A Study of Orthopedic Patient Leaflets and Readability of AI-Generated Text in Foot and Ankle Surgery (SOLE-AI)

骨科患者手册及人工智能生成文本在足踝外科手术中的可读性研究 (SOLE-AI)

阅读:2

Abstract

Introduction The internet age has broadened the horizons of modern medicine, and the ever-increasing scope of artificial intelligence (AI) has made information about healthcare, common pathologies, and available treatment options much more accessible to the wider population. Patient autonomy relies on clear, accurate, and user-friendly information to give informed consent to an intervention. Our paper aims to outline the quality, readability, and accuracy of readily available information produced by AI relating to common foot and ankle procedures. Materials and methods A retrospective qualitative analysis of procedure-specific information relating to three common foot and ankle orthopedic procedures: ankle arthroscopy, ankle arthrodesis/fusion, and a gastrocnemius lengthening procedure was undertaken. Patient information leaflets (PILs) created by The British Orthopaedic Foot and Ankle Society (BOFAS) were compared to ChatGPT responses for readability, quality, and accuracy of information. Four language tools were used to assess readability: the Flesch-Kincaid reading ease (FKRE) score, the Flesch-Kincaid grade level (FKGL), the Gunning fog score (GFS), and the simple measure of gobbledygook (SMOG) index. Quality and accuracy were determined by using the DISCERN tool by five independent assessors. Results PILs produced by AI had significantly lower FKRE scores when compared to BOFAS -40.4 (SD: ±7.69) compared to 91.9 (SD: ±2.24) (p ≤ 0.0001), indicating poor readability of AI-generated text. DISCERN scoring highlighted a statistically significant improvement in accuracy and quality of human-generated information across two PILs with a mean score of 55.06 compared to 46.8. FKGL scoring indicated that the required grade of students to understand AI responses was consistently higher than compared to information leaflets at 11.7 versus 1.1 (p ≤ 0.0001). The number of years spent in education required to understand the ChatGPT-produced PILs was significantly higher in both GFS (14.46 vs. 2.0 years) (p < 0.0001) and SMOG (11.0 vs. 3.06 years) (p < 0.0001). Conclusion Despite significant advances in the implementation of AI in surgery, AI-generated PILs for common foot and ankle surgical procedures currently lack sufficient quality, depth, and readability - this risks leaving patients misinformed regarding upcoming procedures. We conclude that information from trusted professional bodies should be used to complement a clinical consultation, as there currently lacks sufficient evidence to support the routine implementation of AI-generated information into the consent process.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。