Radiology Residents’ Perceptions of Artificial Intelligence: Nationwide Cross-Sectional Survey Study

作者：Yanhua Chen, Ziye Wu, Peicheng Wang, Linbo Xie, Mengsha Yan, Maoqing Jiang, Zhenghan Yang, Jianjun Zheng, Jingfeng Zhang, Jiming Zhu · 发表于：Journal of Medical Internet Research · 年份：2023 · DOI：10.2196/48249 · 被引用次数：53 · 研究领域：Artificial Intelligence in Healthcare and Education、Ethics and Social Impacts of AI、Radiology practices and education

BACKGROUND: Artificial intelligence (AI) is transforming various fields, with health care, especially diagnostic specialties such as radiology, being a key but controversial battleground. However, there is limited research systematically examining the response of "human intelligence" to AI. OBJECTIVE: This study aims to comprehend radiologists' perceptions regarding AI, including their views on its potential to replace them, its usefulness, and their willingness to accept it. We examine the influence of various factors, encompassing demographic characteristics, working status, psychosocial aspects, personal experience, and contextual factors. METHODS: Between December 1, 2020, and April 30, 2021, a cross-sectional survey was completed by 3666 radiology residents in China. We used multivariable logistic regression models to examine factors and associations, reporting odds ratios (ORs) and 95% CIs. RESULTS: In summary, radiology residents generally hold a positive attitude toward AI, with 29.90% (1096/3666) agreeing that AI may reduce the demand for radiologists, 72.80% (2669/3666) believing AI improves disease diagnosis, and 78.18% (2866/3666) feeling that radiologists should embrace AI. Several associated factors, including age, gender, education, region, eye strain, working hours, time spent on medical images, resilience, burnout, AI experience, and perceptions of residency support and stress, significantly influence AI attitudes. For instance, burnout symptoms were associat...