technical paper
Comparison of the Characteristics of COVID-19 and Non-COVID-19 Retractions
keywords:
pandemic science
errors and corrections
retractions
Objective Concerns have been raised about the number of
retracted COVID-19–related studies.1Although this may be
due to the greater scrutiny of COVID-19–related literature,
little is known about the potential differences between
retracted COVID-19–related and non–COVID-19–related
studies, including author characteristics and reasons for
retractions.
Design In this cross-sectional analysis, all retractions of
publications and withdrawals of preprints reporting the
results of COVID-19–related and non–COVID-19–related
medical studies indexed in the Retraction Watch Database
between January 1, 2020, and May 5, 2022, were identified.
Nonoriginal research (eg, retracted letters, viewpoints, and
book chapters) and manuscripts classified by the Retraction
Watch team as having been generated by companies that sell
fake manuscripts (ie, paper mills) were excluded. For each
retraction, the publication type (article or preprint) and
design, number of authors, first and last authors and their
affiliations, and date of retraction were recorded. The most
prominent reasons for retraction were identified and grouped
across similar categories. Scopus and then Google Scholar
were searched to identify first and last author profiles, which
were verified using affiliations, and we recorded an H-index
and year of first publication for each author. The Fisher exact
test and Mann-Whitney test were used to compare
proportions of COVID-19–related vs non–COVID-19–related
retractions.
Results Between January 1, 2020, and May 5, 2022, 140
COVID-19–related and 397 non–COVID-19–related studies
were indexed in the Retraction Watch Database (Table 8);
72.1% of the COVID-19–related studies were peer-reviewed
articles (27.9% were preprints), whereas 99.7% of the
non–COVID-19–related studies were peer-reviewed articles.
COVID-19–related studies were more likely to be retracted or
withdrawn within 6 months of publication or posting than
non–COVID-19–related studies (82.1% vs 58.2%; P < .001). A
greater proportion of modeling studies among the
COVID-19–related than non–COVID-19–related studies was
observed (13.6% vs 1.8%). COVID-19–related studies were
more likely to be retracted without any explanation or to be
removed for non–misconduct-related concerns than non–
COVID-19–related studies (60.0% vs 35.5%). The first
(29.1%) and last (30.7%) authors of COVID-19–related
studies were more likely to have North American affiliations
than the first (9.9%) and last (11.9%) authors of non–
COVID-19–related studies. Nearly all first (97.6%) and last
(98.0%) authors of all studies had academic or hospital
affiliations. First and last authors of COVID-19–related
studies had higher median (IQR) H-indexes than those of
non–COVID-19–related manuscripts (7 2-15 and 17 4-27
vs 2 1-6 and 5 1-18).
Conclusions Author and manuscript characteristics differed
between retracted COVID-19–related and non–COVID-19–
related studies. Although there have been hundreds of
COVID-19–related retractions since the start of the pandemic,
there have also been tens of thousands of preprints and
published articles.
Reference
1. Abritis A, Marcus A, Oransky I. An “alarming” and
“exceptionally high” rate of COVID-19 retractions? Account
Res. 2021;28(1):58-59. doi:10.1080/08989621.2020.1793675
Conflict of Interest Disclosures Xiaoting Shi is supported
by the China Scholarship Council in the past 36 months. Alison
Abritis is an employee of The Center For Scientific Integrity, which
developed and maintains the Retraction Watch Database. Ivan
Oransky is the volunteer executive director of The Center For
Scientific Integrity, a nonprofit organization that is funded through
database licensing fees, a subcontract from the University of Illinois
on a Howard Hughes Medical Institute grant, and donations from
individuals. Joseph S. Ross is a former associate editor of JAMA
Internal Medicine, a current research editor at The BMJ, and
receives research support through Yale University from Johnson
and Johnson to develop methods of clinical trial data sharing, from
the Medical Device Innovation Consortium as part of the National
Evaluation System for Health Technology (NEST), from the US Food
and Drug Administration (FDA) for the Yale-Mayo Clinic Center
for Excellence in Regulatory Science and Innovation program
(U01FD005938), from the Agency for Healthcare Research and
Quality (R01HS022882), from the National Heart, Lung, and Blood
Institute of the National Institutes of Health (NIH) (R01HS025164,
R01HL144644), and from the Laura and John Arnold Foundation to
establish the Good Pharma Scorecard at Bioethics International; in
addition, he is an expert witness at the request of relator’s attorneys,
the Greene Law Firm, in a qui tam suit alleging violations of the
False Claims Act and Anti-Kickback Statute against Biogen Inc.
Joshua D. Wallach is supported by the FDA, Johnson & Johnson,
and the National Institute on Alcohol Abuse and Alcoholism of the
NIH under award 1K01AA028258.