Yapay Zeka Okuryazarlığı Hemşire Yenilikçiliğini Artırıyor, Öz-Yeterlik Aracılığıyla ve İklimle Düzenlenerek

Özet (abstract)

Objective To investigate the current status and related factors of innovative behavior among clinical nurses in tertiary hospitals and explore the relationships and pathways among artificial intelligence literacy, AI self-efficacy, organizational innovation climate, and nurse innovative behavior, for providing a basis for targeted nursing management strategies. Methods This cross-sectional study was conducted on 850 nurses from six tertiary medical institutions using a stratified survey approach in Yueyang city, Hunan province, from June to July 2026, in the General Information Questionnaire, Artificial Intelligence Literacy Scale, Artificial Intelligence Self-Efficacy Scale, Organizational Innovation Climate Scale, and Nurse Innovative Behavior Scale were used. AMOS 24.0 was used to conduct confirmatory factor analysis to assess the model fit of the scales. SPSS 26.0 was used for descriptive statistics, univariate analysis, Pearson correlation analysis, and multiple linear regression. PROCESS macro version 4.2 Models 4 and 14 tested mediation and moderated mediation effects. Results A total of 850 valid questionnaires were obtained, with a valid questionnaire rate of 95.3%. The mean nurse innovative behavior score was 37.93±6.50. The measurement model for the four scales showed good fit, and the scales demonstrated good convergent validity and some evidence of discriminant validity. Artificial intelligence literacy, artificial intelligence self-efficacy, organizational innovation climate, and innovative behavior showed positive associations with one another (r = 0.609–0.797, P < 0.01). Educational level, professional title, participation in research or innovation activities, artificial intelligence literacy, artificial intelligence self-efficacy, and organizational innovation climate were factors associated with nurse innovative behavior and explained 60.9% of the total variance. Artificial intelligence self-efficacy partially mediated the relationship between artificial intelligence literacy and nurse innovative behavior. The indirect effect was 0.322, with a 95% CI of 0.243–0.403, accounting for 52.90% of the total effect. Organizational innovation climate moderated the relationship between artificial intelligence self-efficacy and nurse innovative behavior (b = 0.051, P < 0.01). The index of moderated mediation was 0.041, with a 95% CI of 0.009–0.078. Conclusion AI literacy was closely related to nurse innovative behavior, with AI self-efficacy as a partial mediator and organizational innovation climate as a moderator. Nursing management may focus on AI competencies, application confidence, and organizational support.

Yazarların özeti; kaynağından alınmıştır. Frontiers in Public Health, 2026 · DOI ↗