Artificial intelligence literacy and innovative behavior among clinical nurses: the roles of AI self-efficacy and organizational innovation climate
- 1Medical Department of Hunan Normal University
- 2Nursing Department of Yueyang Hospital Affiliated with Hunan Normal University (Yueyang People's Hospital)
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.
Related
- Editorial: Decoding cancer complexity with artificial intelligence and molecular level studies: informatics-driven approaches for therapeutic innovation
- Innovative approaches: Utilizing artificial intelligence for early diagnosis of main neurodegenerative diseases.
- Balancing innovation and ethics: responsible governance of artificial intelligence hallucinations in healthcare.
- Effectiveness of Artificial Intelligence Systems in Healthcare: A Systematic Review of Clinical and Organizational Outcomes.
- Artificial intelligence and machine learning for organizational and system-level functions in primary health care: A scoping review protocol
BibTeX
@article{li2026artificial,
title = {{Artificial intelligence literacy and innovative behavior among clinical nurses: the roles of AI self-efficacy and organizational innovation climate}},
author = {Jiahang Li and Xianyong Liu and Yang Cao and Caiyan Tang and Jianwei Zhou},
journal = {Frontiers in Public Health},
year = {2026},
month = oct,
doi = {10.3389/fpubh.2026.1958854},
url = {https://www.frontiersin.org/articles/10.3389/fpubh.2026.1958854/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Artificial intelligence literacy and innovative behavior among clinical nurses: the roles of AI self-efficacy and organizational innovation climate
AU - Jiahang Li
AU - Xianyong Liu
AU - Yang Cao
AU - Caiyan Tang
AU - Jianwei Zhou
PY - 2026
DA - 2026/10/22
JO - Frontiers in Public Health
DO - 10.3389/fpubh.2026.1958854
UR - https://www.frontiersin.org/articles/10.3389/fpubh.2026.1958854/full
AB - 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.
SN - 2296-2565
ER -