JMIR Medical Education最新文献

Background: The venipuncture is one of the most frequently performed procedures in health care. Arm phantoms are available for training, because the procedure itself can be challenging. These phantom arms do not represent a realistic setting and do not offer opportunities to train challenging scenarios.

Objective: This randomized, single-blind study aimed to train health care workers on both a commercially available injection arm and an in-house developed 3D-printed arm, to evaluate the perceived realism and adequacy of training on both arms.

Methods: Participants were trained on both the commercially available arm (arm A) and the 3D-printed arm (arm B). Participants were randomized and blinded from knowing which arm they started training on. A questionnaire was filled in on, among others, the perceived realism of the arm (0 for not realistic, 100 for realistic) and adequacy of the training (inadequate, moderate, or adequate).

Results: A total of 68 participants evaluated the perceived realism of arm A and B, which were scored on average 62.97 (SD 21.47) and 63.79 (SD 17.45), respectively. The difference in perceived realism of the two arms was not statistically significant (based on the paired t test, mean difference=-0.82, P=.78). Training on arm A was reported inadequate by 7% (5/68 participants), moderately adequate by 31% (21/68), and adequate by 62% (42/68). This was not significantly different from arm B (marginal homogeneity test, P=.74), with 4% (3/68), 38% (26/68), and 57% (39/68), respectively, reporting that the training was inadequate, moderately adequate, and adequate.

Conclusions: The 3D-printed arm is as realistic and provides an equally adequate training compared to the commercially available arm. The 3D-printed arm offers the additional possibility to design different models representing several levels of difficulty for vascular morphology. This potentially lowers the number of venipuncture failures by preparing health care workers on challenging scenarios.

Background: Since January 2022, Sharjah in the United Arab Emirates has implemented the 4-day work week model for the first time in the public and private sectors, including universities. While this framework may enhance productivity and work-life balance for many professionals, the current study specifically explores the perceptions of students in medicine, dentistry, and health sciences programs regarding the impact of transitioning from a 5-day to a 4-day work week on their academic performance.

Objective: The objective of this study was to explore and analyze the perceptions of students in medicine, dentistry, and health sciences regarding the implementation of a 4-day academic week in the Emirate of Sharjah, United Arab Emirates.

Methods: Twenty-four university students (mean age 20.95, SD 1.30 years; 12 men) studying in medicine, dentistry, physiotherapy, nursing, or medical diagnostic imaging programs, who experienced a transition from a 5-day week to a 4-day week, participated in semistructured interviews lasting approximately 20-30 minutes. All interviews were recorded and transcribed verbatim. The Braun and Clarke 6-phase framework of thematic analysis was used.

Results: We identified 5 themes: academic journey, academic work-life balance, support systems, classroom dynamics, and common stressors of the 4-day academic week. Overall, most students reported increased motivation, engagement, and academic achievement following the transition from a 5-day to a 4-day week. In addition, participants described a positive academic work-life balance, improved physical and mental well-being, optimal use of time for both academic and personal commitments, favorable support from faculty and family members, and maintained or even improved attendance levels. Nevertheless, some students expressed concerns about condensed schedules and longer days, increased stress, disrupted work-life balance, and inadequate support systems to cope with this new framework.

Conclusions: Overall, the 4-day academic week enhanced motivation, academic performance, work-life balance, and the physical and mental well-being of medicine, dental, and health science students. However, some students experienced challenges related to condensed schedules and increased stress. These mixed outcomes highlight that while the 4-day work week offers notable advantages, careful planning and support are essential to mitigate the potential drawbacks and ensure all students can succeed within this new academic framework. Future research could explore strategies to address these challenges and further improve the 4-day week experience for all students.

Unlabelled: Faculty development is a cornerstone of academic medicine, supporting personal growth, professional advancement, and departmental effectiveness across all stages of a faculty member's career. Among the tools available, faculty retreats have increasingly emerged as a high-impact strategy to foster collaboration, advance strategic planning, and address individual and collective goals in a structured, reflective setting. While retreats are widely used in other sectors, practical guidance tailored to the academic medicine context remains limited. This tutorial offers a comprehensive, step-by-step framework for planning and implementing faculty retreats within academic departments. Key elements of effective retreat design are outlined, including (1) conducting a preretreat needs assessment to align goals with faculty priorities, (2) selecting an appropriate format (eg, in-person or hybrid), (3) fostering psychological safety to enhance participation, and (4) using facilitation techniques that promote inclusive dialogue and actionable outcomes. The tutorial also emphasizes logistical considerations, such as agenda design, timing, and participant engagement strategies, alongside mechanisms to ensure follow-up and accountability after the retreat. In addition to highlighting common barriers, such as resource limitations, scheduling constraints, and engagement disparities, the tutorial provides practical solutions drawn from real-world examples in academic medicine. By integrating thoughtful planning, evidence-informed facilitation, and postretreat follow-through, faculty retreats can serve as transformative experiences that support both individual development and departmental cohesion. This resource aims to fill a gap in the literature by equipping leaders in academic medicine with a structured approach to designing, executing, and sustaining the benefits of faculty retreats.

