Indexing status of orthodontic research published in presumed predatory journals: A bibliometric study

Abstract

Objectives

To examine the indexing status of presumed predatory orthodontic publications within established scientific databases.

Methods

Six electronic databases were searched to identify English language orthodontic articles published in 2022. 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 Scopus and ESCI were more prone.

Clinical significance

Predatory and suspect journals are increasingly prevalent with increasing prominence being afforded by their penetration through recognized databases.