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Abstract
This paper reports on an ongoing pilot study exploring the use of artificial intelligence (AI)-generated case studies to teach graduate nursing students about social determinants of health (SDoH) in rural and urban Texas settings. Five master of science in nursing students co-developed unfolding patient scenarios using ChatGPT and StudyCrafter, embedding clinical reasoning, empathy, and equity-focused decision-making. These simulations are currently being piloted with undergraduate students to assess feasibility, usability, and educational value. A mixed-methods design guides the evaluation. Quantitative data are collected via pre- and post-surveys to assess perceived changes in SDoH competency, while qualitative data come from student reflections and reflexive journals. Thematic analysis, conducted using Dedoose, will inform iterative refinement through faculty-student collaboration. As the study is ongoing, this paper outlines the design, methods, and theoretical framework and development of AI-enhanced, equity-focused simulations. This project offers a model for integrating SDoH into nursing curricula and preparing educators to address structural inequities.
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Article Type: Original Article
ELECTRON J GEN MED, Volume 23, Issue 1, February 2026, Article No: em707
https://doi.org/10.29333/ejgm/17634
Publication date: 01 Jan 2026
Online publication date: 23 Dec 2025
Article Views: 251
Article Downloads: 204
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