The increasing use of generative large language models (LLMs) necessitates a fundamental reevaluation of traditional didactic lectures in medical education, particularly within psychiatry. The specialty's inherent diagnostic ambiguity, biopsychosocial complexity, and reliance on nuanced interpersonal skills demand an educational model that transcends mere information transfer, focusing instead on cultivating sophisticated clinical reasoning. This viewpoint argues for a shift from passive knowledge transmission to active, facilitated development of higher-order thinking, aligning with the Bloom taxonomy. We describe four core propositions: (1) shifting foundational knowledge acquisition to faculty-curated asynchronous artificial intelligence (AI)-assisted micromodules; (2) transforming synchronous time into "Ambiguity Seminars" for discussing nuanced cases, biopsychosocial formulation, and ethical dilemmas, leveraging faculty expertise in guiding reasoning; (3) integrating live LLM critical interaction drills to develop prompt engineering skills and critical appraisal of AI outputs; and (4) realigning assessment methods (eg, objective structured clinical examinations [OSCEs], reflective writing) to evaluate clinical reasoning and integrative skills rather than rote recall. Successful implementation requires comprehensive faculty development, explicit institutional investment, and a phased approach that addresses scalability across varying resource settings. This reimagined approach aims to cultivate clinical wisdom, equipping psychiatric trainees with adaptive reasoning frameworks essential for excellence in an AI-mediated future.

Unlabelled: The Dellavalle/Dunnick Dermato-Epidemiology Lab transitioned from a single campus to a dual-campus collaboration between the University of Colorado and the University of Minnesota in 2024. Since the 2020 COVID-19 pandemic, the laboratory has been operating on Zoom and allows medical students from any institution to join. This innovative laboratory structure offers students and other researchers unique opportunities to engage in dermatological research and develop professional networks across two large academic institutions. The laboratory's model embraces a virtual collaborative approach, promotes inclusivity, encourages student-led inquiry, and provides a structured environment for professional development and academic output. Through its commitment to diverse student perspectives and interdisciplinary cooperation, the Dellavalle/Dunnick Dermato-Epidemiology Lab creates a new, equitable, nationwide model for research and mentorship in dermatology, supporting medical students, residents, and fellows to navigate future careers in dermatology.

Background: Competency-based medical education relies heavily on high-quality narrative reflections and feedback within workplace-based assessments. However, evaluating these narratives at scale remains a significant challenge.

Objective: This study aims to develop and apply natural language processing (NLP) models to evaluate the quality of resident reflections and faculty feedback documented in Entrustable Professional Activities (EPAs) on Taiwan's nationwide Emyway platform for otolaryngology residency training.

Methods: This 4-year cross-sectional study analyzes 300 randomly sampled EPA assessments from 2021 to 2025, covering a pilot year and 3 full implementation years. Two medical education experts independently rated the narratives based on relevance, specificity, and the presence of reflective or improvement-focused language. Narratives were categorized into 4 quality levels-effective, moderate, ineffective, or irrelevant-and then dichotomized into high quality and low quality. We compared the performance of logistic regression, support vector machine, and bidirectional encoder representations from transformers (BERT) models in classifying narrative quality. The best performing model was then applied to track quality trends over time.

Results: The BERT model, a multilingual pretrained language model, outperformed other approaches, achieving 85% and 92% accuracy in binary classification for resident reflections and faculty feedback, respectively. The accuracy for the 4-level classification was 67% for both. Longitudinal analysis revealed significant increases in high-quality reflections (from 70.3% to 99.5%) and feedback (from 50.6% to 88.9%) over the study period.

Conclusions: BERT-based NLP demonstrated moderate-to-high accuracy in evaluating the narrative quality in EPA assessments, especially in the binary classification. While not a replacement for expert review, NLP models offer a valuable tool for monitoring narrative trends and enhancing formative feedback in competency-based medical education.

Background: Stomatology education has experienced substantial transformations over recent decades. Nevertheless, a comprehensive summary encompassing the entirety of this field remains absent in the literature.

Objective: This study aimed to perform a bibliometric analysis to evaluate the research status, current focus, and emerging trends in this field over the last two decades.

Methods: We retrieved publications concerning teaching and learning in stomatology education from the Web of Science core collection covering the period from 2003 to 2023. Subsequently, we conducted a bibliometric analysis and visualization using R-Bibliometrix and CiteSpace.

Results: In total, 5528 publications focusing on teaching and learning in stomatology education were identified. The annual number of publications in this field has shown a consistent upward trend. The United States and the United Kingdom emerged as the leading contributors to research. Among academic institutions, the University of Iowa produced the highest number of publications. The Journal of Dental Education was identified as the journal with the highest citation. Wanchek T authored the most highly cited articles in the field. Emerging research hotspots were characterized by keywords such as "deep learning," "machine learning," "online learning," "virtual reality," and "convolutional neural network." The thematic map analysis further revealed that "surgery" and "accuracy" were categorized as emerging themes.

Conclusions: The visualization bibliometric analysis of the literature clearly depicts the current hotspots and emerging topics in stomatology education concerning teaching and learning. The findings are intended to serve as a reference to advance the development of stomatology education research globally.