ArticleBMC nursing2025
Nurses' attitudes toward artificial intelligence: AI literacy as a predictor and the mediating effect of AI anxiety.
Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- The Mediating Role of Work Engagement Between Artificial Intelligence Anxiety and Task Performance Among Nurses: A Cross-Sectional Correlational Study.Healthcare (Basel, Switzerland) · 2026Article
- Artificial intelligence literacy and associations with thriving at work among nurses in Anhui Province, China: a latent profile analysis.BMC nursing · 2026Article
- A concept analysis of artificial intelligence anxiety among nurses based on Walker and Avant's method.BMC nursing · 2026Article
- Multidimensional manifestations of artificial intelligence literacy among clinical nurses: a qualitative descriptive study.BMC nursing · 2026Article
- Artificial intelligence literacy and influencing factors among clinical nurses in southeastern China: a latent profile analysis.BMC nursing · 2026Article
- Artificial Intelligence: Readiness, Attitudes, and AI-Related Anxiety Among Oncology Nurses.Healthcare (Basel, Switzerland) · 2026Article
- Knowledge and attitudes regarding AI-assisted documentation among clinical nurses in China: a cross-sectional study.BMC nursing · 2026Article
- Nurses' AI training acceptance and tool usage: a structural equation model of individual and hospital-level factors.Frontiers in public health · 2026Article
- Artificial intelligence anxiety: a narrative review of psychiatric conceptualization and clinical management.Journal of Yeungnam medical science · 2026Article
- Analysis of latent profiles and influencing factors of artificial intelligence anxiety among newly recruited nurses: a cross-sectional study.Frontiers in public health · 2026Article
- Chain Mediation of Psychological Capital and Burnout Between Nurses' Artificial Intelligence Literacy and Occupational Resilience: A Cross-Sectional Study.Journal of nursing management · 2026Article
- Artificial intelligence anxiety and its association with willingness to receive AI-related training among maternal and child health nurses: a multicenter network analysis.Frontiers in public health · 2026Article
- Latent profile analysis of artificial intelligence anxiety among undergraduate nursing students: a cross-sectional study.Frontiers in public health · 2026Article
- The Mediating and Moderating Roles of Innovation Climate in the Relationship Between Nurses' Attitudes Toward Artificial Intelligence, Creative Self-Efficacy, and Clinical Competence.Journal of nursing management · 2026Article
- How does artificial intelligence literacy affect university students' innovative behavior? A serial mediation analysis based on latent profiles.Frontiers in psychology · 2026Article
- Hospital Digital Transformation, Nursing Data Burden, and Leadership and Governance Capacity: A Critical Narrative Review.Journal of nursing management · 2026Review
- Inclusive Leadership, Psychological Safety, AI Readiness, and Nurses' AI Literacy: A Longitudinal Study.Journal of nursing management · 2026Article
- Dynamic pathways in the development of university students' AI literacy: integrating quantitative and qualitative evidence.Frontiers in psychology · 2026Article
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7 authors.
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Abstract
aimsThis study examines the demographic factors affecting nurses’ attitudes toward artificial intelligence (AI), AI literacy and AI anxiety. Explore the correlations among nurses’ AI literacy, AI anxiety and attitudes toward AI, and determine the internal mechanisms of the correlations among the three.
methodsThis study investigated 478 nurses working in hospitals in Hunan Province, China. A battery of instruments was used for data collection: a Nurse Information Form for Demographics, and three standardized scales—the Artificial Intelligence Literacy Scale (AILS), the Artificial Intelligence Anxiety Scale (AIAS), and the General Attitudes Towards Artificial Intelligence Scale (GAAIS)—to assess the core constructs of this study. Aided by IBM SPSS Statistics (Version 26.0), the collected data were collated and subjected to statistical analysis. Multivariate analysis was performed to investigate the effects of different social demographic data on the study subjects’ attitudes toward AI, AI literacy and AI anxiety. We also analyzed the correlations among attitudes toward AI, AI literacy and AI anxiety, and conducted multiple linear regression analysis on the variables with statistically significant effects on attitudes toward AI in univariate analysis and correlation analysis, using the Hayes PROCESS 4.1 model in SPSS to explore the mediating effects among these variables.
resultsAmong the 478 questionnaires collected, 450 were valid, for an effective response rate of 94.14%. The attitudes toward AI, AI literacy, and AI anxiety scores were 55.10 ± 8.25, 63.86 ± 8.91, and 61.95 ± 24.92, respectively. The education, age and professional title of the nurses significantly differed in terms of their attitudes toward AI. Nurse gender is correlated with AI literacy levels. AI anxiety is significantly negatively correlated with AI literacy (r =-0.32, p ≤ 0.001) and attitudes toward AI (r =- 0.42, p ≤ 0.001), whereas AI literacy and attitudes toward AI are significantly positively correlated (r = 0.45, p ≤ 0.001). The percentage of the mediating effect attributable to AI anxiety was 22.22%.
conclusionsIn our research, nurses’ attitudes toward AI are closely linked to their AI literacy and AI anxiety, with AI anxiety acting as the underlying mechanism that explains the relationship between these two factors. Nursing administrators should focus on enhancing nurses’ AI literacy while monitoring their emotional states to strengthen their positive attitudes toward AI. To achieve this goal, nursing managers could adopt a dual approach: First, practical AI-related training could be provided to improve nurses’ AI literacy. Second, during this critical phase of digital transformation, individuals regularly assess their psychological well-being and implement supportive measures to alleviate AI anxiety.
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