ArticleBMC nursing2025
Factors associated with intention to use generative artificial intelligence in nursing practice: a cross-sectional study.
Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Exploring Nurses' Perspectives on the Use of Artificial Intelligence Chatbots for Mental Health Support: A Cross-Sectional Study in Greece.Nursing reports (Pavia, Italy) · 2026Article
- Generative artificial intelligence literacy profiles and workforce readiness among pre-professional nursing students: a latent profile analysis.Frontiers in public health · 2026Article
- Artificial intelligence literacy, anxiety, and attitudes among registered nurses across different hospital tiers: a multi-center cross-sectional study.Frontiers in public health · 2026Article
- Sociodemographic factors, anxiety and attitudes toward generative artificial intelligence among nurses.Frontiers in psychiatry · 2026Article
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2 authors.
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Abstract
backgroundGenerative 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.
methodsThis 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.
resultsOverall, 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.
conclusionsThis 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.
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