Allahbakhshian Farsani Leili, Riahinia Nosrat, Danesh Farshid, Azimi Ali
Department of Knowledge and Information Science, Faculty of Education and Psychology, Kharazmi University, Tehran, Iran.
Information Management Department, Islamic World Science and Technology Monitoring and Citation Institute (ISC), Shiraz, Iran.
Adv Biomed Res. 2024 Jan 30;13:10. doi: 10.4103/abr.abr_344_23. eCollection 2024.
Analyzing co-occurrence is an effective way to monitor the overview of topic spreading. The present study aimed to conduct a co-occurrence analysis of scientific publications related to COVID-19, emphasizing Global Health Governance (GHG).
This applied research with an analytical approach was carried out on all the scientific publications related to COVID-19, emphasizing GHG (51056 records), extracted from PubMed Central on 26/01/2022. The research population consisted of all the scientific publications related to COVID-19, emphasizing GHG (51056 records), extracted from PubMed Central on 26/01/2022. The data were analyzed using BibExcel, UCINET, Excel, and SPSS software, and Spearman's test was used to confirm correlations.
The co-word network of the thematic area of COVID-19 includes 226 nodes and 7292 edges. COVID-19 and the pandemic formed the most co-word pairs with 2224 connections. The COVID-19* mental health and COVID-19* anxiety, with 1019 and 925 connections, are ranked next, respectively. The term COVID-19 is ranked first with a centrality index of 225. The keywords of pandemic and public health are ranked second and third with the centrality index of 217 and 206, respectively.
The global approach of studies related to COVID-19 is more inclined to the epidemiological and public health fields. Assuming the GHG, detailed and comprehensive planning should be performed to strengthen these studies and pave the way for international cooperation, determining research requisites, and developing applied research studies.
分析共现情况是监测主题传播概况的有效方法。本研究旨在对与新冠疫情相关的科学出版物进行共现分析,重点关注全球卫生治理(GHG)。
本采用分析方法的应用研究针对2022年1月26日从PubMed Central中提取的所有与新冠疫情相关且重点关注全球卫生治理的科学出版物(51056条记录)展开。研究总体包括2022年1月26日从PubMed Central中提取的所有与新冠疫情相关且重点关注全球卫生治理的科学出版物(51056条记录)。使用BibExcel、UCINET、Excel和SPSS软件对数据进行分析,并使用斯皮尔曼检验来确认相关性。
新冠疫情主题领域的共词网络包括226个节点和7292条边。新冠疫情与大流行形成了最多的共词对,有2224个连接。新冠疫情心理健康和新冠疫情焦虑分别以1019和925个连接位列其次。术语“新冠疫情”以225的中心性指数排名第一。大流行和公共卫生的关键词分别以217和206的中心性指数排名第二和第三。
与新冠疫情相关的研究的全球方法更倾向于流行病学和公共卫生领域。假设全球卫生治理,应进行详细和全面的规划,以加强这些研究,并为国际合作、确定研究需求和开展应用研究铺平道路。