Establishing Institutional Scores With the Rigor and Transparency Index: Large-scale Analysis of Scientific Reporting Quality
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Abstract
Background: Improving rigor and transparency measures should lead to improvements in reproducibility across the scientific literature; however, the assessment of measures of transparency tends to be very difficult if performed manually. Objective: This study addresses the enhancement of the Rigor and Transparency Index (RTI, version 2.0), which attempts to automatically assess the rigor and transparency of journals, institutions, and countries using manuscripts scored on criteria found in reproducibility guidelines (eg, Materials Design, Analysis, and Reporting checklist criteria). Methods: The RTI tracks 27 entity types using natural language processing techniques such as Bidirectional Long Short-term Memory Conditional Random Field–based models and regular expressions; this allowed us to assess over 2 million papers accessed through PubMed Central. Results: Between 1997 and 2020 (where data were readily available in our data set), rigor and transparency measures showed general improvement (RTI 2.29 to 4.13), suggesting that authors are taking the need for improved reporting seriously. The top-scoring journals in 2020 were the Journal of Neurochemistry (6.23), British Journal of Pharmacology (6.07), and Nature Neuroscience (5.93). We extracted the institution and country of origin from the author affiliations to expand our analysis beyond journals. Among institutions publishing >1000 papers in 2020 (in the PubMed Central open access set), Capital Medical University (4.75), Yonsei University (4.58), and University of Copenhagen (4.53) were the top performers in terms of RTI. In country-level performance, we found that Ethiopia and Norway consistently topped the RTI charts of countries with 100 or more papers per year. In addition, we tested our assumption that the RTI may serve as a reliable proxy for scientific replicability (ie, a high RTI represents papers containing sufficient information for replication efforts). Using work by the Reproducibility Project: Cancer Biology, we determined that replication papers (RTI 7.61, SD 0.78) scored significantly higher (P<.001) than the original papers (RTI 3.39, SD 1.12), which according to the project required additional information from authors to begin replication efforts. Conclusions: These results align with our view that RTI may serve as a reliable proxy for scientific replicability. Unfortunately, RTI measures for journals, institutions, and countries fall short of the replicated paper average. If we consider the RTI of these replication studies as a target for future manuscripts, more work will be needed to ensure that the average manuscript contains sufficient information for replication attempts.
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Cites
Estimating the reproducibility of psychological science
Open Science Collaboration (2015) · Science · doi:10.1126/science.aac4716 · Cited by 8,515 · see citing works
The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research
Percie du Sert, N., Hurst, V., Ahluwalia, A., Alam, S., Avey, M. T., Baker, M., Browne, W. J., Clark, A., Cuthill, I. C., Dirnagl, U., et al. (2020) · PLOS Biology · doi:10.1371/journal.pbio.3000410 · Cited by 5,939 · see citing works
Raise standards for preclinical cancer research
Begley, C. G., & Ellis, L. M. (2012) · Nature · doi:10.1038/483531a · Cited by 2,979 · cited 3× · see citing works
“However, over the last decade, numerous reports on research irreproducibility have shed light on a lingering problem, one that is proving to be both troublesome and costly [1-5].”
BackgroundResultPromoting an open research culture
Nosek, B. A., Alter, G., Banks, G. C., Borsboom, D., Bowman, S. D., Breckler, S. J., Buck, S., Chambers, C. D., Chin, G., Christensen, G., et al. (2015) · Science · doi:10.1126/science.aab2374 · Cited by 2,708 · see citing works
A call for transparent reporting to optimize the predictive value of preclinical research
Landis, S. C., Amara, S. G., Asadullah, K., Austin, C. P., Blumenstein, R., Bradley, E. W., Crystal, R. G., Darnell, R. B., Ferrante, R. J., Fillit, H., et al. (2012) · Nature · doi:10.1038/nature11556 · Cited by 1,196 · see citing works
The economics of reproducibility in preclinical research
Freedman, L. P., Cockburn, I. M., & Simcoe, T. S. (2015) · PLOS Biology · doi:10.1371/journal.pbio.1002165 · Cited by 1,055 · see citing works
Schweppe, R. E., Klopper, J. P., Korch, C., Pugazhenthi, U., Benezra, M., Knauf, J. A., Fagin, J. A., Marlow, L. A., Copland, J. A., Smallridge, R. C., et al. (2008) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2008-1102 · Cited by 563 · see citing works
Scientific literature: Information overload
Landhuis, E. (2016) · Nature · doi:10.1038/nj7612-457a · Cited by 324 · see citing works
Vasilevsky, N. A., Brush, M. H., Paddock, H., Ponting, L., Tripathy, S. J., LaRocca, G. M., & Haendel, M. A. (2013) · PeerJ · doi:10.7717/peerj.148 · Cited by 271 · see citing works
Assessment of transparency indicators across the biomedical literature: How open is open?
