JMIR Medical Education

Technology, innovation, and openness in medical education in the information age.

Editor-in-Chief:

Blake J. Lesselroth, MD MBI FACP FAMIA, University of Oklahoma | OU-Tulsa Schusterman Center; University of Victoria, British Columbia


Impact Factor 3.6

JMIR Medical Education (JME, ISSN: 2369-3762, Impact Factor 3.6) is an open access, PubMed-indexed, peer-reviewed journal focusing on technology, innovation, and openness in medical education.This includes e-learning and virtual training, which has gained critical relevance in the (post-)COVID world. Another focus is on how to train health professionals to use digital tools. We publish original research, reviews, viewpoint, and policy papers on innovation and technology in medical education. As an open access journal, we have a special interest in open and free tools and digital learning objects for medical education and urge authors to make their tools and learning objects freely available (we may also publish them as a Multimedia Appendix). We also invite submissions of non-conventional articles (e.g., open medical education material and software resources that are not yet evaluated but free for others to use/implement). 

In our "Students' Corner," we invite students and trainees from various health professions to submit short essays and viewpoints on all aspects of medical education, particularly suggestions on improving medical education and suggestions for new technologies, applications, and approaches. 

In 2023, JMIR Medical Education received an inaugural Journal Impact Factor™ of 3.6 (Source: Journal Citation Reports™ from Clarivate, 2023). The journal is indexed in MEDLINE, PubMed, PubMed Central, Scopus, DOAJ, and the Emerging Sources Citation Index (Clarivate).

Recent Articles

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Theme Issue [2023]: Digital Health Skills and Competencies for Clinicians and Health Care Professionals

A momentous amount of health data has been and is being collected. Across all levels of healthcare, data is driving decision making and impacting patient care. A new knowledge and role for those in healthcare is emerging – the need for a health data informed workforce. In this commentary, the authors describe approaches needed to build a health data informed workforce, a new and critical skill for the healthcare ecosystem.

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Reviews in Medical Education

The integration of chatbots in nursing education is a rapidly evolving area with potential transformative impacts. This narrative review aims to synthesize and analyze the existing literature on chatbots in nursing education.

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Artificial Intelligence (AI) in Medical Education

The increasing significance of artificial intelligence (AI) in healthcare has generated an increasing need for healthcare professionals to possess a comprehensive understanding of AI technologies, requiring an adaptation in medical education.

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Health Professionals' Training in eHealth, Digital Medicine, Medical Informatics

Healthcare professionals must learn continuously as a core part of their work. As the rate of knowledge production in biomedicine increases, better support for providers’ continuous learning is needed. In health systems, feedback is pervasive and is widely considered to be essential for learning that drives improvement. Clinical quality dashboards are one widely-deployed approach to delivering feedback, but engagement with these systems is commonly low, reflecting a limited understanding of how to improve the effectiveness of feedback about health care. When coaches and facilitators deliver feedback for improving performance, they aim to be responsive to the recipient’s motivations, information needs, and preferences. However, such functionality is largely missing from dashboards and feedback reports. Precision feedback is the delivery of high-value, motivating performance information that is prioritized based on its motivational potential for a specific recipient, including their needs and preferences. Anesthesia care offers a clinical domain with high-quality performance data and an abundance of evidence-based quality metrics.

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Mobile Approaches to Medical Education

Mobile health (mHealth) is an emerging mobile communication and networking technology for healthcare systems in recent years. The field of mHealth in medical education is growing extremely rapidly. mHealth has brought new changes to medical education. However, no previous study has analyzed both mHealth and medical education.

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Theme Issue [2023]: Digital Health Skills and Competencies for Clinicians and Health Care Professionals

The relationship between educational outcomes and the use of online clinical knowledge support systems in teaching hospitals remains unknown in Japan. A previous study in this regard could have been affected by recall bias because of using a self-reported questionnaire survey.

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Viewpoint and Opinions on Innovation in Medical Education

Large language models (LLM) like ChatGPT, are transforming the landscape of medical education. They offer a vast range of applications, such as tutoring (personalized learning), patient simulation, generation of exam questions, and streamlined access to information. The rapid advancement of medical knowledge and the need for personalized learning underscore the relevance and timeliness of exploring innovative strategies for integrating artificial intelligence (AI) into medical education. In this paper, we propose coupling evidence-based learning strategies such as active recall and memory cues with AI to optimize learning. These strategies include the generation of tests, mnemonics, and visual cues.

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Viewpoint and Opinions on Innovation in Medical Education

Digital technologies have for more than fifty years been employed for creation and distribution of knowledge in health services. Adding to applications for clinical decision support and population health monitoring, digital social media have in the recent decade been employed for knowledge translation, i.e. used in the process where research findings created in academic settings are established as evidence and distributed for use in clinical practice, policymaking, and self-management of health. Until today, it has been considered normal for medical and public health institutions to have social media accounts for dissemination of novel research findings and facilitating conversation about these. However, recent events such as the transformation of the microblog Twitter to platform X has brought to light the fact that the social media industry needs to exploit user data to generate revenue. In this Viewpoint article, it is argued that a redirection is required of social media use in the translation of knowledge to action in medicine and public health. A new kind of social internet is currently forming. The fediverse denotes an ensemble of open social media that can communicate with each other, while remaining independent platforms. In several countries, government institutions, universities and newspapers use open social media to distribute information and enable discussions. They control their own channels while being able to communicate with other platforms through open standards. Examples of medical knowledge translation at open social media platforms where users are less exposed to disinformation are also beginning to appear. The current status of the social media industry calls for a broad discussion about the use of social technologies by health institutions involving researchers and health service practitioners, academic leaders, scientific publishers, social technology providers, policymakers, and the public. This debate should not primarily take place on social media platforms, but at universities, in scientific journals, at public seminars, and other venues allowing transparent and undisturbed communication and formation of opinions.

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Research Letter

The recent introduction of Chat Generative Pre-trained Transformer 4 Vision (ChatGPT-4V) has expanded the capabilities of language models to include image input features, potentially broadening their application in the medical field. This Research Letter evaluates the performance of ChatGPT-4V in interpreting clinical images and tables through the Japanese Medical Licensing Exam (JMLE). Employing the September 25, 2023, version of ChatGPT-4V, the study compared the program’s responses to the 117th JMLE against the passing criteria and the average scores of human examinees. While ChatGPT-4V surpassed the passing threshold with an 85.1% correct response rate in essential knowledge and 76.5% in other areas, it fell short in image-based (71.9%) and table-based questions (35.0%), indicating a significant gap compared to human performance. This suggests limitations in the model’s image and table interpretation, exacerbated by its lower proficiency in non-Latin characters and potential overreliance on text information. Despite its success in passing the JMLE, the study highlights the need for further development of ChatGPT-4V to enhance its reliability for medical applications, including diagnostics.

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Reviews in Medical Education

In recent years Virtual reality (VR) has gained significant importance in medical education. Radiology education also has seen the induction of VR technology. However, there is no comprehensive review in this specific area. The present review aims to fill this gap in the knowledge.

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Preprints Open for Peer-Review

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