JMIR Medical Education

The creation of large language models (LLMs) such as ChatGPT is an important step in the development of artificial intelligence(AI), which shows great potential in medical education due to its powerful language understanding and generative capabilities. The purpose of this study was to quantitatively evaluate and comprehensively analyze ChatGPT's performance in handling questions for the National Nursing Licensure Examination in China and the United States, including the National Council Licensure Examination for Registered Nurses (NCLEX-RN) and the National Nursing Licensure Examination (NNLE).

Limited digital literacy is a barrier for vulnerable patients accessing health care.

The Objective Structured Clinical Examination (OSCE) is a pivotal tool for assessing health care professionals and plays an integral role in medical education.

An integration of digital medicine into medical education can help future physicians shape the digital transformation of medicine.

Instructional and clinical technologies have been transforming dental education. With the emergence of artificial intelligence (AI), the opportunities of utilizing AI in education has increased. With the recent advancement of generative AI, Large Language Models (LLMs) and foundation models (FM) gained attention with their capabilities in natural language understanding and generation as well as combining multiple types of data, such as text, images, and audio. A common example has been ChatGPT, which is based on a powerful LLM, generative pretrained transformer (GPT) model. This article discusses the potential benefits and challenges of incorporating LLMs in dental education, focusing on periodontal charting with a use case to outline capabilities of LLMs. LLMs can provide personalized feedback, generate case scenarios, and create educational content to contribute to the quality of dental education. However, challenges, limitations and risks exist, including bias and inaccuracy in the content created, privacy and security concerns, and the risk of overreliance. With the guidance and oversight, and by effectively and ethically integrating LLMs, dental education can incorporate engaging and personalized learning experiences for students towards readiness for real-life clinical practice.

Professionals with expertise in health informatics play a crucial role in the digital health sector. Despite efforts to train experts in this field, the specific impact of such training, especially for individuals from diverse academic backgrounds, remains undetermined.

Medical interviewing is a critical skill in clinical practice, yet opportunities for practical training are limited in Japanese medical schools, necessitating urgent measures. Given advancements in artificial intelligence (AI) technology, its application in the medical field is expanding. However, reports on its application in medical interviews in medical education are scarce.

Currently, there is a need to optimize knowledge on digital transformation in mental health care, including digital therapeutics (eg, prescription apps), in medical education. However, in Germany, digital health has not yet been systematically integrated into medical curricula and is taught in a relatively small number of electives. Challenges for lecturers include the dynamic field as well as lacking guidance on how to efficiently apply innovative teaching formats for these new digital competencies. Quality improvement projects provide options to pilot-test novel educational offerings, as little is known about the acceptability of participatory approaches in conventional medical education.

ChatGPT has been tested in health care, including the US Medical Licensing Examination and specialty exams, showing near-passing results. Its performance in the field of anesthesiology has been assessed using English board examination questions; however, its effectiveness in Korea remains unexplored.

Australian nursing programs aim to introduce students to digital health requirements for practice. However, innovation in digital health is more dynamic than education providers’ ability to respond. It is uncertain whether what is taught and demonstrated in nursing programs meets the needs and expectations of clinicians regarding capability of nurse graduates.

The use of digital online teaching media in improving surgical skills of medical students is indispensable, yet it is still not widely explored objectively. The first-person-view online teaching method may be more effective as it provides more realism to surgical clerkship students in achieving basic surgical skills.

Healthcare delivery is undergoing an accelerated period of digital transformation, spurred in-part by the COVID-19 pandemic and the use of “virtual-first” care delivery models like telemedicine. Medical education has responded to this shift with calls for improved digital health training, but there is as yet no universal understanding of needed competencies, domains, and best practices for teaching these skills. In this paper, we argue that a “digital determinants of health” (DDoH) framework for understanding intersections of health outcomes, technology, and training is critical to the development of comprehensive digital health competencies in medical education. Much like current social determinants of health models, the DDoH framework can be integrated into undergraduate, graduate, and professional education to guide training interventions as well as competency development and evaluation. We provide possible approaches to integrating this framework into training programs and explore priorities for future research in digitally-competent medical education.