Cognitive status of nursing postgraduates toward Generative Artificial Intelligence: a qualitative study based on the UTAUT framework

作者：Hongzhan Jiang, Ziyan Wang, Meiqi Meng, Bo Li, Sihan Chen, Dan Yang, Xuejing Li, Yufang Hao · 发表于：BMC Nursing · 年份：2026 · DOI：10.1186/s12912-025-04187-2 · 被引用次数：9 · 研究领域：Artificial Intelligence in Healthcare and Education、Artificial Intelligence Applications、AI in Service Interactions

BACKGROUND: Generative Artificial Intelligence (GenAI) has the potential to enhance research efficiency and reduce clinical workload for nursing postgraduates, gradually transforming the development of the healthcare and nursing sectors. Understanding nursing postgraduates' experiences and perceptions of Generative Artificial Intelligence tools is essential for promoting their proper application. AIM: To comprehensively explore Chinese nursing postgraduates' perceptions, attitudes, and needs regarding GenAI using qualitative interviews. DESIGN: A qualitative study design. METHODS: Semi-structured interviews were conducted among 16 nursing postgraduates. Purposeful sampling was used to select master's degree nursing students with experience in the use of artificial intelligence. Thematic analysis was performed to identify recurring patterns and codes. RESULTS: Five major themes emerged from the analysis: (1) performance expectancy, (2) effort expectancy, (3) social influence, (4) usage attitudes and behaviors, and (5) boundaries to Generative Artificial Intelligence adoption. The findings revealed nursing postgraduates' generally positive perceptions and usage behaviors toward Generative Artificial Intelligence, alongside the barriers and concerns they associate with its application. CONCLUSIONS: Generative Artificial Intelligence is increasingly integrated into research and practice in healthcare and nursing. Nursing students should approach Generative Artificial Intelligence...