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Enregistrement W7115730218 · doi:10.48448/zkc3-p805

Consistency and Completeness of Retractions in Public Health Research on COVID-19

2025· other· W7115730218 sur OpenAlexaffabout

Notice bibliographique

RevueUnderline Science Inc. · 2025
Typeother
Langue
Domaine
Thématique
Établissements canadiensUniversity of Regina
Organismes subventionnairesnon disponible
Mots-clésNoticeCompleteness (order theory)Consistency (knowledge bases)Presentation (obstetrics)Public healthData presentation

Résumé

récupéré en direct d'OpenAlex

Caitlin J. Bakker,<sup>1,2</sup> Erin E. Reardon,<sup>3</sup> Sarah Jane Brown,<sup>4</sup> Nicole Theis-Mahon,<sup>4</sup> Sara Schroter,<sup>5,6</sup> Lex Bouter,<sup>7,8</sup> Maurice P. Zeegers<sup>2</sup> <h4>Objective </h4> The scientific community responded rapidly to COVID-19, producing over 200,000 publications in 1 year.<sup>1</sup> This speed brought challenges, including a higher retraction rate.<sup>2</sup> While retraction helps correct the scientific record, retracted status may be inconsistently presented and notices may be incomplete.<sup>3</sup> During a pandemic, inconsistency and incompleteness can have immediate and long-term health impacts. We evaluated retraction presentation consistency and notice completeness for COVID-19 vs non–COVID-19 publications. We describe reasons for retraction and time from publication to retraction. <h4>Design </h4> In March 2023, we retrieved retracted publications categorized as research articles or clinical studies in the subject area of public health and safety from Retraction Watch. A previous study focused on all retracted publications in this period<sup>3</sup>; this is a sub-study comparing COVID-19 with non–COVID-19 publications. Between April 28 and June 6, 2023, we assessed consistency in 11 databases (Academia.edu, CINAHL, Embase.com, Ovid Embase, Ovid Medline, PubMed, ResearchGate, SciHub, Scopus, Web of Science, and publisher websites) using 12 criteria from the International Committee of Medical Journal Editors and National Library of Medicine and notice completeness using 17 criteria from Retraction Watch and the Committee on Publication Ethics. Criteria were scored 0 if missing or 1 if present; partial scores were assigned when evaluating multicomponent criteria, such as bidirectional links. To ensure consistent scoring, a random subset of 21% (92 of 441) of retracted publications were independently reviewed by 2 researchers. Each researcher extracted data using Qualtrics forms, and scoring discrepancies were resolved by consensus. Following this calibration phase, remaining publications were extracted by a single reviewer. Kruskal-Wallis tests assessed differences in scores between COVID-19 and non–COVID-19 publications. <h4>Results</h4> Of 441 publications, 47 were about COVID-19 and 394 were not. COVID-19 publications were published between 2019 and 2022, while non-COVID 19 publications were published between 1978 and 2022. COVID-19 publications were most frequently retracted due to concerns about reliability of data or results (15 [31.9%]) compared with plagiarism (82 [20.8%]) for non–COVID-19 publications. The median time between publication and retraction was 120 (IQR, 15-196) days for COVID-19 publications and 326 (IQR, 124-789) days for non–COVID-19 publications (<i>P</i> &lt; .001). Across 11 databases, 41.2% (110 of 267) of records retrieved for retracted COVID-19 publications were marked as retracted compared with 47.6% (1225 of 2574) for non–COVID-19 publications. There was no statistically significant difference between consistency or completeness scores for COVID-19 vs non–COVID-19 retracted publications (<b>Table 25-1062</b>). No publications met all criteria. https://assets.underline.io/markdown_image/1/image/edc419e41ec09f04154b15739dea0699.png <h4>Conclusions </h4> Incomplete and inconsistent information poses challenges for researchers and practitioners, undermining trust in scientific literature. We found no association between publications being about COVID-19 and the consistency or completeness of retraction information; however, publications about COVID-19 appeared to be retracted more quickly. <h4>References</h4> 1. Shimray SR. Research done wrong: a comprehensive investigation of retracted publications in COVID-19. <i>Account Res</i>. 2022;30(7):393-406. doi:10.1080/08989621.2021.2014327 2. Yeo-Teh NSL, Tang BL. An alarming retraction rate for scientific publications on coronavirus disease 2019 (COVID-19). <i>Account Res</i>. 2020;28(1):47-53. doi:10.1080/08989621.2020.1782203 3. Bakker CJ, Reardon EE, Brown SJ, et al. Identification of retracted publications and completeness of retraction notices in public health. <i>J Clin Epidemiol</i>. 2024;173:111427. doi:10.1016/j.jclinepi.2024.111427 <sup>1</sup>University of Regina, Regina, Saskatchewan, Canada, caitlin.bakker@uregina.ca; <sup>2</sup>Maastricht University, Maastricht, the Netherlands; <sup>3</sup>Emory University, Atlanta, GA, US; <sup>4</sup>University of Minnesota, Minneapolis, MN, US; <sup>5</sup><i>BMJ</i>, London, UK; <sup>6</sup>London School of Hygiene and Tropical Medicine, London, UK; <sup>7</sup>Amsterdam University Medical Center, Amsterdam, the Netherlands; <sup>8</sup>Vrije Universiteit Amsterdam, Amsterdam, the Netherlands. <h4>Conflict of Interest Disclosures</h4> Caitlin J. Bakker is cochair of the National Information Standards Organization Communication of Retractions, Removals and Expressions of Concern Standing Committee. Lex Bouter is a member of the Peer Review Congress Advisory Board but was not involved in the review or decision for this abstract. No other disclosures were reported. <h4>Funding/Support</h4> This research is part of an ongoing PhD collaboration between The BMJ (British Medical Journal) and the team Meta-Research at Maastricht University (UM) on the responsible conduct of publishing scientific research. The BMJ is published by BMJ Group, a wholly owned subsidiary of the British Medical Association. UM is a public legal entity in the Netherlands. This study is part of Caitlin Bakker’s self-funded BMJ/UM PhD. No exchange of funds has taken place for this research project. <h4>Role of the Funder/Sponsor</h4> The authors are wholly responsible for the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the abstract; and decision to submit the abstract for presentation. <h4>Disclaimer</h4> All authors express their own opinions and not necessarily that of their employers.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,046
score de la tête « metaresearch » (Gemma)0,024
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict), Bibliométrie, Études des sciences et des technologies, Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesMétarecherche, Bibliométrie, Études des sciences et des technologies, Charge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,945
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0460,024
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0220,027
Études des sciences et des technologies0,0030,030
Communication savante0,0010,001
Science ouverte0,0030,001
Intégrité de la recherche0,0010,004
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,499
Tête enseignante GPT0,515
Écart entre enseignants0,015 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission2
Résumé présentoui

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