The Mediation Effect of Nurses’ Artificial Intelligence Literacy Between Professional Self‐Concept and Evidence‐Based Practice: A Cross‐Sectional Study

BACKGROUND: AI technology has had a significant revolutionary impact on the fields of healthcare and education. For the nursing staff population, the lack of artificial intelligence (AI) literacy may not only weaken the construction of their professional self-concept but also constrain the development of evidence-based practice. However, empirical research on the intrinsic correlation mechanism between these three factors is still relatively scarce at present. AIM: The purpose of this study was to explore the mediating role of AI literacy in the relationship between nurses' professional self-concept and evidence-based practice. METHODS: A cross-sectional study was conducted from October 15 to November 1, 2025, using convenience sampling to select 497 nurses from four tertiary public hospitals in Chongqing. The data collection tools include participant demographic characteristics, AI Literacy Scale (AILS), Nurse Self-Concept Questionnaire (NSCQ), and Evidence-Based Practice Questionnaire (EBPQ). The statistical software R (version 4.5.2) was adopted for data analysis, which included data feature description, correlation verification, and structural equation modeling. RESULTS: The overall demographic characteristics of the respondents were characterized by high educational levels, a mix of middle-aged and young people, and extensive work experience. The average scores for professional self-concept, AI literacy, and evidence-based practice were 232.29 ± 42.57, 63.34 ± 10.14, and 143.05 ± 22.45, respectively. It was found that a positive relationship exists between nurse AI literacy and professional self-concept (r = 0.89, p < 0.001), as well as between nurse professional self-concept and evidence-based practice (r = 0.94, p < 0.001). A significant positive correlation has also been found between AI literacy and evidence-based practice (r = 0.92, p < 0.001). AI literacy played a partial mediating role between nurse professional self-concept and evidence-based practice, with a mediation effect value of 0.587 (95% CI: 0.569-0.606), which explained 38.5% of the total effect. CONCLUSION: The study confirmed that there was a positive relationship between nurse professional self-concept and evidence-based practice, and AI literacy played a partial mediating effect in this relationship chain. It can be seen that AI literacy plays an indispensable and critical role in promoting the shape of nurse professional self-concept and enhancing their evidence-based practice ability. IMPLICATIONS FOR NURSING MANAGEMENT: Improving the AI literacy of nurses and conducting precise training are fundamental tasks in promoting the effective empowerment of clinical nursing scenarios with AI technology. To this end, it is necessary to integrate knowledge and skills related to AI into the nursing education system and simultaneously promote the lifelong professional development of nurses to effectively enhance their ability to use AI technology to optimize medical services. At the same time, healthcare institutions and nursing managers should focus on building supportive practice environments, advocating for standardized clinical applications of AI technology, and always adhering to the nursing core values guided by patient needs. TRIAL REGISTRATION: Chinese Clinical Trial Registry: ChiCTR2600118905.