Bibliometric insights into the top 100 most-cited annual studies on digital health in nursing education (2020-2024)

2020-2024 年护理教育领域数字健康领域引用次数最多的 100 篇年度研究的文献计量学分析

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Abstract

AIM: This study aims to use bibliometric methods to analyze highly cited nursing education articles on digital health, particularly those 100 top cited publications between 2020 and 2024, from the Web of Science (WOS) Core Collection. DESIGN: A retrospective bibliometric analysis was conducted. METHODS: A bibliometric analysis of the most-cited digital health articles on nursing education in English with the highest citations. Data were sourced from the WOS Core Collection. Analysis was conducted using Excel and SPSS, while VOSviewer was used to visualize keyword trends. The analysis included examining journal distribution, author patterns, research types, methodologies, and keyword trends. RESULTS: The 100 most-cited articles were published between 1993 and 2024 by 91 different first authors from 22 countries. The United States contributed approximately 33% of the articles. Citation counts ranged from 198 to 1. Nurse Education Today was the most frequently cited journal. Review articles had higher average citations (50.96) compared to original articles (24.08). The focus of research has shifted from virtual reality (VR) to artificial intelligence (AI), with ChatGPT emerging as a new trend. CONCLUSION: Digital health is becoming a significant focus in nursing education research. While VR has been a dominant topic, AI is now emerging as a key research area. The findings provide insights into citation patterns and research trends, supporting future impactful studies in this field.

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