The research hotspots and theme trends of artificial intelligence in nurse education: A bibliometric analysis from 1994 to 2023

Abstract

ObjectivesTo explore research hotspots and theme trends in artificial intelligence in nurse education using bibliometric analysis. DesignBibliometric analysis. Data sourcesLiterature from the Web of Science Core Collection from the time of construction to October 31, 2023 was searched. Review methodsAnalyses of countries, authors, institutions, journals, and keywords were conducted using Bibliometrix (based on R language), CiteSpace, the online analysis platform (bibliometric), Vosviewer, and Pajek. ResultsA total of 135 articles with a straight upward trend over the last three years were retrieved. By fitting the curve R2 = 0.6022 (R2 > 0.4), we predicted that the number of annual articles is projected to grow in the coming years. The United States (n = 38), the National University of Singapore (n = 16), Professor Jun Ota (n = 8), and Nurse Education Today (n = 14) are the countries, institutions, authors, and journals that contributed to the most publications, respectively. Collaborative network analysis revealed that 32 institutional and 64 author collaborative teams were established. We identified ten high-frequency keywords and nine clusters. We categorized the research hotspots of artificial intelligence in nurse education into three areas: (1) Artificial intelligence-enhanced simulation robots, (2) machine learning and data mining, and (3) large language models based on natural language processing and deep learning. By analyzing the temporal and spatial evolution of keywords and burst detection, we found that future research trends may include (1) expanding and deepening the application of AI technology, (2) assessment of behavioral intent and educational outcomes, and (3) moral and ethical considerations. ConclusionsFuture research should be conducted on technology applications, behavioral intent, ethical policy, international cooperation, interdisciplinary cooperation, and sustainability to promote the continued development and innovation of AI in nurse education.