ArticleArchives of academic emergency medicine2025
Effectiveness of ChatGPT for Clinical Scenario Generation: A Qualitative Study.
Article in Archives of academic emergency medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Educational Applications of AI-Based Chatbots in Nursing: A Scoping Review.Nursing reports (Pavia, Italy) · 2026Review
- Large language models in emergency medicine education: opportunities, challenges, and implementation pathways.Frontiers in public health · 2026Review
- An Evaluation Framework for Large Language Models in Clinical Nursing: A Scoping Review and Expert Consultation.Journal of nursing management · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: A growing area is the use of ChatGPT in simulation-based learning, a widely recognized methodology in medical education. This study aimed to evaluate ChatGPT's ability to generate realistic simulation scenarios to assist faculty as a significant challenge in medical education. Method: This study employs a qualitative research design and thematic analysis to interpret expert opinions Results: The clinical scenarios were produced by ChatGPT in less than 5 seconds per case. The thematic analysis identified six recurring themes in the experts' discussions: clinical accuracy, the clarity of learning objectives, the logical flow of patient cases, realism and feasibility, alignment with nursing competencies, and level of difficulty. All the experts agreed that the scenarios were realistic and followed clinical guidelines. However, they also identified several errors and areas that needed improvement. The experts identified and documented specific errors, incorrect recommendations, missing information, and inconsistencies with standard nursing practices. Conclusion: It seems that, ChatGPT can be a valuable tool for developing clinical scenarios, but expert review and refinement are necessary to ensure the accuracy and alignment of the generated scenarios with clinical and educational standards.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.