The literacy-profile dependent mediation identified highlights differentiated literacy-attitude-behavior pathways and underscores the necessity of adopting tailored, profile-specific professional development strategies instead of one-size-fits-all approaches.
Abstract
Background
Nursing educators play a pivotal role in the effective integration of artificial intelligence (AI) into nursing education. Investigating the heterogeneity of their AI literacy and its impact on attitude and behavior is a prerequisite for developing targeted interventions.
Objective
This study aimed to identify latent profiles of AI literacy among nursing educators and to examine the mediating role of AI attitude in the relationship between literacy and behavior.
Methods
A cross-sectional survey was conducted with 339 nursing educators in China. Latent profile analysis (LPA) was performed in Mplus to identify distinct AI literacy subgroups. Mediation analyses were performed using both variable-centered and person-centered approaches.
Results
Three distinct AI literacy profiles were identified: foundational (12.4%), developing (47.5%), and proficient (40.1%). The variable-centered analysis revealed that AI attitude partially mediated the relationship between AI literacy and behavior. Person-centered analysis further indicated that this mediating effect was significant only for the proficient literacy profile, but not for the developing profile, highlighting subgroup-specific mechanisms in the literacy-behavior pathway.
Conclusion
The literacy-profile dependent mediation identified highlights differentiated literacy-attitude-behavior pathwaysand underscores the necessity of adopting tailored, profile-specific professional development strategies instead of one-size-fits-all approaches.
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, which suggests that more favorable attitudes may be linked to stronger self-efficacy, which may be related to lower anxiety.
Qin Zeng, Shenghua Zhang, Jiachen Hu et al.· Frontiers in Public Health· 0 citations
Undergraduate nursing students’ AI literacy is heterogeneous and markedly related to learning engagement, providing valuable insights for improving student engagement in AI-supported learning environments.
Min Li, Yue Cao, Ruilin Zhang et al.· Frontiers in Public Health· 0 citations
Background: Generative Artificial Intelligence (GenAI) is increasingly integrated into nursing education, yet structured AI literacy training and ethical guidance remain limited. Consequently, nursing students often rely on informal learning, resulting in variability in AI readiness, confidence, and responsible use. Aims: This study was conducted to examine (1) whether AI literacy was positively associated with AI self-efficacy and AI attitudes and (2) whether AI self-efficacy mediated the relationship between AI literacy and AI attitudes. Methods: A cross-sectional survey using convenience sampling was conducted with 100 prelicensure nursing students in New York City. Data were collected using the AI Literacy Scale (AILS), AI Self-Efficacy Scale (AISES), and Generative AI Attitude Scale (GAIAS). Correlation and path analyses were performed using SPSS and Amos 30.0. Results: The participants had a mean age of 30.25 years, and 71% were women. AI literacy and AI self-efficacy were both positively associated with AI attitudes (all p < 0.001). Path analysis showed that AI literacy significantly predicted AI self-efficacy (β = 0.39, p < 0.001) and AI attitudes (β = 0.28, p = 0.003). AI self-efficacy significantly predicted AI attitudes (β = 0.31, p = 0.001) and partially mediated the relationship between AI literacy and AI attitudes. Conclusions: AI self-efficacy partially mediated the relationship between AI literacy and AI attitudes. Nursing curricula may benefit from structured AI education that integrates guided GenAI practice, case-based learning, and faculty feedback. Such educational frameworks warrant further empirical investigation regarding their potential to foster AI literacy, AI self-efficacy, and positive attitudes toward responsible AI integration, particularly through longitudinal studies assessing subsequent behavioral outcomes.
Shinhi Han, H. Kang, P. Gimber et al.· Nursing Reports· 0 citations
The findings indicate that nursing students had generally positive levels of AI literacy and attitudes toward AI, and higher AI literacy was associated with more positive attitudes toward AI.
M. Çil, Berna Eren Fidancı, D. Yildiz· Journal of Education and Res...· 0 citations
Understanding nurses’ AI literacy and its relationship with thriving at work may help hospitals design more targeted support strategies to support nurses’ AI literacy and thriving at work in similar clinical contexts.
Self-efficacy plays a critical mediating role in the relationship between digital literacy and AI anxiety among nursing students, and interventions aimed at enhancing both digital literacy and self-efficacy may be effective in reducing AI-related anxiety and supporting nursing students' psychological adaptation to emerging technologies.
Gamze Akay, Uğur Saruhan, Yeşim Saruhan et al.· BMC Nursing· 0 citations