Factors associated with intention to use generative artificial intelligence in nursing practice: a cross-sectional study

Abstract

BACKGROUND: Generative artificial intelligence (GAI) can be used to support healthcare professionals. An in-depth understanding of how healthcare professionals adopt and use GAI in practice is lacking. We aimed to identify the intention to use GAI in nursing practice, its application areas, and the key factors associated with this intention. METHODS: This cross-sectional study comprised an online survey with 46 items to assess nurses' intention to use GAI. Data were collected between March 17 and 28, 2025. The participants were 176 nurses working at a tertiary hospital in Seoul, Korea. Descriptive statistics, Mann-Whitney U tests, Kruskal-Wallis H tests, correlation analyses, multiple regression analyses, and an exploratory subgroup analysis were performed. RESULTS: Overall, 61.4% of nurses reported having no experience with GAI, whereas 38.6% had used it, primarily in educational material development (50.0%) and data analysis (26.5%). Voluntariness (coefficient = 0.358, p < .001), performance expectancy (coefficient = 0.344, p < .001), and GAI literacy (coefficient = 0.192, p = .010) were key factors associated with usage intention; experience with GAI, effort expectancy, social influence, facilitating conditions, and perceived risk were not significantly associated with the intention to use GAI. The subgroup analysis revealed that the influence of key factors was moderated by prior user experience. CONCLUSIONS: This study revealed that voluntariness, performance expectancy, and GAI literacy are key drivers of nurses' intention to use GAI. Notably, their importance differs according to user experience, highlighting the need for tailored strategies to get nurses to use GAI. In the future, the sustained value of GAI in nursing practice should be assessed.

Ähnliche Arbeiten