软件部署
技术接受模型
领域(数学)
医学教育
临床实习
心理学
医学
家庭医学
计算机科学
可用性
数学
人机交互
操作系统
纯数学
作者
Peter J. Schulz,May O. Lwin,Kalya M. Kee,Wilson Wen Bin Goh,Thomas Y. Lam,Joseph J.�Y. Sung
标识
DOI:10.3389/fpubh.2023.1301563
摘要
Introduction The potential for deployment of Artificial Intelligence (AI) technologies in various fields of medicine is vast, yet acceptance of AI amongst clinicians has been patchy. This research therefore examines the role of antecedents, namely trust, attitude, and beliefs in driving AI acceptance in clinical practice. Methods We utilized online surveys to gather data from clinicians in the field of gastroenterology. Results A total of 164 participants responded to the survey. Participants had a mean age of 44.49 (SD = 9.65). Most participants were male ( n = 116, 70.30%) and specialized in gastroenterology ( n = 153, 92.73%). Based on the results collected, we proposed and tested a model of AI acceptance in medical practice. Our findings showed that while the proposed drivers had a positive impact on AI tools’ acceptance, not all effects were direct. Trust and belief were found to fully mediate the effects of attitude on AI acceptance by clinicians. Discussion The role of trust and beliefs as primary mediators of the acceptance of AI in medical practice suggest that these should be areas of focus in AI education, engagement and training. This has implications for how AI systems can gain greater clinician acceptance to engender greater trust and adoption amongst public health systems and professional networks which in turn would impact how populations interface with AI. Implications for policy and practice, as well as future research in this nascent field, are discussed.
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