0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessAbstract Background Infectious diseases carry large global burdens and have implications for society at large. Therefore, reproducible, transparent research is extremely important. Methods We evaluated transparency indicators (code and data sharing, registration, and conflict and funding disclosures) in the 5340 PubMed Central Open Access articles published in 2019 or 2021 in the 9 most cited specialty journals in infectious diseases using the text-mining R package, rtransparent. Results A total of 5340 articles were evaluated (1860 published in 2019 and 3480 in 2021 [of which 1828 were on coronavirus disease 2019, or COVID-19]). Text mining identified code sharing in 98 (2%) articles, data sharing in 498 (9%), registration in 446 (8%), conflict of interest disclosures in 4209 (79%), and funding disclosures in 4866 (91%). There were substantial differences across the 9 journals: 1%–9% for code sharing, 5%–25% for data sharing, 1%–31% for registration, 7%–100% for conflicts of interest, and 65%–100% for funding disclosures. Validation-corrected imputed estimates were 3%, 11%, 8%, 79%, and 92%, respectively. There were no major differences between articles published in 2019 and non-COVID-19 articles in 2021. In 2021, non-COVID-19 articles had more data sharing (12%) than COVID-19 articles (4%). Conclusions Data sharing, code sharing, and registration are very uncommon in infectious disease specialty journals. Increased transparency is required.
Emmanuel A. Zavalis, Despina G. Contopoulos‐Ioannidis, John P A Ioannidis (2023). Transparency in Infectious Disease Research: Meta-research Survey of Specialty Journals. , 228(3), DOI: https://doi.org/10.1093/infdis/jiad130.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2023
Authors
3
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1093/infdis/jiad130
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access