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.