Telemedicine Literature during COVID-19: A Scientometric Analysis


Telemedicine, Telecare, COVID-19, Scientometrics

How to Cite

Borhani, S. ., Zohari, M. ., karim, N. ., Rashidi, H. ., & Asadzandi, S. (2022). Telemedicine Literature during COVID-19: A Scientometric Analysis. Iranian Red Crescent Medical Journal, 24(3).


Background: During the COVID-19 pandemic, telemedicine is applied for various purposes, such as reducing the time of diagnosis and initiating treatment, quarantining and stabilizing patients, enabling the system to closely monitor the citizens at home, and supporting health professionals.

Objectives: The present study used Scientometrics analysis to comprehensively analyze the body of research conducted on telemedicine regarding COVID-19.

Methods: By using a searching formula, 900 documents were retrieved from the Web of Science. Co-authorship networks were drawn by CiteSpace and Gephi software that are free and powerful illustrating networks. The selected co-authorship indicators were Degree Centrality, Betweenness Centrality, and Closeness Centrality.

Results: Andrea M. Russo had by far a high degree of centrality, compared to other authors. Regarding the countries, Belgium and Portugal had a larger node, indicating that they had a higher degree of centrality. Neurosciences had a large node, showing the higher degree of centrality of this subject area. Psychology and Clinical Neurology were also the nodes with a higher degree of centrality. The degree of centrality was high for the University of Zurich, University of Barcelona, and King College London, and the connections of these nodes were more and even stronger, compared to other nodes.

Conclusion: This study, which was based on 900 scientific credentials in the field of telemedicine during COVID-19, indicated the level of cooperation among authors, countries, and organizations in 2020. Moreover, by presenting different indicators in these networks’ researchers, countries, and key organizations were introduced for each indicator.


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