Common measures or common metrics? A plea to harmonize measurement results
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Objective: There is a great variety of measurement instruments to assess similar constructs in clinical research and practice. This complicates the interpretation of test results and hampers the implementation of measurement‐based care. Method: For reporting and discussing test results with patients, we suggest converting test results into universally applicable common metrics. Two well‐established metrics are reviewed: T scores and percentile ranks. Their calculation is explained, their merits and drawbacks are discussed, and recommendations for the most convenient reference group are provided. Results: We propose to express test results as T scores with the general population as reference group. To elucidate test results to patients, T scores may be supplemented with percentile ranks, based on data from a clinical sample. The practical benefits are demonstrated using the published data of four frequently used instruments for measuring depression: the CES‐D, PHQ‐9, BDI‐II and the PROMIS depression measure. Discussion: Recent initiatives have proposed to mandate a limited set of outcome measures to harmonize clinical measurement. However, the selected instruments are not without flaws and, potentially, this directive may hamper future instrument development. We recommend using common metrics as an alternative approach to harmonize test results in clinical practice, as this will facilitate the integration of measures in day‐to‐day practice.
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Cited by
Sorted by citations
Stein, D. J., Craske, M. G., Rothbaum, B. O., Chamberlain, S. R., Fineberg, N. A., Choi, K. W., de Jonge, P., Baldwin, D. S., & Maj, M. (2021) · World Psychiatry · doi:10.1002/wps.20919 · Cited by 60 · see citing works
Measuring the active elements of cognitive-behavioral therapies
Cohen, Z. D., Barnes-Horowitz, N. M., Forbes, C. N., & Craske, M. G. (2023) · Behaviour Research and Therapy · doi:10.1016/j.brat.2023.104364 · Cited by 58 · see citing works
Sierk, A., Travers, E., Economides, M., Loe, B. S., Sun, L., & Bolton, H. (2022) · JMIR Mental Health · doi:10.2196/34103 · Cited by 21 · see citing works
- Authors
- de Beurs, E., Boehnke, J. R., & Fried, E. I.
- Affiliations
- Department of Clinical Psychology Leiden University & Arkin GGZ Amsterdam The Netherlands
- University of Dundee (GB)
- Leiden University (NL)
- Venue
- Clinical Psychology & Psychotherapy
- Publisher
- Wiley
- Published
- 2022-06-19
- Volume
- 29
- Issue
- 5
- Pages
- 1755-1767
- ISSN
- 1063-3995 (ISSN-L)
- 1099-0879
- PMC
- PMC9796399
- OpenAlex
- W4223921457
- Cited by
- 55
- References
- 18
- Citations by year
- 2026: 15 · 2025: 6 · 2024: 12 · 2023: 12 · 2022: 6 · 2021: 4
- FWCI
- 5.51
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Clinical Psychology & Psychotherapy (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Discovery Research Portal (University of Dundee) (publishedVersion, cc-by-nc-nd)
- Leiden Repository (Leiden University) (submittedVersion, cc-by-nc-nd)
- Discovery Research Portal (University of Dundee) (submittedVersion, cc-by)
- PsyArXiv (OSF Preprints) (submittedVersion)
- PsyArXiv (OSF Preprints) (submittedVersion, cc-by)
- Data Archiving and Networked Services (DANS) (submittedVersion, cc-by-nc-nd)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Psychology › Applied Psychology › Psychological Testing and Assessment
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Keywords
- common metric, T-score, percentile ranks, measurement-based care, depression assessment, outcome measure standardization, CES-D, PHQ-9, Beck Depression Inventory-II, reference groups
- MeSH terms
- Depression, Depressive Disorder, Humans, Psychometrics, Reproducibility of Results, Benchmarking
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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.
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