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AI literacy and AI anxiety in nursing students: the serial mediating roles of attitudes and self-efficacy

作者
Qin Zeng,Shenghua Zhang,Jiacheng Hu,Yajun Wu,Min Yang,Yuan Hu
出处
期刊:Frontiers in Public Health [Frontiers Media]
卷期号:14: 1918134-1918134 被引量:1
标识
DOI:10.3389/fpubh.2026.1918134
摘要

Background: The rapid integration of artificial intelligence (AI) into health care demands that future nurses develop foundational AI competencies. However, the mechanisms through which AI literacy alleviates AI-related anxiety among nursing students remain inadequately understood, particularly regarding the sequential psychological processes involved. Objective: This study aimed to test whether attitudes toward AI and AI self-efficacy mediate the relationship between AI literacy and AI anxiety in nursing students, and to examine the serial mediation pathway among these variables. Methods: A multicenter cross-sectional survey was conducted among 1,482 nursing students from 11 universities in Sichuan Province, China, between May and October 2025. Validated Chinese versions of the Artificial Intelligence Literacy Scale (AILS), General Attitudes toward Artificial Intelligence Scale (GAAIS), Artificial Intelligence Self-Efficacy Scale (AISES), and Artificial Intelligence Anxiety Scale (AIAS) were administered. Structural equation modeling (SEM) was employed to examine direct and indirect effects. Results: < 0.001). Significant indirect associations were observed through AI attitudes and AI self-efficacy separately and through the serial pathway AI literacy → attitudes → self-efficacy → anxiety. These findings describe model-based associations and should not be interpreted as evidence of temporal or causal ordering. Conclusion: Higher AI literacy was associated with lower AI anxiety, and this association was partly accounted for by AI attitudes and AI self-efficacy in the proposed serial mediation model. The observed ordering suggests that more favorable attitudes may be linked to stronger self-efficacy, which may in turn be related to lower anxiety; however, the cross-sectional design does not establish causality. Nursing education may therefore consider combining AI knowledge and skills training with opportunities to develop balanced attitudes and confidence in using AI.

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