Digital Resilience of Clinical Nurses Across Hospital Tiers: A Multicenter Cross‐Sectional Study in China
Ming Yu, Ronghui Geng, Rong Yu, Mengjia Zhou, Xiaoli Fan, Lingling JiangAim
To investigate the status of digital resilience among clinical nurses in China and to analyze its influencing factors, thereby providing a reference for promoting the application of artificial intelligence technology in healthcare.
Design
A descriptive, cross‐sectional study.
Methods
From August to September 2025, 680 clinical nurses were recruited from three hospitals in Nantong City, Jiangsu Province, China (one tertiary A hospital, n = 220; two tertiary B hospitals, n = 460). Data were collected using a general information questionnaire, the Artificial Intelligence Literacy Scale, the Perceived Organizational Support Scale, the General Self‐Efficacy Scale, and a clinically adapted version of the Digital Resilience Scale. Multiple linear regression (enter method) was performed to identify influencing factors.
Results
The total score of digital resilience among clinical nurses was 123.68 ± 10.43 (out of 195). Nurses in the tertiary A hospital scored significantly higher than those in tertiary B hospitals (125.17 ± 6.49 vs. 123.05 ± 11.80, t = 3.020, p = 0.003). Multiple linear regression revealed that perceived organizational support ( β = 0.621), hospital tier ( β = − 0.335), AI literacy ( β = 0.272), monthly income ( β = 0.126), monthly night shifts ( β = − 0.091), educational level ( β = 0.069), and self‐efficacy ( β = 0.066) were significant factors influencing digital resilience (all p < 0.05), collectively accounting for 76.3% of the total variance (adjusted R 2 = 0.763).
Conclusion
This multicenter study revealed significant disparities in digital resilience across hospital tiers. Tertiary A hospital nurses scored highest, followed by secondary hospital nurses, while tertiary B hospital nurses scored lowest. These differences were mainly driven by AI literacy, organizational support, and self‐efficacy. Hospital tier also moderated the relationship between organizational support and digital resilience, with stronger effects in lower‐tier hospitals.
Implications for Nursing
Nursing administrators should implement tier‐specific strategies to strengthen digital resilience. Tertiary A hospitals need advanced AI training and leadership development. Secondary and tertiary B hospitals require foundational digital infrastructure and organizational support, including structured AI training, mentorship, and technical assistance. Differentiated resource allocation across hospital tiers will facilitate successful AI integration into clinical nursing practice. Future research should investigate the mechanisms underlying these tier differences and evaluate tier‐specific interventions.