Evidence map›Paper›PMID 41234474›Full record

ArticleJournal of the Medical Library Association : JMLA2025

Analyzing the citation impact of predatory journals in the health sciences.

Erin Watson, Li Zhang

Abstract read
In one paragraph

Article in Journal of the Medical Library Association : JMLA, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Erin Watsone.watson@usask.ca, University of Saskatchewan Library, Saskatoon, Saskatchewan, Canada.ORCID https://orcid.org/0000-0001-7250-9912
Li Zhangli.zhang@usask.ca, University of Saskatchewan Library, Saskatoon, Saskatchewan, Canada.ORCID https://orcid.org/0000-0001-9056-7868

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Predatory journal articles do not undergo rigorous peer review and so their quality is potentially lower. Citing them disseminates the unreliable data they may contain and may undermine the integrity of science. Using citation analysis techniques, this study investigates the influence of predatory journals in the health sciences. Methods: The twenty-six journals in the "Medical Sciences" category of a known predatory publisher were selected. The number of articles published by these journals was recorded based on the information from their websites. The "Cited References" search function in Web of Science was used to retrieve citation data for these journals. Results: Of the 3,671 articles published in these predatory journals, 1,151 (31.4%) were cited at least once by 3,613 articles indexed in Web of Science. The number of articles that cited articles published in predatory journals increased significantly from 64 in 2014 to 665 in 2022, an increase of 10-fold in nine years. The citing articles were published by researchers from all over the world (from high-, middle-, and lower-income countries) and in the journals of traditional and open access publishers. Forty-three percent (1,560/3,613) of the citing articles were supported by research funds. Conclusions: The content from articles published in predatory journals has infiltrated reputable health sciences journals to a substantial extent. It is crucial to develop strategies to prevent citing such articles.

Indexed as

BibliometricsJournal Impact FactorPeer Review, ResearchPeriodicals as TopicHumansOpen Access Publishingcitation analysishealth sciencesPredatory journalsWeb of Science

Identifiers

PMID41234474
PMCPMC12606076

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.