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• W4223921457 endingPage "1767" @default.
• W4223921457 startingPage "1755" @default.
• W4223921457 abstract "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.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.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.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." @default.
• W4223921457 created "2022-04-19" @default.
• W4223921457 creator A5010786185 @default.
• W4223921457 creator A5027563654 @default.
• W4223921457 creator A5072520929 @default.
• W4223921457 date "2022-06-19" @default.
• W4223921457 modified "2023-10-14" @default.
• W4223921457 title "Common measures or common metrics? A plea to harmonize measurement results" @default.
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• W4223921457 doi "https://doi.org/10.1002/cpp.2742" @default.
• W4223921457 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35421265" @default.

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