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
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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.

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The Future of Generative AI in Continuing Professional Development (CPD): Crowdsourcing the Alliance Community. Unravelling Orthopaedic Surgeons' Perceptions and Adoption of Generative AI Technologies. An Overview of Continuing Medical Education/Continuing Professional Development Systems in the Middle East and North Africa: A Mixed Methods Assessment. Revolutionising Faculty Development and Continuing Medical Education Through AI-Generated Videos. An Overview of Continuing Medical Education/Continuing Professional Development Systems in Europe: A Mixed Methods Assessment.
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