Home PublicationsCV

Adi Weintraub

Senior Academic

ChatGPT in urogynecology

Comparing large language model responses to human experts

Reut Rotem, Craven Simon, Misgav Rottenstreich, Barry A. O'reilly, Adi Y. Weintraub, Orfhlaith E. O'Sullivan

Introduction: Large 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 Methods: A 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. Results: A 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. Conclusions: In 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.

Publication language English
Pages 1629-1635
Journal Acta Obstetricia et Gynecologica Scandinavica
Volume 105
Issue number 8
Publication status Published - 01.08.2026

Keywords

Urogynecology
artificial intelligence
decision-making
natural language processing
patient education

ASJC Scopus subject areas

Obstetrics and Gynecology
Access to Document
10.1111/aogs.70085
Other files and links
Link to publication in Scopus