ArticleJournal of educational evaluation for health professions2023
Comparing ChatGPT’s ability to rate the degree of stereotypes and the consistency of stereotype attribution with those of medical students in New Zealand in developing a similarity rating test: a methodological study.
Article in Journal of educational evaluation for health professions, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Review
- ChatGPT and Other Large Language Models in Medical Education - Scoping Literature Review.Medical science educator · 2025Review
- Efficacy and limitations of ChatGPT as a biostatistical problem-solving tool in medical education in Serbia: a descriptive studyJournal of educational evaluation for health professions · 2023Article
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Authors and funding
3 authors.
Funding
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Abstract
Learning about one’s implicit bias is crucial for improving one’s cultural competency and thereby reducing health inequity. To evaluate bias among medical students following a previously developed cultural training program targeting New Zealand Māori, we developed a text-based, self-evaluation tool called the Similarity Rating Test (SRT). The development process of the SRT was resource-intensive, limiting its generalizability and applicability. Here, we explored the potential of ChatGPT, an automated chatbot, to assist in the development process of the SRT by comparing ChatGPT’s and students’ evaluations of the SRT. Despite results showing non-significant equivalence and difference between ChatGPT’s and students’ ratings, ChatGPT’s ratings were more consistent than students’ ratings. The consistency rate was higher for non-stereotypical than for stereotypical statements, regardless of rater type. Further studies are warranted to validate ChatGPT’s potential for assisting in SRT development for implementation in medical education and evaluation of ethnic stereotypes and related topics.
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