ArticleDigital health
Safety and user perception of general-purpose large language models in pediatric healthcare: Evaluations of ChatGPT by doctors and parents.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Large Language Model and Pediatric Neurosurgery - A Neurosurgeon's Perspective on the Artificial Nervous System.Journal of Korean Neurosurgical Society · 2026Article
- Performance of ChatGPT-4o in Providing Information on Pediatric Inborn Errors of Immunity: A Cross-Sectional Evaluation.Journal of clinical medicine · 2026Article
- Generative AI use and social disparities in pediatric rehabilitation: a cross-sectional study of ChatGPT use among parents of children with speech and language disorders in Türkiye.Frontiers in public health · 2026Article
- Cross-sectional comparative evaluation of five large language model-driven chatbots on an expert-curated 44-question set of parent-facing questions about pediatric vitamin D deficiency.Frontiers in pediatrics · 2026Article
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background/Objective: Although the internet has broadened access to medical resources, concerns persist regarding the quality and accuracy of available content. ChatGPT, a general-purpose large language model, may help bridge this gap. This study evaluates its safety and user perception in addressing pediatric healthcare queries. Methods: Nine experts independently evaluated 41 questions, with three experts assigned to each of the following topics: vitamin D (15 questions), food allergies (16 questions), and sleep problems (10 questions). Each question was answered separately by ChatGPT3.5 and ChatGPT4. Ratings were determined by expert consensus or, in cases of disagreement, the lowest rating. Additionally, 27 parents evaluated ChatGPT's responses. Results: Experts rated 73.2% of responses from ChatGPT3.5 as "completely correct" or "correct but not comprehensive," while 26.8% were rated as "partially incorrect" or "completely incorrect." For ChatGPT4, these figures were 68.3% and 31.7%, respectively. The difference in accuracy ratings between the two versions was not statistically significant (chi-square test, Conclusion: As over a quarter of responses contained expert-identified inaccuracies, the current performance of ChatGPT is insufficient for safe and reliable use in clinical decision-making. Nevertheless, it has potential to expand health information access for parents. However, these findings should be interpreted with caution given the small sample size and potential selection bias regarding parents' educational backgrounds. Future improvements should enhance accuracy, clarity, and integration between parents and healthcare professionals.
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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.