Indexing status of orthodontic research published in presumed predatory journals: a bibliometric study.
Type: paratext
Abstract: Objectives To examine the frequency and features of presumed predatory orthodontic publications. We also aimed to assess the presence of these types of publications in established scientific databases.Methods Six electronic databases were searched to identify orthodontic articles published in 2022 in English. Equal numbers of articles from legitimate (n = 159) and suspect or predatory journals (n = 159) were considered. Data regarding journal, article and author characteristics were obtained. The indexing status of the publications in PubMed, Ovid, Embase, Web of Science, Scopus and EBSCOhost was evaluated. The total number of databases that the article was indexed in, level of evidence, origin of first author and research funding were recorded. Univariable ordinal regression analyses were performed to explore potential association between article legitimacy and indexing status.Results The majority of studies in predatory journals were found in non-specialized journals (79.6%). Scopus was the most porous database, indexing over half of predatory and suspect articles (56%). In Web of Science (Core collection), the distribution of articles across different indexing categories varied (SCIE; 16.4%, ESCI; 30.2%). In contrast, only 8.2% of these articles appeared in Medline. Articles in legitimate journals tended to have higher level of evidence and were indexed in more databases in comparison to predatory/suspect publications (OR=1.5; 95% CI: 1.37-1.64; p<0.01). The origin of the first author was a significant predictor for journal legitimacy (p<0.001).Conclusion A high proportion of orthodontic publications appear in presumed predatory and suspect journals which are in turn often indexed in trustworthy databases. Medline was the least susceptible to predatory publications, while Web of Science and Scopus were more prone.Clinical Significance Predatory and suspect journals are increasingly prevalent with the penetration of these journals into recognized databases. We were able to identify associated trends.
DOI: 10.48620/77140
Authors: Maroulakos, Michael P, Al-Moghrabi, Dalya, Fleischmann, Isabel, Pandis, Nikolaos, Fleming, Padhraig S
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6967064613
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