Bibliometric and content analysis of ChatGPT research in nursing education: The rabbit hole in nursing education

Abstract

AimThis study was conducted to perform the bibliometric and content analysis of ChatGPT studies in nursing education. BackgroundChatGPT is an artificial intelligence-based chatbot developed by OpenAI. The benefits and limitations of the use of ChatGPT in nursing education are still discussed; however, it is a tool having potential to be used in nursing education. DesignBibliometric and content analysis. MethodsThe study data were scanned through Scopus and Web of Science. Bibliometric analysis was carried out with VOSViewer and Bibliometrix software. In the bibliometric analysis, science mapping and performance analysis techniques were used. Various bibliometric data, including most cited publications, journals and countries, were analyzed and visualized. The synthetic knowledge synthesis method was used in content analysis. ResultsWe analyzed 53 publications to which 151 authors contributed. The publications had been published in 29 different journals. The average number of citations of publications is 8.2. It was determined that most of the articles were published in Nurse Education Today and Nurse Educator journals and that the leading countries were the USA and Canada. It was observed that international cooperation on the issue was weak. The most frequently mentioned keywords in the publications were "ChatGPT", "artificial intelligence" and "nursing". The following three themes emerged after the content analysis: (1) Integration of ChatGPT into nursing education; (2) Potential benefits and limitations of ChatGPT; and (3) Stepping down the rabbit hole. ConclusionsWe expect that the results of the study can give nursing faculties and academics ideas about the current status of ChatGPT in nursing education and enable them to make inferences for the future.