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Get Free AccessObjective To evaluate whether the COVID-19 experts who appear most frequently in media have high citation impact for their research overall, and for their COVID-19 peer-reviewed publications in particular and to examine the representation of women among such experts. Design Cross-linking of data sets of most highly visible COVID-19 media experts with citation data on the impact of their published work (career-long publication record and COVID-19-specific work). Setting Cable news appearance in prime-time programming or overall media appearances. Participants Most highly visible COVID-19 media experts in the USA, Switzerland, Greece and Denmark. Interventions None. Outcome measures Citation data from Scopus along with discipline-specific ranks of overall career-long and COVID-19-specific impact based on a previously validated composite citation indicator. Results We assessed 76 COVID-19 experts who were highly visible in US prime-time cable news, and 50, 12 and 2 highly visible experts in media in Denmark, Greece and Switzerland, respectively. Of those, 23/76, 10/50, 2/12 and 0/2 were among the top 2% of overall citation impact among scientists in the same discipline worldwide. Moreover, 37/76, 15/50, 7/12 and 2/2 had published anything on COVID-19 that was indexed in Scopus as of 30 August 2021. Only 18/76, 6/50, 2/12 and 0/2 of the highly visible COVID-19 media experts were women. 55 scientists in the USA, 5 in Denmark, 64 in Greece and 56 in Switzerland had a higher citation impact for their COVID-19 work than any of the evaluated highly visible media COVID-19 experts in the respective country; 10/55, 2/5, 22/64 and 14/56 of them were women. Conclusions Despite notable exceptions, there is a worrisome disconnect between COVID-19 claimed media expertise and scholarship. Highly cited women COVID-19 experts are rarely included among highly visible media experts.
John P A Ioannidis, Alangoya Tezel, Reshma Jagsi (2021). Overall and COVID-19-specific citation impact of highly visible COVID-19 media experts: bibliometric analysis. , 11(10), DOI: https://doi.org/10.1136/bmjopen-2021-052856.
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Type
Article
Year
2021
Authors
3
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1136/bmjopen-2021-052856
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