Artificial Intelligence Anxiety in Nursing Students: The Impact of Self-efficacy.

Abstract

As in many other sectors, artificial intelligence has an impact on health. Artificial intelligence anxiety may occur because of a lack of knowledge about the effects of artificial intelligence, its outcomes, and how it will be used, as well as potential labor concerns. This study aims to determine the artificial intelligence anxiety levels of nursing students and examine whether there is a relationship with their self-efficacy levels. This cross-sectional study, conducted at a public nursing school in Turkey, involved 317 nursing students. Data were collected using a personal information form, the General Self-efficacy Scale, and the Artificial Intelligence Anxiety Scale. There was a negative, moderately strong correlation between the General Self-efficacy Scale and the learning subdimension ( r = -0.369) and the Artificial Intelligence Anxiety Scale ( r = -0.313) and a weak negative correlation between the job replacement subdimension ( r = -0.215), sociotechnical blindness subdimension ( r = -0.232), and artificial intelligence configuration subdimension ( r = -0.211). The General Self-efficacy Scale has a significant negative effect on the Artificial Intelligence Anxiety Scale ( β = -.313, t = -5.845, P < .05). These findings suggest that higher self-efficacy is associated with lower artificial intelligence anxiety. It is recommended to enhance technical competence and self-efficacy in nursing education.