Trial reportJMIR medical education2025
Evaluating ChatGPT-4o as an Educational Support Tool for the Emergency Management of Dental Trauma: Randomized Controlled Study Among Students.
Trial report in JMIR medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The impact of generative artificial intelligence on clinical skills and knowledge acquisition in medical undergraduates: a systematic review and meta-analysis.BMC medical education · 2026Pooled it
- ChatGPT in Pediatric Dental Trauma: A Cross-Sectional Assessment of Response Reliability to Parental Queries.Cureus · 2026Article
- Effects of Artificial Intelligence-Supported Education on Critical Thinking, Problem-Solving, Clinical Reasoning, and Decision-Making in Health Science Education: A Systematic Review of Interventional Studies.Advances in medical education and practice · 2026Review
- AI-enabled language technologies for language-mediated learning and clinical communication in international undergraduate dental education: a scoping review.Frontiers in medicine · 2026Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDigital tools are increasingly used to support clinical decision-making in dental education. However, the accuracy and efficiency of different support tools, including generative artificial intelligence, in the context of dental trauma management remain underexplored.
objectiveThis study aimed to evaluate the accuracy of various information sources (chatbot, textbook, mobile app, and no support tool) in conveying clinically relevant educational content related to decision-making in the primary care of traumatically injured teeth. Additionally, the effect of the input strategy on the chatbot's output response was evaluated.
methodsFifty-nine dental students with limited prior experience in dental trauma were randomly assigned to one of 4 groups: chatbot (based on generative pretrained transformer [GPT]-4o, n=15), digital textbook (n=15), mobile app (AcciDent app 3.5, n=15), and control group (no support tool, n=14). Participants answered 25 dichotomous questions in a digital examination format using the information source allocated to their group. The primary outcome measures were the percentage of correct responses and the time required to complete the examination. Additionally, for the group using ChatGPT-4o, the quality of prompts and the clarity of chatbot responses were independently evaluated by 2 calibrated examiners using a 5-point Likert scale. Statistical analyses included nonparametric analyses using Kruskal-Wallis tests and mixed-effects regression analyses with an α level of .05.
resultsAll support tools led to a significantly higher accuracy compared with the control group (P<.05), with mean accuracies of 87.47% (SD 5.63%), 86.40% (SD 5.19%), and 86.40% (SD 6.38%) for the textbook, the AcciDent app, and ChatGPT-4o, respectively. The groups using the chatbot and the mobile app required significantly less time than the textbook group (P<.05). Within the ChatGPT-4o group, higher prompt quality was associated with greater clarity of the chatbot's responses (odds ratio 1.44, 95% CI 1.13-1.83, P<.05), which in turn increased the likelihood of students selecting the correct answers (odds ratio 1.89, 95% CI 1.26-2.80, P<.05).
conclusionsChatGPT-4o and the AcciDent app can serve dental students as an accurate and time-efficient support tool in dental trauma care. However, the performance of ChatGPT-4o varies with the precision of the input prompt, underscoring the necessity for users to critically evaluate artificial intelligence-generated responses.
trial registrationOSF Registries 10.17605/OSF.IO/XW62J; https://osf.io/xw62j/overview.
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