Predicting nursing students’ behavioral intentions to use AI: The interplay of ethical awareness, digital literacy, moral sensitivity, attitude, self-efficacy, anxiety, and social influence

Abstract

Integration of artificial intelligence (AI) into nursing practice has the potential to transform healthcare delivery. However, understanding the factors influencing nursing students’ readiness to adopt AI is essential for effective implementation. This study aimed to explore the behavioral intentions of nursing students to use AI by examining the interplay of ethical awareness, digital literacy, moral sensitivity, attitudes, self-efficacy, anxiety, and social influence. A descriptive cross-sectional methodological design was used to recruit 460 nursing students from two governmental universities in Jordan. Data were collected using validated self-administered questionnaires and analyzed using structural equation modeling (SEM) to evaluate the interrelationships among the variables. Findings revealed that positive attitudes (β = 0.43, p < .001), digital literacy (β = 0.40, p < .001), self-efficacy (β = 0.36, p < .001), and AI ethical awareness (β = 0.31, p < .001) were significant predictors of behavioral intention to use AI. Participation in AI workshops and social support also positively influenced intentions, while negative attitudes (β = -0.29, p < .001) and anxiety (β = -0.15, p < .001) served as barriers. Together, these factors accounted for 47% of the variance in behavioral intention (R2 = 0.47). In this scope, educational institutions should prioritize AI-focused training and ethics curricula, while healthcare policymakers should develop robust guidelines and invest in educational resources to prepare a workforce equipped for AI-integrated healthcare.

Topics & Concepts