Evidence map›Paper›PMID 38525400›Full record

ArticleAdvanced biomedical research2024

Co-Occurrence Analysis of COVID-19 Publications with an Emphasis on the Global Health Governance (GHG).

Leili Allahbakhshian Farsani, Nosrat Riahinia, Farshid Danesh, Ali Azimi

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In one paragraph

Article in Advanced biomedical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Leili Allahbakhshian FarsaniDepartment of Knowledge and Information Science, Faculty of Education and Psychology, Kharazmi University, Tehran, Iran.
Nosrat RiahiniaDepartment of Knowledge and Information Science, Faculty of Education and Psychology, Kharazmi University, Tehran, Iran.
Farshid DaneshInformation Management Department, Islamic World Science and Technology Monitoring and Citation Institute (ISC), Shiraz, Iran.
Ali AzimiDepartment of Knowledge and Information Science, Faculty of Education and Psychology, Kharazmi University, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: 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). Materials and Methods: 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. Results: 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. Conclusion: 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.

Indexed as

analysisco-occurrenceCOVID-19global healthpublicationsscientometrics

Identifiers

PMID38525400
PMCPMC10958719

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.