Reproducibility Policies in Cardiology Journals: The REPLICA Cross-Sectional Study
Notice bibliographique
Résumé
Abstract Importance Transparency and data sharing are valuable practices in research, contributing to improved precision and flexibility in cumulative evidence; and ultimately expanding the research ecosystem by addressing one of the philosophical research norms that implies that knowledge belongs to society. Objectives The objective of the Reproducibility Policies In Cardiology Journals (REPLICA) study was to estimate the proportions of policies and guidance for reproducibility and transparency practices among Cardiology journals, as well as to determine details of completeness of reporting and data sharing conditions whenever disclosed. Design Cross-sectional analysis. Setting Cross-sectional study through analyses of journals deposited in the National Library of Medicine (NLM) Catalog tagged with the “ Cardiology ” and “ Vascular Diseases ” entry terms. Eligibility Criteria Cardiology journals from the NLM Catalog database that published at least one randomized clinical trial in 2018. Journals that published articles in English, Spanish, French, or Portuguese and were available in MEDLINE/PubMed were eligible for inclusion. Exposures The exposures were mainly related to journal’s characteristics such as publisher operations characteristics (e.g., journal access only by subscription), indexation in the DOAJPlus, requirement for registration for RCTs, and others. Main outcomes and measures We prespecified a primary composite outcome composed of data-sharing policy or guidance. Secondary outcomes were proportions of reporting guidelines within the journal’s instructions for the author’s section (e.g., CONSORT), and also other components of sharing practices. Results We assessed 148 journals. Of them, 74 (50.0%, 95%CI 41.9% to 58.1%) presented policy or guidance for data sharing. We found guidance for data sharing in 68 journals (47.5% 95%CI 39.4% to 55.8%). Notably, among them, only two mentioned sharing individual participant data (IPD). Regarding guidelines for article reporting, we identified that 132 journals displayed guidance for authors, in which 27 (20.45%, 95%CI 14.34% to 28.29%) had CONSORT and EQUATOR Network guidance content. Conclusion and relevance In summary, we found a mild proportion of policies and guidance for data-sharing. Moreover, transparency practices inclined to RCTs are suboptimal, as mirrored by the very low prevalence of IPD data-sharing policy and guidance as well as specific reporting guidelines instructions for RCTs. Key Points Question What is the proportion of journals displaying policies and guidance about data sharing in cardiology journals? Findings We found a low prevalence of policy and guidance for data sharing in Cardiology journals, as well as transparency and reproducibility practices; details, individual participant data sharing, registration, and completeness of reporting, for example. Meaning Journals play a role in driving reproducibility and transparency among scientific areas. Stakeholders involved in the editorial processes should be open to understand the valuable impact of data-sharing practices and learn how to implement such mechanisms, that being the case.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,177 | 0,459 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,008 | 0,010 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,004 | 0,006 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».