JMIR Publications

ABSTRACT

Background:

Enhancing nursing students' awareness, attitudes, beliefs, and preparedness toward artificial intelligence (AI) may help improve their healthcare knowledge and practice. Objectives: This study aimed to assess nursing students' attitudes, perceptions, self-efficacy, barriers, and anxiety that influence their readiness to adopt AI in nursing practice.

Objective:

This study aimed to assess nursing students' attitudes, perceptions, self-efficacy, barriers, and anxiety that influence their readiness to adopt AI in nursing practice.

Methods:

This study used a cross-sectional correlational design. Data were collected from 307 nursing internship students using an eight-part, self-administered questionnaire.

Results:

Increased self-efficacy with computers correlated with decreased barriers to accessing AI technology, lower computer anxiety scale scores (r=−0.27, p<0.001 and r=−0.568, p<0.001, respectively), and higher perceptions of using AI (r=0.27, p<0.001). Meanwhile, nursing students’ readiness to adopt AI in nursing practice was associated with decreased barriers to accessing AI technology and a more positive attitude toward and perception of using AI (r=−0.20, p<0.001; r=−0.32, p<0.001; r=0.14, p=0.011, respectively). Increased barriers to accessing AI technology were associated with negative attitudes toward AI and nursing students' perceptions of using AI (r=−0.34, p<0.001; r=−0.39, p<0.001, respectively). A multilayer neural network model demonstrated strong predictive performance, as indicated by a training sum of squares error of 65.93% and a relative error of 0.62%. The generalization ability of the model was supported by a test sum of squares error of 35.49%. Importantly, the model identified barriers (β = 0.27), attitudes (β = 0.16), and perceptions (β = 0.15) as the most significant predictors, while self-efficacy (β = 0.11) and anxiety (β = 0.07) showed smaller contributions, despite non-significant bivariate associations with nursing students’ AI readiness.

Conclusions:

Several contributing factors influenced nursing students’ readiness to embrace AI, with barriers, attitudes, and perceptions emerging as the most consistent factors, whereas self-efficacy and anxiety may play indirect roles. To improve the adoption of AI among nursing students, such factors should be dealt with in such educational programs; interrelated adoption of AIs in nursing practice is expounded as a more favorable environment.