School of Economic and Management, Anhui University of Science and Technology, Huainan 232001, China.
Int J Environ Res Public Health. 2022 Oct 15;19(20):13311. doi: 10.3390/ijerph192013311.
Artificial intelligence (AI)-assisted diagnosis and treatment could expand the medical scenarios and augment work efficiency and accuracy. However, factors influencing healthcare workers' adoption intention of AI-assisted diagnosis and treatment are not well-understood. This study conducted a cross-sectional study of 343 dental healthcare workers from tertiary hospitals and secondary hospitals in Anhui Province. The obtained data were analyzed using structural equation modeling. The results showed that performance expectancy and effort expectancy were both positively related to healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Social influence and human-computer trust, respectively, mediated the relationship between expectancy (performance expectancy and effort expectancy) and healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Furthermore, social influence and human-computer trust played a chain mediation role between expectancy and healthcare workers' adoption intention of AI-assisted diagnosis and treatment. Our study provided novel insights into the path mechanism of healthcare workers' adoption intention of AI-assisted diagnosis and treatment.
人工智能（AI）辅助诊断和治疗可以拓展医疗场景，提高工作效率和准确性。然而，影响医疗工作者采用 AI 辅助诊断和治疗意愿的因素尚不清楚。本研究对安徽省 343 名来自三级医院和二级医院的牙科医疗工作者进行了横断面研究。使用结构方程模型对获得的数据进行了分析。结果表明，绩效期望和努力期望均与医疗工作者采用 AI 辅助诊断和治疗的意愿呈正相关。社会影响和人机信任分别在期望（绩效期望和努力期望）与医疗工作者采用 AI 辅助诊断和治疗的意愿之间起到中介作用。此外，期望与医疗工作者采用 AI 辅助诊断和治疗的意愿之间存在社会影响和人机信任的链式中介作用。本研究为医疗工作者采用 AI 辅助诊断和治疗的意愿路径机制提供了新的见解。
