JMIR Medical Education

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

Editor-in-Chief:

Nabil Zary, MD, PhD, Mohammed Bin Rashid University of Medicine and Health Science, Dubai, UAE


Impact Factor 2023

JMIR Medical Education (JME) 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. 

The journal is indexed in PubMed, PubMed Central, Scopus, DOAJ, and the Emerging Sources Citation Index (Clarivate).

Recent Articles

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Theme Issue: ChatGPT and Generative Language Models in Medical Education

The integration of large language models (LLMs), such as those in the Generative Pre-trained Transformers (GPT) series, into medical education has the potential to transform learning experiences for students and elevate their knowledge, skills, and competence. Drawing on a wealth of professional and academic experience, we propose that LLMs hold promise for revolutionizing medical curriculum development, teaching methodologies, personalized study plans and learning materials, student assessments, and more. However, we also critically examine the challenges that such integration might pose by addressing issues of algorithmic bias, overreliance, plagiarism, misinformation, inequity, privacy, and copyright concerns in medical education. As we navigate the shift from an information-driven educational paradigm to an artificial intelligence (AI)–driven educational paradigm, we argue that it is paramount to understand both the potential and the pitfalls of LLMs in medical education. This paper thus offers our perspective on the opportunities and challenges of using LLMs in this context. We believe that the insights gleaned from this analysis will serve as a foundation for future recommendations and best practices in the field, fostering the responsible and effective use of AI technologies in medical education.

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Preliminary Experiences with New Educational Technology

Graduate students in medical fields must learn about epidemiology and data analysis to conduct their research. R is a software environment used to develop and run packages for statistical analysis; it can be challenging for students to learn because of compatibility with their computers and problems with package installations. Jupyter Notebook was used to run R, which enhanced the graduate students’ ability to learn epidemiological data analysis by providing an interactive and collaborative environment that allows for more efficient and effective learning.

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Reviews in Medical Education

Single-choice items (eg, best-answer items, alternate-choice items, single true-false items) are 1 type of multiple-choice items and have been used in examinations for over 100 years. At the end of every examination, the examinees’ responses have to be analyzed and scored to derive information about examinees’ true knowledge.

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Graduate and Postgraduate Education for Health Professionals

Near-peer teaching (NPT) is becoming an increasingly popular pedagogical tool in health professions education. Despite the shift in formal medical education from face-to-face teaching toward encompassing web-based learning activities, NPT has not experienced a similar transition. Apart from the few reports on NPT programs hastily converted to web-based learning in light of the COVID-19 pandemic, no studies to date have explored web-based learning in the specific context of NPT.

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

Electronic health records (EHRs) play a substantial role in modern health care, especially during prerounding, when residents gather patient information to inform daily care decisions of the care team. The effective use of the EHR system is crucial for efficient and frustration-free prerounding. Ideally, the system should be designed to support efficient user interactions by presenting data effectively and providing easy navigation between different pages. Additionally, training on the system should aim to make user interactions more efficient by familiarizing the users with best practices that minimize interaction time while using the full potential of the system’s capabilities. However, formal training on EHR systems often falls short of providing residents with all the necessary EHR-related skills, leading to the adoption of inefficient practices and the underuse of the system’s full range of capabilities.

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Student/Learners Perceptions and Experiences with Educational Technology

Telemedicine use increased as a response to health care delivery changes necessitated by the COVID-19 pandemic. However, lack of standardized curricular content creates gaps and inconsistencies in effectively integrating telemedicine training at both the undergraduate medical education and graduate medical education levels.

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Dental Education and Training for Dentists and Dental Students

A successful periodontitis treatment demands good manual skills. A correlation between biological sex and dental students’ manual dexterity is currently unknown.

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Theme Issue: ChatGPT and Generative Language Models in Medical Education

Large language models, such as ChatGPT by OpenAI, have demonstrated potential in various applications, including medical education. Previous studies have assessed ChatGPT’s performance in university or professional settings. However, the model’s potential in the context of standardized admission tests remains unexplored.

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Undergraduate Education for Future Doctors

The use of artificial intelligence (AI) in medicine is expected to increase significantly in the upcoming years. Advancements in AI technology have the potential to revolutionize health care, from aiding in the diagnosis of certain diseases to helping with treatment decisions. Current literature suggests the integration of the subject of AI in medicine as part of the medical curriculum to prepare medical students for the opportunities and challenges related to the use of the technology within the clinical context.

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Artificial Intelligence (AI) in Medical Education

Large language models exhibiting human-level performance in specialized tasks are emerging; examples include Generative Pretrained Transformer 3.5, which underlies the processing of ChatGPT. Rigorous trials are required to understand the capabilities of emerging technology, so that innovation can be directed to benefit patients and practitioners.

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Quality of Medical Educational and Instructional Material

The COVID-19 pandemic was accompanied by the spread of uncontrolled health information and fake news, which also quickly became an infodemic. Emergency communication is a challenge for public health institutions to engage the public during disease outbreaks. Health professionals need a high level of digital health literacy (DHL) to cope with difficulties; therefore, efforts should be made to address this issue starting from undergraduate medical students.

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Graduate and Postgraduate Education for Health Professionals

Prolonged grief disorder (PGD) is a newly recognized mental disorder characterized by pervasive intense grief that persists longer than cultural or social expectations and interferes with functioning. The COVID-19 epidemic has resulted in increased rates of PGD, and few clinicians feel confident in treating this condition. PGD therapy (PGDT) is a simple, short-term, and evidence-based treatment developed in tandem with the validation of the PGD diagnosis. To facilitate the dissemination of PGDT training, we developed a web-based therapist tutorial that includes didactic training on PGDT concepts and principles as well as web-based multimedia patient scenarios and examples of clinical implementation of PGDT.

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Preprints Open for Peer-Review

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