Serghiou, S., Contopoulos-Ioannidis, D. G., Boyack, K. W., Riedel, N., Wallach, J. D., & Ioannidis, J. P. A. (2021) · PLOS Biology · doi:10.1371/journal.pbio.3001107 · Cited by 139 · see citing works
Investigation of Cross-Contamination and Misidentification of 278 Widely Used Tumor Cell Lines
Huang, Y., Liu, Y., Zheng, C., & Shen, C. (2017) · PLOS ONE · doi:10.1371/journal.pone.0170384 · Cited by 105 · cited 1× · see citing works
“Misidentified and contaminated cell lines continue to be a significant problem, with reported use rates varying between 10% and 50% [49-51].”
BackgroundMacleod, M., Collings, A. M., Graf, C., Kiermer, V., Mellor, D., Swaminathan, S., Sweet, D., & Vinson, V. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2103238118 · Cited by 77 · see citing works
Human Biosample Authentication Using the High-Throughput, Cost-Effective SNPtraceTM System
Liang-Chu, M. M. Y., Yu, M., Haverty, P. M., Koeman, J., Ziegle, J., Lee, M., Bourgon, R., & Neve, R. M. (2015) · PLOS ONE · doi:10.1371/journal.pone.0116218 · Cited by 62 · see citing works
Weissgerber, T., Riedel, N., Kilicoglu, H., Labbé, C., Eckmann, P., ter Riet, G., Byrne, J., Cabanac, G., Capes-Davis, A., Favier, B., et al. (2021) · Nature Medicine · doi:10.1038/s41591-020-01203-7 · Cited by 57 · see citing works
Self-citationCeL-ID: cell line identification using RNA-seq data
Mohammad, T. A., Tsai, Y. S., Ameer, S., Chen, H.-I. H., Chiu, Y.-C., & Chen, Y. (2019) · BMC Genomics · doi:10.1186/s12864-018-5371-9 · Cited by 19 · see citing works
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Open Science 2.0: Towards a truly collaborative research ecosystem
Thibault, R. T., Amaral, O. B., Argolo, F., Bandrowski, A. E., Davidson, A. R., & Drude, N. I. (2023) · PLOS Biology · doi:10.1371/journal.pbio.3002362 · Cited by 72 · see citing works
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- Authors
- Menke, J., Eckmann, P., Ozyurt, I. B., Roelandse, M., Anderson, N., Grethe, J., Gamst, A., & Bandrowski, A.
- Affiliations
- University of California San Diego (US)
- Corresponding author
- Bandrowski, Anita
- ORCID
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2022-06-27
- Volume
- 24
- Issue
- 6
- Pages
- e37324
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC9274430
- OpenAlex
- W4281393074
- Cited by
- 25
- References
- 15
- Citations by year
- 2026: 6 · 2025: 3 · 2024: 4 · 2023: 6 · 2022: 6
- FWCI
- 2.86
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- National Institutes of Health (5u24da039832-02, 1r43od024432-01, DA039832, U24 DK097771/DK/NIDDK, DK097771, U24 DA039832/DA/NIDA, U24DK097771)
- National Institute of Mental Health (R44MH119094)
- National Institute on Drug Abuse (DA039832, U24-DA039832)
- National Institute of General Medical Sciences (R24GM144308)
- National Institute of Diabetes and Digestive and Kidney Diseases (DK097771, U24DK097771)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
- Social Sciences › Decision Sciences › Information Systems and Management › Academic Publishing and Open Access
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- research reproducibility, research transparency, research rigor, natural language processing, entity recognition, replication study, open access publications, PubMed Central, author affiliation
- MeSH terms
- Humans, Norway, Publishing, Research Design, Reproducibility of Results, Checklist
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