Bibliometric insights into the top 100 most-cited annual studies on digital health in nursing education (2020–2024)
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. Method...
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2025-05-01
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| Series: | Digital Health |
| Online Access: | https://doi.org/10.1177/20552076251342165 |
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| author | Chunxiu Zhou Lili Ma |
| author_facet | Chunxiu Zhou Lili Ma |
| author_sort | Chunxiu Zhou |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-d35c7d88ce094a50877ab2d1aaaef768 |
| institution | OA Journals |
| issn | 2055-2076 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Digital Health |
| spelling | doaj-art-d35c7d88ce094a50877ab2d1aaaef7682025-08-20T01:50:00ZengSAGE PublishingDigital Health2055-20762025-05-011110.1177/20552076251342165Bibliometric insights into the top 100 most-cited annual studies on digital health in nursing education (2020–2024)Chunxiu Zhou0Lili Ma1 Precision Health Management Center, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai, China Department of Nursing, , School of Medicine, Tongji University, Shanghai, ChinaAim 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.https://doi.org/10.1177/20552076251342165 |
| spellingShingle | Chunxiu Zhou Lili Ma Bibliometric insights into the top 100 most-cited annual studies on digital health in nursing education (2020–2024) Digital Health |
| title | Bibliometric insights into the top 100 most-cited annual studies on digital health in nursing education (2020–2024) |
| title_full | Bibliometric insights into the top 100 most-cited annual studies on digital health in nursing education (2020–2024) |
| title_fullStr | Bibliometric insights into the top 100 most-cited annual studies on digital health in nursing education (2020–2024) |
| title_full_unstemmed | Bibliometric insights into the top 100 most-cited annual studies on digital health in nursing education (2020–2024) |
| title_short | Bibliometric insights into the top 100 most-cited annual studies on digital health in nursing education (2020–2024) |
| title_sort | bibliometric insights into the top 100 most cited annual studies on digital health in nursing education 2020 2024 |
| url | https://doi.org/10.1177/20552076251342165 |
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