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      COSMIN guideline for systematic reviews of patient-reported outcome measures

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          Abstract

          Purpose

          Systematic reviews of patient-reported outcome measures (PROMs) differ from reviews of interventions and diagnostic test accuracy studies and are complex. In fact, conducting a review of one or more PROMs comprises of multiple reviews (i.e., one review for each measurement property of each PROM). In the absence of guidance specifically designed for reviews on measurement properties, our aim was to develop a guideline for conducting systematic reviews of PROMs.

          Methods

          Based on literature reviews and expert opinions, and in concordance with existing guidelines, the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) steering committee developed a guideline for systematic reviews of PROMs.

          Results

          A consecutive ten-step procedure for conducting a systematic review of PROMs is proposed. Steps 1–4 concern preparing and performing the literature search, and selecting relevant studies. Steps 5–8 concern the evaluation of the quality of the eligible studies, the measurement properties, and the interpretability and feasibility aspects. Steps 9 and 10 concern formulating recommendations and reporting the systematic review.

          Conclusions

          The COSMIN guideline for systematic reviews of PROMs includes methodology to combine the methodological quality of studies on measurement properties with the quality of the PROM itself (i.e., its measurement properties). This enables reviewers to draw transparent conclusions and making evidence-based recommendations on the quality of PROMs, and supports the evidence-based selection of PROMs for use in research and in clinical practice.

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          Most cited references16

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          How to select outcome measurement instruments for outcomes included in a “Core Outcome Set” – a practical guideline

          Background In cooperation with the Core Outcome Measures in Effectiveness Trials (COMET) initiative, the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) initiative aimed to develop a guideline on how to select outcome measurement instruments for outcomes (i.e., constructs or domains) included in a “Core Outcome Set” (COS). A COS is an agreed minimum set of outcomes that should be measured and reported in all clinical trials of a specific disease or trial population. Methods Informed by a literature review to identify potentially relevant tasks on outcome measurement instrument selection, a Delphi study was performed among a panel of international experts, representing diverse stakeholders. In three consecutive rounds, panelists were asked to rate the importance of different tasks in the selection of outcome measurement instruments, to justify their choices, and to add other relevant tasks. Consensus was defined as being achieved when 70 % or more of the panelists agreed and when fewer than 15 % of the panelists disagreed. Results Of the 481 invited experts, 120 agreed to participate of whom 95 (79 %) completed the first Delphi questionnaire. We reached consensus on four main steps in the selection of outcome measurement instruments for COS: Step 1, conceptual considerations; Step 2, finding existing outcome measurement instruments, by means of a systematic review and/or a literature search; Step 3, quality assessment of outcome measurement instruments, by means of the evaluation of the measurement properties and feasibility aspects of outcome measurement instruments; and Step 4, generic recommendations on the selection of outcome measurement instruments for outcomes included in a COS (consensus ranged from 70 to 99 %). Conclusions This study resulted in a consensus-based guideline on the methods for selecting outcome measurement instruments for outcomes included in a COS. This guideline can be used by COS developers in defining how to measure core outcomes. Electronic supplementary material The online version of this article (doi:10.1186/s13063-016-1555-2) contains supplementary material, which is available to authorized users.
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            Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change

            Changes in scores on health status questionnaires are difficult to interpret. Several methods to determine minimally important changes (MICs) have been proposed which can broadly be divided in distribution-based and anchor-based methods. Comparisons of these methods have led to insight into essential differences between these approaches. Some authors have tried to come to a uniform measure for the MIC, such as 0.5 standard deviation and the value of one standard error of measurement (SEM). Others have emphasized the diversity of MIC values, depending on the type of anchor, the definition of minimal importance on the anchor, and characteristics of the disease under study. A closer look makes clear that some distribution-based methods have been merely focused on minimally detectable changes. For assessing minimally important changes, anchor-based methods are preferred, as they include a definition of what is minimally important. Acknowledging the distinction between minimally detectable and minimally important changes is useful, not only to avoid confusion among MIC methods, but also to gain information on two important benchmarks on the scale of a health status measurement instrument. Appreciating the distinction, it becomes possible to judge whether the minimally detectable change of a measurement instrument is sufficiently small to detect minimally important changes.
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              Physical activity questionnaires for youth: a systematic review of measurement properties.

              Because of the diversity in available questionnaires, it is not easy for researchers to decide which instrument is most suitable for his or her specific demands. Therefore, we systematically summarized and appraised studies examining measurement properties of self-administered and proxy-reported physical activity (PA) questionnaires in youth. Literature was identified through searching electronic databases (PubMed, EMBASE using 'EMBASE only' and SportDiscus) until May 2009. Studies were included if they reported on the measurement properties of self-administered and proxy-reported PA questionnaires in youth (mean age <18 years) and were published in the English language. Methodological quality and results of included studies was appraised using a standardized checklist (qualitative attributes and measurement properties of PA questionnaires [QAPAQ]). We included 54 manuscripts examining 61 versions of questionnaires. None of the included questionnaires showed both acceptable reliability and validity. Only seven questionnaires received a positive rating for reliability. Reported validity varied, with correlations between PA questionnaires and accelerometers ranging from very low to high (previous day PA recall: correlation coefficient [r] = 0.77). In general, PA questionnaires for adolescents correlated better with accelerometer scores than did those for children. From this systematic review, we conclude that no questionnaires were available with both acceptable reliability and validity. Considerably more high-quality research is required to examine the validity and reliability of promising PA questionnaires for youth.
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                Author and article information

                Contributors
                +31204445903 , c.prinsen@vumc.nl
                Journal
                Qual Life Res
                Qual Life Res
                Quality of Life Research
                Springer International Publishing (Cham )
                0962-9343
                1573-2649
                12 February 2018
                12 February 2018
                2018
                : 27
                : 5
                : 1147-1157
                Affiliations
                [1 ]ISNI 0000 0004 0435 165X, GRID grid.16872.3a, Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, , VU University Medical Center, ; De Boelelaan 1089a, 1081 HV Amsterdam, The Netherlands
                [2 ]ISNI 0000 0004 1767 9005, GRID grid.20522.37, Health Services Research Unit, , IMIM-Hospital del Mar Medical Research Institute; CIBER Epidemiología y Salud Pública (CIBERESP), ; Barcelona, Spain
                [3 ]ISNI 0000000122986657, GRID grid.34477.33, Department of Health Services, , University of Washington, ; Seattle, WA USA
                [4 ]ISNI 0000 0004 0435 165X, GRID grid.16872.3a, Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, , VU University Medical Center, ; P.O. Box 7057, 1007 MB Amsterdam, The Netherlands
                Author information
                http://orcid.org/0000-0002-0956-3788
                http://orcid.org/0000-0001-6489-2827
                http://orcid.org/0000-0002-2659-5482
                http://orcid.org/0000-0001-8627-9636
                http://orcid.org/0000-0003-0756-0492
                http://orcid.org/0000-0002-5454-2804
                http://orcid.org/0000-0003-4570-2826
                Article
                1798
                10.1007/s11136-018-1798-3
                5891568
                29435801
                26c3a949-4a3c-42fd-8451-7f14e46517db
                © The Author(s) 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 23 January 2018
                Funding
                Funded by: European Union’s Seventh Framework Programme [FP7/2007-2013]
                Award ID: 305081
                Award Recipient :
                Categories
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                Custom metadata
                © Springer International Publishing AG, part of Springer Nature 2018

                Public health
                cosmin,systematic review,measurement properties,prom,outcome measurement instrument,outcome measures,methodology

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