ArticleJMIR medical education2026
Impact of a Practical, Hands-On, Continuing Professional Development Course About AI in Health Care Professions Education on the Perceptions and Behaviors of Health Care Educators: Qualitative Case Study.
Article in JMIR medical education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- AI-Empowered Nuclear Medicine Education, Part 2: Practical AI Applications for Educators.Journal of nuclear medicine technology · 2026Article
- AI-Empowered Nuclear Medicine Education, Part 1: Theoretical and Ethical Foundation.Journal of nuclear medicine technology · 2026Article
- AI-Empowered Nuclear Medicine Education, Part 3: Practical AI Applications for Learners.Journal of nuclear medicine technology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI) is increasingly being used in many aspects of society, including health care and education. AI has the potential to enhance health care delivery, education, and administration. Health care trainees will be required to master these AI technologies. To teach trainees to effectively and ethically leverage AI technologies, educators must be appropriately trained and empowered to use these technologies. Objective: We developed a health professions education course to enable health care professionals to overcome their fears and concerns about integrating multimodal generative AI technologies in daily practice. The course was also designed to foster generative AI skills and confidence in educational, administrative, research, and clinical activities. Methods: Using a multimethod approach, we analyzed data gathered from three different sources using the 6-phase reflexive thematic analysis by Braun and Clarke. This involved familiarization with the data sources, generating initial codes, developing, refining, and defining the themes, and finally, writing up the results. Results: Our findings indicate that 16 of 21 (76%) learners initially described apprehension or fear toward AI technologies. After experiential engagement with AI technologies together with their peers, they were able to shift their perspectives and gain confidence to integrate AI tools in their daily practice. Conclusions: A brief 6-week continuing professional development course on the use of AI technologies for health care professional educators, focused on experiential and peer-based learning, resulted in shifts in perception, affect, and behavior toward AI technologies. It also propelled learners to shift increasingly outward in their discussion, application, and preliminary advocacy for AI technologies in their daily practice.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.