Perceptions and experiences of generative artificial intelligence training to support research for Chinese nurses: A qualitative focus group study
Ling Tong, Yirou Niu, Lixue Zhou, Shuai Jin, Yanling Wang, Qian Xiao
Abstract
Objectives: Nurses' clinical research activities have contributed to optimizing the care process and improving patient outcomes, and generative artificial intelligence (GAI) may help clinical nurses strengthen their research skills. To support research, this study aimed to explore the Chinese nurses' perceptions and experiences of GAI training. Methods: This study used a descriptive qualitative design. The China Nurses Network conducted a three-day training session on "GAI for Nursing Research" theme, we selected 23 nurses by a convenience sampling method among participating in the training. The researchers conducted three focus group interviews at the end of each day. All focus groups were interviewed face-to-face to facilitate interaction, data collection, and observation. The data were analyzed using conventional content analysis and coded manually. Results: The results showed that nurses' use of GAI to support scientific research was dynamic and characterized by evolving perceptions and practices. Four themes and 11 sub-themes emerged from the analysis: 1) utilization efficacy: cope with research ability, affected by many factors; 2) booster research: growth and challenges go hand in hand; 3) role reversal: from GAI-dominated to nurse-dominated; 4) beautiful dream: more features on research, more assistants on clinical care. Conclusions: The effectiveness of GAI in supporting clinical nurses in conducting research is mainly limited by differences in personal research literacy, lack of ethical regulation, and information accuracy. In the future, it is necessary to improve nurses' relevant skills through specialized training and promote the standardization of technical regulations to ensure the appropriate application of GAI in nursing research.