{"title":"The Usability of Neurological Occupational Therapy Case Studies Generated by ChatGPT.","authors":"Si-An Lee, Jin-Hyuck Park","doi":"10.3390/healthcare13111341","DOIUrl":null,"url":null,"abstract":"<p><p><b>Background/Objectives</b>: Case-based learning is essential in occupational therapy education, but developing standardized cases requires significant resources. This study explores the usability of AI-generated case studies using ChatGPT. <b>Methods</b>: A four-stage process was applied: (1) prompt development based on existing frameworks, (2) case generation ensuring diversity and relevance, (3) expert evaluation using a 5-point Likert scale, and (4) data analysis. Five neurological cases were generated and reviewed by ten experts. <b>Results</b>: Experts rated the cases highly in clinical realism (4.22/5), information comprehensiveness (4.56/5), and educational value (4.44/5). The AI-generated cases successfully provided structured occupational therapy scenarios, assessment results, and clinical questions. <b>Conclusions</b>: Five AI-generated occupational therapy cases were developed and reviewed by occupational therapy experts to evaluate their clinical realism, comprehensiveness, and educational value. While expert feedback was favorable, the effectiveness of these cases for student learning has not yet been empirically tested.</p>","PeriodicalId":12977,"journal":{"name":"Healthcare","volume":"13 11","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12155196/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Healthcare","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3390/healthcare13111341","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Background/Objectives: Case-based learning is essential in occupational therapy education, but developing standardized cases requires significant resources. This study explores the usability of AI-generated case studies using ChatGPT. Methods: A four-stage process was applied: (1) prompt development based on existing frameworks, (2) case generation ensuring diversity and relevance, (3) expert evaluation using a 5-point Likert scale, and (4) data analysis. Five neurological cases were generated and reviewed by ten experts. Results: Experts rated the cases highly in clinical realism (4.22/5), information comprehensiveness (4.56/5), and educational value (4.44/5). The AI-generated cases successfully provided structured occupational therapy scenarios, assessment results, and clinical questions. Conclusions: Five AI-generated occupational therapy cases were developed and reviewed by occupational therapy experts to evaluate their clinical realism, comprehensiveness, and educational value. While expert feedback was favorable, the effectiveness of these cases for student learning has not yet been empirically tested.
期刊介绍:
Healthcare (ISSN 2227-9032) is an international, peer-reviewed, open access journal (free for readers), which publishes original theoretical and empirical work in the interdisciplinary area of all aspects of medicine and health care research. Healthcare publishes Original Research Articles, Reviews, Case Reports, Research Notes and Short Communications. We encourage researchers to publish their experimental and theoretical results in as much detail as possible. For theoretical papers, full details of proofs must be provided so that the results can be checked; for experimental papers, full experimental details must be provided so that the results can be reproduced. Additionally, electronic files or software regarding the full details of the calculations, experimental procedure, etc., can be deposited along with the publication as “Supplementary Material”.