Integrating diversity, equity, and inclusion in generative AI applications for healthcare education: a scoping review.

Abstract

Capabilities of generative AI (GenAI) tools continue to advance, positioning them as promising resources for supporting healthcare education. However, their implementation also presents challenges and unknown implications related to Diversity, Equity and Inclusion (DEI). Despite the growing body of literature on GenAI, there remains a significant gap in research examining how DEI considerations are addressed in GenAI applications in healthcare education. This review synthesizes existing literature on the integration of DEI in GenAI applications for healthcare education. Specifically, it examines how DEI is recognized, the strategies used for its integration, and the reported outcomes of these efforts. It also identifies limitations and offers recommendations for integrating DEI in GenAI within healthcare education. JBI scoping review methodology was used, and three databases (PubMed, Embase, and CINAHL) were searched. The reporting was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for the scoping review (PRISMA-ScR). Descriptive statistics and content analysis were conducted, with findings reported using tables and narrative summaries. This review included 16 studies. Content generation for educational materials was the dominant use case (n = 12), while fewer studies explored more complex applications such as interactive virtual patient simulations (n = 3) and simulation-based, scenario-driven training (n = 2), which may reflect the early stage of the field. Notable gaps identified across the 16 studies included a lack of consistent conceptual clarity regarding how to operationalize and integrate DEI, limited engagement with diverse partners in the development of GenAI, and a lack of evaluations examining how DEI is incorporated or addressed. Most studies instead evaluated aspects of GenAI performance or user perspectives. By identifying these gaps, this review offers a foundation for developing frameworks that support systematic DEI integration across the GenAI lifecycle, from innovation development and implementation through to evaluation, and informs future research directions by calling for multi-perspective collaboration and institutional accountability in how GenAI is monitored and evaluated. This scoping review represents an important first step upon which future efforts can build to advance the integration and evaluation of DEI in GenAI applications for healthcare education.