JMIR Medical Education

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

Editor-in-Chief:

Gunther Eysenbach, MD, MPH, FACMI, Founding Editor and Publisher; Adjunct Professor, School of Health Information Science, University of Victoria, Canada


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 PubMed, PubMed Central, Scopus, DOAJ, and the Emerging Sources Citation Index (Clarivate).

Recent Articles

Article Thumbnail
Virtual Reality and Augmented Reality in Medical Education

Telementorship provides a way to maintain the professional skills of isolated rural health care workers. The incorporation of augmented reality (AR) technology into telementoring systems could be used to mentor health care professionals remotely under different clinical situations.

|
Article Thumbnail
Theme Issue: ChatGPT and Generative Language Models in Medical Education

ChatGPT has shown impressive performance in national medical licensing examinations, such as the United States Medical Licensing Examination (USMLE), even passing it with expert-level performance. However, there is a lack of research on its performance in low-income countries’ national licensing medical examinations. In Peru, where almost one out of three examinees fails the national licensing medical examination, ChatGPT has the potential to enhance medical education.

|
Article Thumbnail
Virtual Reality and Augmented Reality in Medical Education

Virtual reality is used to an increasing extent in various fields and is now making inroads into health and social education. Virtual reality simulation can provide a safe and controlled environment for students to practice and master skills that are transferable to real-world situations without putting patients, clients, or themselves at risk of any harm. Virtual reality simulation using 360° videos represents a novel approach to simulation in health care and social work education, and this inspired our interest in exploring students’ experiences with such a learning activity.

|
Article Thumbnail
Research Letter

Using large language models, we developed a method to efficiently query existing flashcard libraries and select those most relevant to an individual's medical school curricula.

|
Article Thumbnail
Theme Issue: ChatGPT and Generative Language Models in Medical Education

Large language model (LLM)–based chatbots are evolving at an unprecedented pace with the release of ChatGPT, specifically GPT-3.5, and its successor, GPT-4. Their capabilities in general-purpose tasks and language generation have advanced to the point of performing excellently on various educational examination benchmarks, including medical knowledge tests. Comparing the performance of these 2 LLM models to that of Family Medicine residents on a multiple-choice medical knowledge test can provide insights into their potential as medical education tools.

|
Article Thumbnail
Artificial Intelligence (AI) in Medical Education

Artificial intelligence (AI) has many applications in various aspects of our daily life, including health, criminal, education, civil, business, and liability law. One aspect of AI that has gained significant attention is natural language processing (NLP), which refers to the ability of computers to understand and generate human language.

|
Article Thumbnail
Tutorials in Medical Education

The use of virtual reality (VR) stimulation in clinical settings has increased in recent years. In particular, there has been increasing interest in the use of VR stimulation for a variety of purposes, including medical training, pain therapy, and relaxation. Unfortunately, there is still a limited amount of real-world 360-degree content that is both available and suitable for these applications. Therefore, this tutorial paper describes a pipeline for the creation of custom VR content. It covers the planning and designing of content; the selection of appropriate equipment; the creation and processing of footage; and the deployment, visualization, and evaluation of the VR experience. This paper aims to provide a set of guidelines, based on first-hand experience, that readers can use to help create their own 360-degree videos. By discussing and elaborating upon the challenges associated with making 360-degree content, this tutorial can help researchers and health care professionals anticipate and avoid common pitfalls during their own content creation process.

|
Article Thumbnail
Training for Public Health Professionals and Epidemiologists

Formal education of oncology is lacking in many undergraduate medical curricula. Mentoring schemes can expose participants to specific areas of medicine and may address the shortfalls in oncology education. Few mentoring schemes have been designed within the United Kingdom, especially within oncology. There is a need to understand reasons for mentor and mentee participation in such schemes and to identify ways to minimize barriers to engagement.

|
Article Thumbnail
Viewpoint and Opinions on Innovation in Medical Education

The COVID-19 pandemic altered how residency interviews occur. Despite 2 years of web-based interviews, these are still perceived as inferior to in-person experiences. Showcasing a program and location is critical for recruitment; however, it is difficult to highlight the program’s location and community digitally. This article presents the authors’ viewpoints on designing and implementing a virtual second look for residency applicants.

|
Article Thumbnail
Theme Issue: ChatGPT and Generative Language Models in Medical Education

ChatGPT is a conversational large language model that has the potential to revolutionize knowledge acquisition. However, the impact of this technology on the quality of education is still unknown considering the risks and concerns surrounding ChatGPT use. Therefore, it is necessary to assess the usability and acceptability of this promising tool. As an innovative technology, the intention to use ChatGPT can be studied in the context of the technology acceptance model (TAM).

|
Article Thumbnail
Theme Issue: ChatGPT and Generative Language Models in Medical Education

Large language models (LLMs) have demonstrated significant potential in diverse domains, including medicine. Nonetheless, there is a scarcity of studies examining their performance in medical examinations, especially those conducted in languages other than English, and in direct comparison with medical students. Analyzing the performance of LLMs in state medical examinations can provide insights into their capabilities and limitations and evaluate their potential role in medical education and examination preparation. 

|
Article Thumbnail
Evaluation of Medical Education

Despite guidelines recommending the use of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) in certain patients with type 2 diabetes (T2D), they are not being prescribed for many of these patients. Web-based continuing medical education (CME) patient simulations have been used to identify clinicians’ practice gaps and improve clinical decision-making as measured within a simulation, but the impact of this format on real-world treatment has not been researched.

|

Preprints Open for Peer-Review

We are working in partnership with