潜在医师使用基于人工智能的诊断支持系统的意愿的决定因素。
Determinants of Intention to Use Artificial Intelligence-Based Diagnosis Support System Among Prospective Physicians.
机构信息
Institute for Preventive Medicine and Public Health, Hanoi Medical University, Hanoi, Vietnam.
Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden.
出版信息
Front Public Health. 2021 Nov 26;9:755644. doi: 10.3389/fpubh.2021.755644. eCollection 2021.
This study aimed to develop a theoretical model to explore the behavioral intentions of medical students to adopt an AI-based Diagnosis Support System. This online cross-sectional survey used the unified theory of user acceptance of technology (UTAUT) to examine the intentions to use an AI-based Diagnosis Support System in 211 undergraduate medical students in Vietnam. Partial least squares (PLS) structural equational modeling was employed to assess the relationship between latent constructs. Effort expectancy (β = 0.201, < 0.05) and social influence (β = 0.574, < 0.05) were positively associated with initial trust, while no association was found between performance expectancy and initial trust ( > 0.05). Only social influence (β = 0.527, < 0.05) was positively related to the behavioral intention. This study highlights positive behavioral intentions in using an AI-based diagnosis support system among prospective Vietnamese physicians, as well as the effect of social influence on this choice. The development of AI-based competent curricula should be considered when reforming medical education in Vietnam.
本研究旨在构建一个理论模型,以探讨医学生采用人工智能(AI)辅助诊断系统的行为意向。本在线横断面调查采用统一技术接受模型(UTAUT),对越南 211 名本科医学生使用 AI 辅助诊断系统的意向进行了评估。偏最小二乘法(PLS)结构方程模型用于评估潜在结构之间的关系。努力期望(β=0.201,<0.05)和社会影响(β=0.574,<0.05)与初始信任呈正相关,而绩效期望与初始信任之间无相关性(>0.05)。仅社会影响(β=0.527,<0.05)与行为意向呈正相关。本研究强调了越南未来医生使用 AI 辅助诊断系统的积极行为意向,以及社会影响对这一选择的影响。在越南进行医学教育改革时,应考虑开发基于 AI 的胜任力课程。