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Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
Checklists to detect potential predatory biomedical journals: a systematic review
Samantha Cukier1, Lucas Helal1, Danielle B Rice1
1Centre for Journalology, Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON, K1H 8L6, Canada.
Background:
The increase in the number of predatory journals puts scholarly communication at risk. In order to guard against publication in predatory journals, authors may use checklists to help detect predatory journals. We believe there are a large number of such checklists yet it is uncertain whether these checklists contain similar content. We conducted a systematic review to identify checklists that help to detect potential predatory journals and examined and compared their content and measurement properties.
Methods:
We searched MEDLINE, Embase, PsycINFO, ERIC, Web of Science and Library, and Information Science & Technology Abstracts (January 2012 to November 2018); university library websites (January 2019); and YouTube (January 2019). We identified sources with original checklists used to detect potential predatory journals published in English, French or Portuguese. Checklists were defined as having instructions in point form, bullet form, tabular format or listed items. We excluded checklists or guidance on recognizing "legitimate" or "trustworthy" journals. To assess risk of bias, we adapted five questions from A Checklist for Checklists tool a priori as no formal assessment tool exists for the type of review conducted.
Results:
Of 1528 records screened, 93 met our inclusion criteria. The majority of included checklists to identify predatory journals were in English (n = 90, 97%), could be completed in fewer than five minutes (n = 68, 73%), included a mean of 11 items (range = 3 to 64) which were not weighted (n = 91, 98%), did not include qualitative guidance (n = 78, 84%), or quantitative guidance (n = 91, 98%), were not evidence-based (n = 90, 97%) and covered a mean of four of six thematic categories. Only three met our criteria for being evidence-based, i.e. scored three or more "yes" answers (low risk of bias) on the risk of bias tool.
Conclusion:
There is a plethora of published checklists that may overwhelm authors looking to efficiently guard against publishing in predatory journals. The continued development of such checklists may be confusing and of limited benefit. The similarity in checklists could lead to the creation of one evidence-based tool serving authors from all disciplines.
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