Bibliographic Details
| Title: |
Evaluating the performance of large language models in health education for patients with ankylosing spondylitis/spondyloarthritis: a cross-sectional, single-blind study in China |
| Authors: |
Yong Ren, Yuanqing Li, Jieruo Gu, Qing Lv, Wenqi Xia, Jingyu Zhang, Huifen Liu, Ya Wen, Liling Xu, Yuling Chen, Yue-ning Kang, Shuang-yan Cao, Fanxuan Meng, Ruyi Liao, Xiaomin Li, Jiayun Wu, Shenghui Wen |
| Source: |
BMJ Open, Vol 15, Iss 3 (2025) |
| Publisher Information: |
BMJ Publishing Group, 2025. |
| Publication Year: |
2025 |
| Collection: |
LCC:Medicine |
| Subject Terms: |
Medicine |
| More Details: |
Objectives To evaluate the potential of large language models (LLMs) in health education for patients with ankylosing spondylitis (AS)/spondyloarthritis (SpA), focusing on the accuracy of information transmission, patient acceptance and performance differences between different models.Design Cross-sectional, single-blind study.Setting Multiple centres in China.Participants 182 volunteers, including 4 rheumatologists and 178 patients with AS/SpA.Primary and secondary outcome measures Scientificity, precision and accessibility of the content of the answers provided by LLMs; patient acceptance of the answers.Results LLMs performed well in terms of scientificity, precision and accessibility, with ChatGPT-4o and Kimi models outperforming traditional guidelines. Most patients with AS/SpA showed a higher level of understanding and acceptance of the responses from LLMs.Conclusions LLMs have significant potential in medical knowledge transmission and patient education, making them promising tools for future medical practice. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2044-6055 |
| Relation: |
https://bmjopen.bmj.com/content/15/3/e097528.full; https://doaj.org/toc/2044-6055 |
| DOI: |
10.1136/bmjopen-2024-097528 |
| Access URL: |
https://doaj.org/article/c3f8a15833b948a093bf8cf7eef528e4 |
| Accession Number: |
edsdoj.3f8a15833b948a093bf8cf7eef528e4 |
| Database: |
Directory of Open Access Journals |
