Latent profiles of nurses’ attitudes toward artificial intelligence in nursing and associated factors: a cross-sectional study

Abstract

Artificial intelligence (AI) is being gradually integrated into clinical nursing practice, where it plays an important role in improving nursing quality, reducing nurses’ workload, and promoting the intelligent transformation of nursing. Nurses’ attitudes toward AI applications in nursing directly affect the promotion and implementation of this technology. Understanding these attitudes and their heterogeneity is crucial for the successful implementation of AI technology. This study aimed to identify potential types of nurses’ attitudes toward the use of AI in nursing and to explore the factors associated with profile membership with type affiliation. A cross-sectional survey was conducted among 206 clinical nurses in Anhui Province, China, in July 2025. Data were collected using a general information questionnaire, the Attitudes Toward the Application of AI Technology in Nursing Scale, and the Multidimensional Nursing Generations Questionnaire. Latent profile analysis(LPA) was used to identify distinct attitude profiles. Univariate analyses and multinomial logistic regression were performed to explore associated factors. Three profiles were identified: positive acceptance (16.02%), ambivalent balance (9.71%), and cautious skepticism (74.27%). Multinomial logistic regression showed that educational level, computer proficiency, English proficiency, and generational characteristics were significantly associated with profile membership (all P < 0.05). Nurses showed moderate attitudes toward AI in nursing with substantial heterogeneity. Profile-tailored strategies may help nursing managers facilitate the effective and sustainable implementation of AI technologies in clinical practice.