Unravelling Orthopaedic Surgeons' Perceptions and Adoption of Generative AI Technologies.

Journal of CME Pub Date : 2024-12-09 eCollection Date: 2024-01-01 DOI:10.1080/28338073.2024.2437330
Matthias Schmidt, Yasmin B Kafai, Adrian Heinze, Monica Ghidinelli
{"title":"Unravelling Orthopaedic Surgeons' Perceptions and Adoption of Generative AI Technologies.","authors":"Matthias Schmidt, Yasmin B Kafai, Adrian Heinze, Monica Ghidinelli","doi":"10.1080/28338073.2024.2437330","DOIUrl":null,"url":null,"abstract":"<p><p>This mixed-methods study investigates the adoption of generative AI among orthopaedic surgeons, employing a Unified Theory of Acceptance and Use of Technology (UTAUT) based survey (<i>n</i> = 177) and follow-up interviews (<i>n</i> = 7). The research reveals varying levels of AI familiarity and usage patterns, with higher adoption in research and professional development compared to direct patient care. A significant generational divide in perceived ease of use highlights the need for tailored training approaches. Qualitative insights uncover barriers to adoption, including the need for more evidence-based support, as well as concerns about maintaining critical thinking skills. The study exposes a complex interplay of individual, technological, and organisational factors influencing AI adoption in orthopaedic surgery. The findings underscore the need for a nuanced approach to AI integration that considers the unique aspects of orthopaedic surgery and the diverse perspectives of surgeons at different career stages. This provides valuable insights for educational institutions and healthcare organisations in navigating the challenges and opportunities of AI adoption in specialised medical fields.</p>","PeriodicalId":73675,"journal":{"name":"Journal of CME","volume":"13 1","pages":"2437330"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11632920/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of CME","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/28338073.2024.2437330","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This mixed-methods study investigates the adoption of generative AI among orthopaedic surgeons, employing a Unified Theory of Acceptance and Use of Technology (UTAUT) based survey (n = 177) and follow-up interviews (n = 7). The research reveals varying levels of AI familiarity and usage patterns, with higher adoption in research and professional development compared to direct patient care. A significant generational divide in perceived ease of use highlights the need for tailored training approaches. Qualitative insights uncover barriers to adoption, including the need for more evidence-based support, as well as concerns about maintaining critical thinking skills. The study exposes a complex interplay of individual, technological, and organisational factors influencing AI adoption in orthopaedic surgery. The findings underscore the need for a nuanced approach to AI integration that considers the unique aspects of orthopaedic surgery and the diverse perspectives of surgeons at different career stages. This provides valuable insights for educational institutions and healthcare organisations in navigating the challenges and opportunities of AI adoption in specialised medical fields.

揭示骨科医生对生成人工智能技术的看法和采用。
这项混合方法研究调查了骨科医生对生成式人工智能的采用情况,采用了基于技术接受和使用统一理论(UTAUT)的调查(n = 177)和随访访谈(n = 7)。该研究揭示了不同程度的人工智能熟悉度和使用模式,与直接患者护理相比,在研究和专业发展中采用的人工智能更高。在易用性方面存在明显的代际差异,这突出了量身定制培训方法的必要性。定性洞察揭示了采用的障碍,包括需要更多基于证据的支持,以及对保持批判性思维技能的关注。该研究揭示了影响人工智能在骨科手术中应用的个人、技术和组织因素之间复杂的相互作用。研究结果强调,需要一种细致入微的人工智能集成方法,考虑到骨科手术的独特方面和不同职业阶段外科医生的不同观点。这为教育机构和医疗机构在应对专业医疗领域采用人工智能的挑战和机遇方面提供了宝贵的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信