Determinants of Intention to Use Artificial Intelligence-Based Diagnosis Support System Among Prospective Physicians - Tran, Anh Quynh; Nguyen, Long Hoang; Nguyen, Hao Si Anh; Nguyen, Cuong Tat; Vu, Linh Gia; Zhang, Melvyn; Vu, Thuc Minh Thi; Nguyen, Son Hoang; Tran, Bach Xuan; Latkin, Carl A.; Ho, Roger C. M.; Ho, Cyrus S. H. (Frontiers in Public Health, 2021)
Background: This study aimed to develop a theoretical model to explore the behavioral intentions of medical students to adopt an AI-based Diagnosis Support System. Methods: 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. Results: Effort expectancy (β=0.201, p<0.05) and social influence (β=0.574, p<0.05) were positively associated with initial trust, while no association was found between performance expectancy and initial trust (p>0.05). Only social influence (β=0.527, p<0.05) was positively related to the behavioral intention. Conclusions: 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