Increasing value and reducing waste: addressing inaccessible research
Open accessAbstract
The study protocol, publications, full study report detailing all analyses, and participant-level dataset constitute the main documentation of methods and results for health research. However, journal publications are available for only half of all studies and are plagued by selective reporting of methods and results. The protocol, full study report, and participant-level dataset are rarely available. The quality of information provided in study protocols and reports is variable and often incomplete. Inaccessibility of full information for the vast majority of studies wastes billions of dollars, introduces bias, and has a detrimental impact on patient care and research. To help improve this situation at a systemic level, three main actions are warranted. Firstly, it is important that academic institutions and funders reward investigators who fully disseminate their research protocols, reports, and participant-level datasets. Secondly, standards for the content of protocols, full study reports, and data sharing practices should be rigorously developed and adopted for all types of health research. Finally, journals, funders, sponsors, research ethics committees, regulators, and legislators should implement and enforce policies supporting study registration and availability of journal publications, full study reports, and participant-level datasets.
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Protocol registration is applicable to and recommended for all studies and is supported by various platforms, such as the Open Science Framework.
“However, protocol registration is applicable to and recommended for all studies and is supported by various platforms, such as the Open Science Framework [3, 29, 35–37].”
From Assessing transparency practices in dental randomized controlled trials (2024) · cites this paper as [36]
Recommendation 3 (page not available) calls for study registration across all health research, and “Identification of unpublished research” extends the discussion beyond clinical trials to systematic reviews, observational research, and preclinical experiments. The paper discusses registry infrastructure but does not identify the Open Science Framework as a platform; its recommendation is also framed around health research rather than all studies without qualification. (LLM, conf=0.86)
Experimental — accuracy not yet measuredStudies with statistically non-significant results may not have been submitted for publication, or particular results that were statistically non-significant may have been omitted from study reports.
“studies with statistically non-significant results may not have been submitted for publication (publication bias), or particular results that were statistically non-significant may have been omitted from study reports (selective non-reporting bias).”
From PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews (2021) · cites this paper as [82]
Full documentation of research, including protocols for sharing data and code, increases the value of research that is undertaken.
“Recent reports on waste in research have highlighted that full documentation of research, including protocols for sharing data and code, increase the value of research that is undertaken.20,21”
From Guidelines for accurate and transparent health estimates reporting: the GATHER statement (2016) · cites this paper as [21]
A high proportion of clinical trials remain unpublished.
“However, a high proportion of clinical trials remain unpublished.112 113”
From SPIRIT 2025 explanation and elaboration: updated guideline for protocols of randomised trials (2025) · cites this paper as [112]
The medical literature represents a biased subset of existing data, potentially leading to overestimation of benefits, underestimation of harms, and detrimental impact on patient care and research.
“Overall, the medical literature represents a biased subset of existing data, potentially leading to overestimation of benefits, underestimation of harms, and a detrimental impact on patient care and research.112 117 118”
From SPIRIT 2025 explanation and elaboration: updated guideline for protocols of randomised trials (2025) · cites this paper as [112]
Positive or statistically significant studies are published more often, on average, than studies with null or negative findings.
“These investigations have found that, on average, studies with statistically significant or “positive” results are more likely to be published than null or “negative” studies (Figure 1).”
From Investigating and dealing with publication bias and other reporting biases in meta-analyses of health research: a review (2021) · cites this paper as [8]
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Self-citation
Flagged first, then by citations
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- Authors
- Chan, A.-W., Song, F., Vickers, A., Jefferson, T., Dickersin, K., Gøtzsche, P. C., Krumholz, H. M., Ghersi, D., & van der Worp, H. B.
- Affiliations
- University of Toronto (CA)
- University of East Anglia (GB)
- Memorial Sloan Kettering Cancer Center (US)
- Cochrane (GB)
- Johns Hopkins University (US)
- Rigshospitalet (DK)
- Yale New Haven Hospital (US)
- National Health and Medical Research Council (AU)
- Corresponding author
- Chan, An-Wen
- ORCID
- Venue
- The Lancet
- Publisher
- Elsevier BV
- Published
- 2014-01
- Volume
- 383
- Issue
- 9913
- Pages
- 257-266
- ISSN
- 0099-5355 (ISSN-L)
- 0140-6736
- PMC
- PMC4533904
- OpenAlex
- W2122908200
- Semantic Scholar
- 3241e3add9399cf4609c0e81c7cee6628eda6b90
- Cited by
- 887
- References
- 116
- Citations by year
- 2026: 20 · 2025: 47 · 2024: 60 · 2023: 54 · 2022: 71 · 2021: 116 · 2020: 71 · 2019: 74 · 2018: 68 · 2017: 84 · 2016: 103 · 2015: 69 · 2014: 48
- FWCI
- 280.19
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- The Lancet (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- UEA Digital Repository (University of East Anglia) (acceptedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Funders
- Prostate Cancer Foundation
- Yale University
- Foundation for Cardiovascular Research
- National Institutes of Health
- Sidney Kimmel Center for Prostate and Urologic Cancers
- National Cancer Institute (P50 CA92629, P30CA008748, P50CA092629)
- Topics
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- 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 transparency, research registration, selective reporting, data sharing, research waste, research funding incentives, research ethics committees, science policy
- MeSH terms
- Clinical Trials as Topic, Humans, Periodicals as Topic, Publishing, Research Design, Publication Bias, Access to Information, Information Dissemination, Biomedical Research
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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