# A scoping review of the use of generative artificial intelligence tools in health profession education

**Authors:** Mounyah Basil, Waad Ahmed, Reem Hajeomar, Judith Strawbridge, Matthew Lynch, Banan Mukhalalati

PMC · DOI: 10.1186/s12909-025-08527-3 · BMC Medical Education · 2026-01-23

## TL;DR

This scoping review explores how generative AI is being used in health profession education, highlighting its potential and challenges.

## Contribution

The study provides a comprehensive synthesis of current literature on GenAI integration in health professions education.

## Key findings

- Most studies focused on ChatGPT in medical and nursing education, particularly for content creation.
- Curriculum design and GenAI literacy remain underexplored areas in the literature.
- Students and faculty generally have a positive perception of GenAI in education.

## Abstract

Generative Artificial Intelligence (GenAI) is one of the leading innovations that is expected to reshape society for decades to come. Health professions education (HPE) programs are expected to prepare graduates with adequate knowledge and skills to provide high-quality patient-centered care. Although the use of GenAI in health professions is increasing, its optimal integration in HPE is still ambiguous. This scoping review aims to synthesize currently available literature regarding the use of GenAI in health professions education.

This scoping review is conducted following JBI methodology for scoping reviews framework 2020 and aligned with PRISMA-ScR. A systematic and comprehensive search was conducted in PubMed, ERIC, CINAHL, Embase, Scopus, Cochrane Library, and ProQuest Central with no language restrictions. The identified evidence was screened and extracted using Covidence software. Publications on the integration of GenAI in undergraduate or graduate health profession education were considered. Data was analyzed and presented using graphs and charts. Followed by a narrative thematic mapping of the included studies.

Out of 14,208 scanned records, 241 were considered eligible. The included studies discuss the application of GenAI in diverse education processes of different health professions, such as curriculum design, content creation, content delivery, personalized learning, assessment, evaluation, and feedback provision. Most studies focused on ChatGPT integration in medical and nursing education, with content creation emerging as the predominant area of integration, whereas curriculum design and GenAI literacy were underexplored. Perception studies reported a positive perspective regarding GenAI used in education among students and faculty.

This review provides an overview of the current integration of GenAI in HPE in the literature, highlighting the associated opportunities, challenges, facilitators, and barriers. Future education efforts should focus on enhancing GenAI literacy, developing policy, and adopting a balanced approach. In addition to conducting comparative studies and long-term assessment of GenAI impact.

The online version contains supplementary material available at 10.1186/s12909-025-08527-3.

## Full-text entities

- **Genes:** NINL (ninein like) [NCBI Gene 22981] {aka NLP}
- **Diseases:** hallucination (MESH:D006212), infection (MESH:D007239), anxiety (MESH:D001007), HPE (OMIM:603663), congenital heart disease (MESH:D006330), AI (MESH:C538142), LLM (MESH:D007806), neurology (MESH:D009461), disabilities (MESH:D009069)
- **Chemicals:** GenAI (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

53 references — full list in the complete paper: https://tomesphere.com/paper/PMC12911342/full.md

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Source: https://tomesphere.com/paper/PMC12911342