The mediating effects of technology trust and perceived value in the relationship between eHealth literacy and attitude toward the usage of artificial intelligence in nursing: a cross-sectional study
Zhi Chen, Tsu‐Yin Wu, Xingxing Wu, Jinjia Wang, Shufen Ke, Hong Li, Rong Lin
Abstract
BACKGROUND: Attitude toward the usage of artificial intelligence in nursing directly affect nurses' technology adoption behavior. Positive attitude toward the usage of artificial intelligence can help nurses analyze large data sets and propose potential diagnoses, thereby improving diagnostic accuracy. Empirical studies have shown that there is a potential association between eHealth literacy, technology trust, perceived value, and attitude toward the usage of artificial intelligence. This study aims to explore the mediating role of technology trust and perceived value in the relationship between eHealth literacy and attitude toward the usage of artificial intelligence in nursing. METHODS: This study used a cross-sectional survey design and a self-administered online questionnaire collection platform to conduct an online survey of 564 registered nurses (clinical nurses) in Fuzhou, Fujian Province, China from March to April, 2025. The online survey was conducted in accordance with the Checklist for Reporting Results of Internet Electronic Surveys. Descriptive analysis, Harman univariate analysis, Pearson correlation test, structural equation model, and bootstrap method were used for data analysis. RESULTS: Bivariate correlation analysis found that eHealth literacy, technology trust, perceived value and artificial intelligence were positively correlated (r = 0.399 ~ 0.637, P < 0.001). Perceived value played a partial mediating role in the relationship between eHealth literacy and attitude toward the usage of artificial intelligence. Technology trust and perceived value played a chain-mediation role between eHealth literacy and attitude toward the usage of artificial intelligence. CONCLUSION: eHealth literacy was found to positively predict nurses' attitudes toward the use of AI, both directly and indirectly. These findings provide a theoretical foundation for the development of nursing AI training programs and the design of clinically applicable AI systems, contributing to a better alignment between technological innovation and the practical needs of nursing care. CLINICAL TRIAL NUMBER: Not applicable.