Using artificial intelligence to create case studies addressing social determinants in graduate nursing education

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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