Mediating effect of technostress on the relationship between artificial intelligence literacy and attitude toward digital technology among health profession students: a structural equation modeling approach

技术压力对卫生专业学生人工智能素养与数字技术态度之间关系的中介作用:结构方程模型方法

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Abstract

BACKGROUND: This study aimed to examine the effect of artificial intelligence (AI) literacy on attitudes toward digital technology and the mediating effect of technostress on this relationship among health profession students. METHODS: An online survey was conducted from May to October 2025 with 1,314 students enrolled in medical schools, nursing schools, dental schools, and graduate schools of dentistry nationwide. Structural equation modeling and bootstrapping analyses were performed. RESULTS: The analysis revealed that AI literacy significantly reduced technostress and enhanced attitudes toward digital technology. Technostress also had a negative effect on attitudes toward digital technology, and a partial mediating effect was identified in the relationship between AI literacy and attitudes toward digital technology. In other words, higher levels of AI literacy were associated with lower technostress, which, in turn, led to more positive attitudes toward digital technology. Multigroup analysis further showed that the effect of AI literacy on technostress differed across majors, being significant for medical and nursing students, but not for dental students. CONCLUSION: This study confirmed that improving AI literacy reduces technology-related stress and promotes positive attitudes toward digital technology. These findings suggest the need for AI and digital technology education designs that consider the psychological factors of learners in medical education. Furthermore, the observed group differences suggest that AI literacy may function differently depending on discipline-specific technological and educational contexts.

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