Experiences and challenges of clinical nursing staff using generative AI to support clinical research: a qualitative study

Generative artificial intelligence (GenAI) is increasingly integrated into nursing research. However, existing studies predominantly focus on education or treat nurse researchers homogeneously, overlooking frontline nurses’ specific experiences and challenges in using GenAI for clinical research-a field with complex data and strict ethical demands. This study aimed to explore frontline clinical nurses’ experiences, challenges, role perceptions, and support needs when using GenAI in clinical research in China, to inform the development of guidelines, tools, and training. An exploratory qualitative descriptive design was adopted. 12 frontline clinical nurses with experience in both clinical research and GenAI application were recruited from multiple tertiary hospitals in Zhejiang Province via purposive and snowball sampling. To ensure sample diversity, participants were selected to cover different departments, professional titles, working years, research experience and GenAI usage habits. Data were collected through semi-structured online interviews, inductively analyzed via thematic content analysis using NVivo 15.0 software, and the study followed the COREQ checklist. Data saturation was dynamically assessed during repeated coding; no new codes or themes emerged after the 10th participant interview, and two additional interviews further confirmed saturation. Five interrelated themes emerged, forming an interpretive model of collaborative practice ecology summarized from this sample. The themes included: (1) a spectrum of attitudes from efficiency-driven acceptance to ethical skepticism; (2) dual application scenarios empowering data tasks but limited in clinical context understanding; (3) core challenges: technical reliability, data security, and academic integrity ambiguities; (4) evolving role perceptions from basic tool to potential Intelligent data-analysis assistant; (5) expectations for profession-adapted technology, targeted literacy training, and clear institutional norms. Collaboration between nurses and GenAI requires balancing efficiency and risk. In this sample, frontline nurses recognize GenAI’s research value but remain vigilant regarding technical defects, data privacy, academic integrity, and limited clinical contextual understanding. A systematic strategy encompassing context-adapted tools, enhanced AI literacy, and clear ethical and organizational guidelines is needed. This study recruited only GenAI-experienced nurses from tertiary hospitals in one Chinese province, and caution is advised when applying these findings to other settings. Not applicable.