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COSMIN Risk of Bias tool to assess the quality of studies on reliability or measurement error of outcome measurement instruments: a Delphi study
Open accessPublished version of a preprint
Abstract
Background: Scores on an outcome measurement instrument depend on the type and settings of the instrument used, how instructions are given to patients, how professionals administer and score the instrument, etc. The impact of all these sources of variation on scores can be assessed in studies on reliability and measurement error, if properly designed and analyzed. The aim of this study was to develop standards to assess the quality of studies on reliability and measurement error of clinician-reported outcome measurement instruments, performance-based outcome measurement instrument, and laboratory values. Methods: We conducted a 3-round Delphi study involving 52 panelists. Results: Consensus was reached on how a comprehensive research question can be deduced from the design of a reliability study to determine how the results of a study inform us about the quality of the outcome measurement instrument at issue. Consensus was reached on components of outcome measurement instruments, i.e. the potential sources of variation. Next, we reached consensus on standards on design requirements ( n = 5), standards on preferred statistical methods for reliability ( n = 3) and measurement error ( n = 2), and their ratings on a four-point scale. There was one term for a component and one rating of one standard on which no consensus was reached, and therefore required a decision by the steering committee. Conclusion: We developed a tool that enables researchers with and without thorough knowledge on measurement properties to assess the quality of a study on reliability and measurement error of outcome measurement instruments.
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Metadata
- Authors
- Mokkink, L. B., Boers, M., van der Vleuten, C. P. M., Bouter, L. M., Alonso, J., Patrick, D. L., de Vet, H. C. W., & Terwee, C. B.
- Affiliations
- Amsterdam Public Health (NL)
- Universitat Pompeu Fabra (ES)
- University of Washington (US)
- Corresponding author
- Mokkink, L. B.
- Venue
- BMC Medical Research Methodology
- Published
- 2020-12
- Volume
- 20
- Issue
- 1
- Pages
- 293-293
- ISSN
- 1471-2288 (ISSN-L)
- PMC
- PMC7712525
- OpenAlex
- W3107903990
- Cited by
- 588
- References
- 31
- Citations by year
- 2026: 106 · 2025: 121 · 2024: 149 · 2023: 101 · 2022: 72 · 2021: 37 · 2020: 2
- FWCI
- 32.32
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Medical Research Methodology (publishedVersion, cc-by)
- Research Square (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, cc-by)
- VU Research Portal (publishedVersion, other-oa)
- Pure Amsterdam UMC (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (submittedVersion)
- Repositori digital de la UPF (Universitat Pompeu Fabra) (submittedVersion, cc-by)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (91617098)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Reliability and Agreement in Measurement
- Social Sciences › Sociology and Political Science › Delphi Technique in Research
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- COSMIN, risk of bias, reliability statistics, measurement error, outcome measurement instruments, clinician-reported outcomes, performance-based outcome measures, laboratory parameters, study quality assessment, Delphi consensus, measurement properties
- MeSH terms
- Delphi Technique, Humans, Reproducibility of Results, Bias, Consensus
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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