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Background <p>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.</p> Method <p>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.</p> Results <p>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.</p> Conclusion <p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月23日

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  • Mounyah Basil,
  • Waad Ahmed,
  • Reem Hajeomar,
  • Judith Strawbridge,
  • Matthew Lynch,
  • Banan Mukhalalati

摘要

Background

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.

Method

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.

Results

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.

Conclusion

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.