Data collection

The top 6 impact factor (IF) orthodontic journals as listed in 2017 Journal Citation Reports (JCR, Clarivate Analytics, Philadelphia, PA, USA) were examined in this study, namely Orthodontics & Craniofacial research (OCR; IF, 2.077), European Journal of Orthodontics, (EJO; IF, 2.033), American Journal of Orthodontics and Dentofacial Orthopedics (AJODO; IF, 1.842), The Korean Journal of Orthodontics (KJO; IF, 1.617), The Angle Orthodontist (AO; IF, 1.592), and Progress in Orthodontics (PIOR; IF, 1.250).

All issues published by the abovementioned journals between January and December 2018 were accessed using institutional subscription and hand-searched for original research articles, reviews, and case reports. Articles not falling into these categories were excluded.

Two investigators (first and second authors) underwent a 4-h training in article screening and data extraction, divided in 2 sessions. In the first session, each investigator screened titles and abstracts of a preselected sample of 40 articles. Any practical issues encountered were discussed during the second session. For the purposes of the study, the following information was extracted simultaneously and on a consensus basis from each eligible article: (i) journal title, (ii) article title, (iii) names of first and last authors, (iv) study type, i.e., randomized clinical trials, prospective observational study, retrospective observational study, narrative review, systematic review or meta-analysis, survey, case report [6], (v) topic, i.e., oral health-related quality of life (OHRQOL)/esthetics/practice management/socio-demographics, biomaterials, diagnosis, treatment, growth, new technologies, periodontics/caries prevention, side effects, other [1], (vi) number of authors, (vii) number of total citations (TC), (viii) number of self-citations, (ix) self-citation rate (SCR) calculated as the percentage of the author self-citations to the total citations included in the reference list, also termed as synchronous self-citation [11], (x) author rank, i.e., first, last or first/last in case of an equal number of self-citations assigned to both first and last authors, (xi) gender, and (xii) origin as indicated by the geographical location of the affiliation of the most self-citing author (first or last author). To facilitate data analysis, regions were classified into 5 groups, i.e., Asia, Europe, North America, South America, and other, which included Africa, Oceania, or a combination of continents. Articles were grouped as well according to the number of authors as follows: 1–3, 4–5, and > 5 authors. Gender of the authors was determined using genderize.io (https://genderize.io/; Demografix ApS, Roskilde, Denmark), a free online service that collects data from social networks across 79 countries and 89 languages. This tool was chosen due to its superior performance in gender prediction compared to other name-to-gender inference services [12]. The collected data were entered into a Microsoft Excel spreadsheet (Microsoft Corporation, Redmond, VA, USA) for further processing.