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      Sample size used to validate a scale: a review of publications on newly-developed patient reported outcomes measures

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          Abstract

          Purpose

          New patient reported outcome (PRO) measures are regularly developed to assess various aspects of the patients’ perspective on their disease and treatment. For these instruments to be useful in clinical research, they must undergo a proper psychometric validation, including demonstration of cross-sectional and longitudinal measurement properties. This quantitative evaluation requires a study to be conducted on an appropriate sample size. The aim of this research was to list and describe practices in PRO and proxy PRO primary psychometric validation studies, focusing primarily on the practices used to determine sample size.

          Methods

          A literature review of articles published in PubMed between January 2009 and September 2011 was conducted. Three selection criteria were applied including a search strategy, an article selection strategy, and data extraction. Agreements between authors were assessed, and practices of validation were described.

          Results

          Data were extracted from 114 relevant articles. Within these, sample size determination was low (9.6%, 11/114), and were reported as either an arbitrary minimum sample size (n = 2), a subject to item ratio (n = 4), or the method was not explicitly stated (n = 5). Very few articles (4%, 5/114) compared a posteriori their sample size to a subject to item ratio. Content validity, construct validity, criterion validity and internal consistency were the most frequently measurement properties assessed in the validation studies.

          Approximately 92% of the articles reported a subject to item ratio greater than or equal to 2, whereas 25% had a ratio greater than or equal to 20. About 90% of articles had a sample size greater than or equal to 100, whereas 7% had a sample size greater than or equal to 1000.

          Conclusions

          The sample size determination for psychometric validation studies is rarely ever justified a priori. This emphasizes the lack of clear scientifically sound recommendations on this topic. Existing methods to determine the sample size needed to assess the various measurement properties of interest should be made more easily available.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12955-014-0176-2) contains supplementary material, which is available to authorized users.

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          Most cited references24

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          How to Use a Monte Carlo Study to Decide on Sample Size and Determine Power

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            The Scientific Use of Factor Analysis in Behavioral and Life Sciences

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              Robustness Studies in Covariance Structure Modeling: An Overview and a Meta-Analysis

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                Author and article information

                Contributors
                emmanuelle.anthoine@chu-nantes.fr
                leila.moret@chu-nantes.fr
                aregnault@mapigroup.com
                veronique.sebille@univ-nantes.fr
                jean-benoit.hardouin@univ-nantes.fr
                Journal
                Health Qual Life Outcomes
                Health Qual Life Outcomes
                Health and Quality of Life Outcomes
                BioMed Central (London )
                1477-7525
                9 December 2014
                9 December 2014
                2014
                : 12
                : 1
                : 2
                Affiliations
                [ ]Public Health Department, University Hospital of Nantes, 85, rue Saint Jacques, 44093 Nantes Cedex 1, France
                [ ]EA 4275 SPHERE “bioStatistics, Pharmacoepidemiology and Human sciEnces Research tEam”, University of Nantes, 1, rue Gaston Veil, 44035 Nantes Cedex 1, France
                [ ]Biometry Platform, University Hospital of Nantes, 5, Allée de l’Ile Gloriette, 44093 Nantes Cedex 1, France
                [ ]Mapi HEOR & Strategic Market Access, 27 rue de la Villette, 69003 Lyon, France
                Article
                176
                10.1186/s12955-014-0176-2
                4275948
                25492701
                8fc0bcc2-dc60-45a1-bb65-b621bcc3a044
                © Anthoine et al.; licensee BioMed Central Ltd. 2014

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 24 July 2014
                : 20 November 2014
                Categories
                Review
                Custom metadata
                © The Author(s) 2014

                Health & Social care
                psychometrics,review,sample size,scale,health status,validation
                Health & Social care
                psychometrics, review, sample size, scale, health status, validation

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