Using artificial intelligence to create case studies addressing social determinants in graduate nursing education.
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 pat...
| Publicado en: | Electronic Journal of General Medicine Vol. 23; no. 1; pp. 1 - 8 |
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| Autores principales: | , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Modestum Publications
Feb2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=191820202&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 191820202 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 25163507 LNCB jtl: Electronic Journal of General Medicine issn: 25163507 maglogo: N pubinfo: dt: Feb2026 vid: 23 iid: 1 pid: 52459 pub: Modestum Publications place: , <Blank> artinfo: ui: 191820202 191820202 191820202 10.29333/ejgm/17634 191820202 ppf: 1 ppct: 7 formats: tig: atl: Using artificial intelligence to create case studies addressing social determinants in graduate nursing education. aug: au: Alexander, Karen Elaine Mathews, Nisha Sutherland, Steven Joseph, Jolly Holmes, Katecia Sims, Madison affil: University of Houston-Clear Lake, Houston, TX, USA sug: subj: Artificial Intelligence Utilization Case Studies Learning Methods Social Determinants of Health Education, Nursing, Graduate Students, Nursing, Graduate Psychosocial Factors Rural Areas Texas Urban Areas Texas Human Texas Male Female Registered Nurses Pilot Studies Chatbot Clinical Reasoning Empathy Decision Making Simulations Multimethod Studies Pretest-Posttest Design Reflection Thematic Analysis Collaboration Faculty-Student Relations Experimental Studies Male Female ab: 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. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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