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2
Triggering, clicking, locking and crepitus of the finger: A comprehensive overview.手指的触发、弹响、卡顿及摩擦音:全面概述
World J Orthop. 2023 Oct 18;14(10):733-740. doi: 10.5312/wjo.v14.i10.733.
3
How Efficient Is ChatGPT in Accessing Accurate and Quality Health-Related Information?ChatGPT在获取准确且高质量的健康相关信息方面效率如何?
Cureus. 2023 Oct 7;15(10):e46662. doi: 10.7759/cureus.46662. eCollection 2023 Oct.
4
Using ChatGPT to evaluate cancer myths and misconceptions: artificial intelligence and cancer information.利用 ChatGPT 评估癌症谣言和误解:人工智能与癌症信息。
JNCI Cancer Spectr. 2023 Mar 1;7(2). doi: 10.1093/jncics/pkad015.
5
Evaluation of the Quality of Information Available on the Internet Regarding Chronic Ankle Instability.互联网上关于慢性踝关节不稳定信息质量的评估。
Medicina (Kaunas). 2022 Sep 20;58(10):1315. doi: 10.3390/medicina58101315.
6
Current Concepts in the Management of Advanced Trigger Finger: A Critical Analysis Review.当前先进扳机指管理理念:批判性分析综述。
JBJS Rev. 2021 Sep 9;9(9):01874474-202109000-00002. doi: e21.00006.
7
Platelet-rich plasma versus corticosteroid injection for treatment of trigger finger: study protocol for a prospective randomized triple-blind placebo-controlled trial.富血小板血浆与皮质类固醇注射治疗扳机指:前瞻性随机三盲安慰剂对照试验研究方案。
Trials. 2020 Nov 27;21(1):984. doi: 10.1186/s13063-020-04907-w.
8
Physical modalities for the conservative treatment of wrist and hand's tenosynovitis: A systematic review.物理疗法治疗腕和手部腱鞘炎:系统评价。
Semin Arthritis Rheum. 2020 Dec;50(6):1280-1290. doi: 10.1016/j.semarthrit.2020.08.006. Epub 2020 Aug 29.
9
DISCERN: an instrument for judging the quality of written consumer health information on treatment choices.DISCERN:一种用于评判关于治疗选择的书面消费者健康信息质量的工具。
J Epidemiol Community Health. 1999 Feb;53(2):105-11. doi: 10.1136/jech.53.2.105.

评估ChatGPT对扳机指治疗常见问题的回答质量。

Assessing the quality of ChatGPT's responses to commonly asked questions about trigger finger treatment.

作者信息

Gezer Mehmet Can, Armangil Mehmet

机构信息

Department of Orthopedics and Traumatology, Mamak State Hospital, Ankara-Türkiye.

Department of Orthopedics and Traumatology, Hand Surgery Unit, Ankara University Faculty of Medicine, Ankara-Türkiye.

出版信息

Ulus Travma Acil Cerrahi Derg. 2025 Apr;31(4):389-393. doi: 10.14744/tjtes.2025.32735.

DOI:10.14744/tjtes.2025.32735
PMID:40211643
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12000978/
Abstract

BACKGROUND

This study aims to evaluate the accuracy and reliability of Generative Pre-trained Transformer (ChatGPT; OpenAI, San Francisco, California) in answering patient-related questions about trigger finger. This evaluation has the potential to enhance patient education prior to treatment and provides insight into the role of artificial intelligence (AI)-based systems in the patient educa-tion process.

METHODS

The ten most frequently asked questions regarding trigger finger were compiled from patient education websites and a literature review, then posed to ChatGPT. Two orthopedic specialists evaluated the responses using the Journal of the American Medical Association (JAMA) Benchmark criteria and the DISCERN instrument (A Tool for Judging the Quality of Written Consumer Health Information on Treatment Choices). Additionally, the readability of the responses was assessed using the Flesch-Kincaid Grade Level.

RESULTS

The DISCERN scores for ChatGPT's responses to trigger finger questions ranged from 35 to 47, with an average of 42, indicating "moderate" quality. While 60% of the responses were satisfactory, 40% contained deficiencies. According to the JAMA Benchmark criteria, the absence of scientific references was a significant drawback. The average readability level corresponded to the university level, making the information difficult to understand for patients with low health literacy. Improvements are needed to enhance the accessibility and comprehensibility of the content for a broader patient population.

CONCLUSION

To the best of our knowledge, this is the first study to investigate the use of ChatGPT in the context of trigger finger. While ChatGPT shows reasonable effectiveness in providing general information on trigger finger, expert oversight is necessary before it can be relied upon as a primary source for patient education.

摘要

背景

本研究旨在评估生成式预训练变换器(ChatGPT;OpenAI,加利福尼亚州旧金山)在回答有关扳机指的患者相关问题时的准确性和可靠性。该评估有可能在治疗前加强患者教育,并深入了解基于人工智能(AI)的系统在患者教育过程中的作用。

方法

从患者教育网站和文献综述中整理出关于扳机指的十个最常见问题,然后向ChatGPT提问。两名骨科专家使用《美国医学会杂志》(JAMA)基准标准和DISCERN工具(一种判断书面消费者健康信息治疗选择质量的工具)对回答进行评估。此外,使用弗莱什-金凯德年级水平评估回答的可读性。

结果

ChatGPT对扳机指问题回答的DISCERN分数在35至47之间,平均为42,表明质量为“中等”。虽然60%的回答令人满意,但40%存在缺陷。根据JAMA基准标准,缺乏科学参考文献是一个重大缺陷。平均可读性水平相当于大学水平,这使得健康素养较低的患者难以理解这些信息。需要改进以提高内容对更广泛患者群体的可及性和可理解性。

结论

据我们所知,这是第一项在扳机指背景下研究ChatGPT使用情况的研究。虽然ChatGPT在提供关于扳机指的一般信息方面显示出合理的有效性,但在将其作为患者教育的主要来源之前,需要专家监督。