ArticleActa obstetricia et gynecologica Scandinavica2026
ChatGPT in urogynecology: Comparing large language model responses to human experts.
Article in Acta obstetricia et gynecologica Scandinavica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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.
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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.
- Patient education materials by ChatGPT: Real intention and interpretation.Acta obstetricia et gynecologica Scandinavica · 2026Article
- Aligning AI and clinical expertise: A collaborative path for patient education.Acta obstetricia et gynecologica Scandinavica · 2026Article
- Applications, Challenges, and Future Directions of Large Language Models in Health Care Communication: Scoping Review.Journal of medical Internet research · 2026Article
- Artificial Intelligence in Patient Education: A Clinical Reflection : (Comment on "Development and Evaluation of an Augmented Artificial Intelligence Model for Urogynecology Queries").International urogynecology journal · 2026Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionLarge language models (LLMs) are increasingly used in healthcare, including urogynecology, where stigma may limit open discussion. LLM-based chat platforms may provide a less intimidating and more accessible way for patients to obtain information, but their reliability requires evaluation. This study compared the quality of ChatGPT-generated responses in urogynecology with those provided by a consultant urogynecologist, focusing on understandability, helpfulness, and reassurance. MATERIAL AND
methodsA cross-sectional survey was conducted among urogynecology patients. After informed consent, participants reviewed responses to six common questions, each answered by ChatGPT and a single consultant. A blinded third-party consultant verified clinical accuracy. Patients rated responses using a 5-point Likert scale across three domains (maximum score 15 per response). Wilcoxon signed-rank tests were used for comparison.
resultsA total of 203 patients participated (median age 56 years, interquartile range 46-66). ChatGPT responses received higher total ratings than consultant responses (76 [67-85] vs. 72 [63-80], p < 0.01). Scores were higher for understandability, helpfulness, and reassurance (all p < 0.01). ChatGPT was preferred in four of six questions, one showed no difference, and one favored the consultant. Subgroup analyses showed no significant variation based on patient characteristics.
conclusionsIn this exploratory study, women rated ChatGPT's responses as clearer and more reassuring than consultant answers. These findings reflect patient perceptions in a limited setting and should be interpreted with caution. While LLMs may have a supportive role in patient education, their use must remain secondary to expert clinical care and subject to careful oversight.
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Registered trials
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