Methods
In order to assess these correlations, we collected data referring to
scholar productivity, as expressed by the number of publications,
citable documents, citations, citations per document and the H index for
the OECD countries using The Scimago Journal and Country rank (SJR)
(http://www.scimagojr.com, accessed at June 26, 2020). It is an open
database which includes both journals and country indicators powered by
Elsevier’s B.V. Scopus database. The data collected were limited to the
field of ORL-HNS between the years 1996-2019. The 2018 GDP per capita
(in 2010 US dollars) was collected from the World Bank
(http://www.worldbank.org, accessed at accessed at June 26, 2020).
Data regarding total health spending as percent of GDP (health
expenditure) in 2018 were derived from the OECD Web site
(https://data.oecd.org/healthres/health-spending.htm, accessed at
accessed at June 26, 2020). Data regarding gross domestic expenditure in
research and development as percent of the GDP (GERD) for the year 2015
or more recent (latest available) were obtained from the United Nations
Educational, Scientific, and Cultural Organization (UNESCO)
(http://www.unesco.org, accessed at accessed at June 26, 2020).
In order to compare different bibliometric parameters to various global
regions, each of the OECD countries was categorized into a different
region according to the SJR categories; North America, Latin America,
Western Europe, Eastern Europe, Asiatic region, Middle East and the
Pacific Region. The different regions were evaluated for bibliometric
parameters. To further analyse the data retrieved, the OCED countries
were labelled in accordance to their native language; native or
non-native English-speaking. The same comparisons were then applied to
these two groups.