gender identity, including 49 (6%) featuring SGM patients and 752 (94%) featuring non-SGM patients. Questions featuring SGM patients overrepresented gay men and underrepresented bisexual women and transgender patients relative to US population trends. SGM patient questions also disproportionately focused on sexual health, and did so at the expense of representing other medical conditions. Given the ubiquity of USMLE practice materials, these patterns may contribute to implicit bias around SGM patients among the future US physician workforce.

Introduction: Speaking-up behavior is crucial for preventing patient harm, yet evidence suggests that increased clinical experience does not necessarily promote it. Gender, contextual factors, and prior patient safety training may also influence speaking-up tendencies, but research on their interaction remains limited. To address this gap, this study examines the impact of clinical experience, gender, patient safety training, and scenario severity on speaking-up behavior to inform targeted educational interventions.

Methods: This cross-sectional study analyzed 306 medical students from two cohorts (2020 and 2023) at a medical university in Northern Taiwan. A simulation-based assessment session evaluated students' speaking-up behavior in life-threatening and non-life-threatening medical error scenarios. Data on clinical experience, gender, and prior patient safety training were collected. Speaking-up behavior was assessed using the Speaking-Up Behavior Checklist, and binary logistic regression was conducted to examine associations.

Results: Increased clinical experience was significantly associated with lower speaking-up behavior (Exp(B) = 0.916, p = 0.005), particularly among male students, while female students' behavior remained unchanged. Additionally, students were less likely to speak up in life-threatening scenarios (Exp(B) = 0.886, p = 0.007), while scenario type had no significant effect on those with less clinical experience. Prior patient safety training was not significantly associated with speaking-up behavior.

Discussion: These findings suggest that clinical experience, gender, and scenario influence speaking-up behavior. While clinical skills improve with experience, heightened hierarchical awareness and professional relationships may increase hesitation. This implies the importance of structured policies, targeted training, and cultural transformation to foster a safe environment for speaking up. Future research should also examine psychological and organizational factors to better guide educational and systemic interventions.

Purpose: The level of medical students' empathy may be related to mental health and burnout. Whether one predicts the other remains to be tested. The present study sought to test the reciprocal influences between empathy and mental health or burnout in a population of medical students using a longitudinal design.

Method: From 2021 to 2024, a questionnaire was sent annually to all medical students at the University of Lausanne (Switzerland). The questionnaire included validated measures of empathy (cognitive, affective, and behavioral as well as an emotion recognition test), mental health (depression symptoms, anxiety, and stress), and burnout (emotional exhaustion, cynicism, and academic efficacy). Random-Intercept Cross-Lagged Panel Models were used to estimate how empathy predicts mental health or burnout the following time point and vice versa.

Results: In total, 1852 medical students filled in at least one yearly questionnaire. The cross-sectional correlations showed that cognitive and behavioral empathy were related to better mental health and less burnout, whereas affective empathy was related to more mental health issues and burnout. Empathy, mental health, and burnout levels were predicted by their respective previous level as well as gender identification and curriculum years of the medical students. However, neither empathy nor mental health or burnout predicted the other from one time point to the next.

Conclusions: The present study does not support a reciprocal relationship between empathy and mental health or burnout, but rather a parallel evolution across years. The results of this study emphasize the importance of recognizing each student's individuality. They further advocate for learning environments that support the development of communication competencies and nurture the well-being of medical students.[Box: see text].

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.

Introduction: Resilience is essential for medical educators to fulfil their responsibilities. While research often focuses on individual well-being programs, less is known about how resilience is shaped by systemic and institutional interventions, particularly across diverse cultural contexts. This study explores interventions perceived by Hong Kong (HK) medical educators as fostering their resilience.

Methods: Participants were purposively sampled across socio-demographic characteristics collected via an online survey. Twenty medical educators from two HK medical schools participated in video-recorded, semi-structured online interviews. Transcripts were anonymized and an abductive reflective thematic analysis was conducted. Researchers iteratively engaged with Bronfenbrenner's Process-Person-Context-Time (PPCT) model to deepen interpretation.

Results: Nine interrelated themes were identified across four PPCT domains. Resilience was shaped by personal reflection and self-care (Person); supportive relationships and communication (Process); institutional conditions (Context); and changes across life stages plus external events (Time). Process- and Context-level interventions were perceived as essential for fostering medical educators' resilience.

Discussion/conclusion: The findings underscore the importance of designing resilience interventions that address relational, institutional, systemic and cultural dimensions. Key areas include professional recognition, communication, resource allocation, and psychologically safe environments. Understanding culturally- and contextually-specific experiences of resilience may assist in crafting fit-for-purpose resilience interventions for educators in multicultural environments.

This paper provides twelve practical tips for institutions preparing to submit successful applications for the ASPIRE Award in the category of Assessment of Students, part of AMEE's global initiative to recognize excellence in health professions education. This paper emphasizes the importance of achieving institutional buy-in, aligning assessment systems with the school's mission and context, assembling a strong submission team, and providing explanation of the award criteria. It highlights the collection and presentation of comprehensive evidence, including metrics like psychometric analysis and construct alignment, to demonstrate standards of excellence. Engaging students in the application process is critical, as their perspectives enhance transparency, equity, and accountability. Institutions are encouraged to address inconsistencies, demonstrate impact through quality improvement cycles, and showcase their commitment to continuous learning and professional development. The tips also include the value of engaging with the ASPIRE Academy for expert support and collaboration during the application process. This paper highlights that the ASPIRE award is an opportunity to foster reflection, collaboration, and innovation, while contributing to global standards of excellence in assessment in health professions education.