Nurse Researchers’ Experiences and Perceptions of Generative AI: Qualitative Semistructured Interview Study

作者：Ruifu Kang, Zehui Xuan, Ling Tong, Yanling Wang, Shuai Jin, Qian Xiao · 发表于：Journal of Medical Internet Research · 年份：2025 · DOI：10.2196/65523 · 被引用次数：9 · 研究领域：Artificial Intelligence in Healthcare and Education、AI in Service Interactions、Simulation-Based Education in Healthcare

Background: With the rapid development and iteration of generative artificial intelligence, the growing popularity of such groundbreaking tools among nurse researchers, represented by ChatGPT (OpenAI), is receiving passionate debate and intrigue. Although there has been qualitative research on generative artificial intelligence in other fields, little is known about the experiences and perceptions of nurse researchers; this study seeks to report on the topic. Objective: This study aimed to describe the experiences and perceptions of generative artificial intelligence among Chinese nurse researchers, as well as provide a reference for the application of generative artificial intelligence in nursing research in the future. Methods: Semistructured interviews were used to collect data in this qualitative study. Researchers mainly conducted interviews on the cognition, experience, and future expectations of nurse researchers regarding the use of generative artificial intelligence. Twenty-seven nurse researchers were included in the study. Through purposive sampling and snowball sampling, there were 7 nursing faculty researchers, 10 nursing graduate students, and 10 clinical nurse researchers. Data were analyzed using inductive content analysis. Results: Five themes and 12 subthemes were categorized from 27 original interview documents as follows: (1) diverse reflections on human-machine symbiosis, which includes the interplay between substitution and assistance, researchers shapin...