JMIR Publications

ABSTRACT

Background:

With the rapid development and iteration of generative artificial intelligence, the growing popularity of such groundbreaking tools among nurse researchers, represented by ChatGPT, 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, and this study seeks to report on the subject.

Objective:

This study aimed to describe the experiences and perceptions of generative artificial intelligence among Chinese nurse researchers. Provide a reference for the application of generative artificial intelligence in nursing research in the future.

Methods:

Semi-structured interviews were used to collect data in this qualitative study. Data were analyzed employing inductive content analysis.

Results:

Five themes and twelve sub-themes were categorized from 27 original interview documents as follows: (1) Diverse reflections on human-machine symbiosis, which includes the interplay between substitution, researchers shaping the potential space of generative artificial intelligence, and researchers accepting generative artificial intelligence with alacrity; (2) Heterogeneity of groups and experiences, including diversity in experiences of using and heterogeneity in the perception and use among different groups; (3) Research paradigm reshaping in the infancy stage, which involves a groundbreaking auxiliary tool in nursing research and the incubation of innovative research paths; (4) Ethical concerns and application challenges, considering insight into the public opinion around generative artificial intelligence, academic integrity and medical ethical challenges, and limitations on application in nursing research; (5) Future development and capacity reinforcement, which concerns reinforcement needs for utilization competency and collaboration and exploration in future nursing research. In this context, the first four themes form the rocket of the human-machine symbiosis journey. Only when humans fully leverage the advantages of machines (generative artificial intelligence) and overcome the shortcomings of them, can this human-machine symbiosis journey reach towards the correct future direction (fifth theme).

Conclusions:

This study explored the experiences and perceptions of nurse researchers interacting with generative artificial intelligence, which was a "symbiotic journey" full of windings. The human-machine interaction process relentlessly moves nurse researchers to improve scientific literacy, digital literacy, and prompt skills. Meanwhile, the potential hazards and concerns of this topic for nurse researchers became apparent, with an emphasis on academic integrity, drafting relevant specifications, and the accuracy of generated content. Collaboration with interdisciplinary professionals, utilizing supervised fine-tuning, knowledge graphs, and retrieval augmented generation techniques, to develop nursing research-specific multimodal artificial general intelligence was expected to meet the individual needs of nurse researchers.