广东省基层医生对人工智能辅助诊疗技术的应用意愿分析

目的 探讨广东省基层医生对人工智能（artificial intelligence,AI）辅助诊疗技术的应用意愿及其影响因素。方法 采用方便抽样方法选取广东省的基层医生为研究对象，对其人口学特征以及AI辅助诊疗技术应用意愿进行问卷调查。拟合结构方程模型分析基层医生对AI辅助诊疗技术应用意愿的影响因素。结果 纳入广东省基层医生3 490名，平均年龄（32.99±15.89）岁，男性1 815名（52.01%）。基层医生支持AI辅助诊疗技术服务患者、认为AI可促进医疗技术进步和高精尖医疗技术普及、愿意尝试使用或继续使用AI辅助诊疗技术为患者提供服务的同意率分别为82.15%、78.83%、78.45%。结构方程模型结果显示，感知有用性、感知满意度、感知服务质量、感知信息质量以及较高学历对基层医生应用AI辅助诊疗技术产生正向影响，标化路径系数分别为0.354、0.268、0.121、0.270、0.035(P<0.05或P<0.01)；较高职称对基层医生应用AI辅助诊疗技术产生负向影响，标化路径系数为-0.045(P<0.01)。结论 广东省基层医生对AI辅助诊疗技术的应用...

Application willingness of artificial intelligence-assisted diagnosis and treatment technology among primary care physicians in Guangdong Province

Objective To explore the application willingness of artificial intelligence （AI）-assisted diagnosis and treatment technology and its influencing factors among primary care physicians in Guangdong Province. Methods Primary care physicians in Guangdong Province were selected by convenient sampling method to conduct a questionnaire survey on their demographic characteristics and willingness to apply AI-assisted diagnosis and treatment technology. The structural equation modeling was fitted to analyze the influencing factors of primary care physicians' willingness to apply AI-assisted diagnosis and treatment technology. Results A total of 3 490 primary care physicians from Guangdong Province were included, with an average age of （32.99±15.89） years, and 1 815 were male （52.01%）. The consent rates of primary care physicians who supported AI-assisted diagnosis and treatment technology to serve patients, believed that AI could promote the progress of medical technology and the popularization of advanced and sophisticated medical technology, and were willing to try or continue to use AI-assisted diagnosis and treatment technology to provide services for patients was 82.15%, 78.83%, and 78.45% respectively. The results of structural equation modeling showed that perceived usefulness, perceived satisfaction, perceived service quality, perceived information quality, and a higher education level had a positive impact on the willingness of primary care physicians to apply AI-assisted diagnosis and treatment technology, and the standardized path coefficients were 0.354, 0.268, 0.121, 0.270, and 0.035 respectively （P<0.05 or P<0.01）. The higher professional title had a negative impact on the willingness of primary care physicians to apply AI-assisted diagnosis and treatment technology, and the standardized path coefficient was -0.045 （P<0.01）. Conclusions Primary care physicians' willingness to apply AI-assisted diagnosis and treatment technology is generally high in Guangdong Province. Perceived usefulness, perceived satisfaction, perceived information quality, perceived service quality, education level, and professional title are the influencing factors of primary care physicians' willingness to apply AI-assisted diagnosis and treatment technology.