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Psychometric behaviour of the strengths and difficulties questionnaire (SDQ) in the Spanish national health survey 2006

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      Abstract

      BackgroundThe Strengths and Difficulties Questionnaire (SDQ) is a tool to measure the risk for mental disorders in children. The aim of this study is to describe the diagnostic efficiency and internal structure of the SDQ in the sample of children studied in the Spanish National Health Survey 2006.MethodsA representative sample of 6,773 children aged 4 to 15 years was studied. The data were obtained using the Minors Questionnaire in the Spanish National Health Survey 2006. The ROC curve was constructed and calculations made of the area under the curve, sensitivity, specificity and the Youden J indices. The factorial structure was studied using models of exploratory factorial analysis (EFA) and confirmatory factorial analysis (CFA).ResultsThe prevalence of behavioural disorders varied between 0.47% and 1.18% according to the requisites of the diagnostic definition. The area under the ROC curve varied from 0.84 to 0.91 according to the diagnosis. Factor models were cross-validated by means of two different random subsamples for EFA and CFA. An EFA suggested a three correlated factor model. CFA confirmed this model. A five-factor model according to EFA and the theoretical five-factor model described in the bibliography were also confirmed. The reliabilities of the factors of the different models were acceptable (>0.70, except for one factor with reliability 0.62).ConclusionsThe diagnostic behaviour of the SDQ in the Spanish population is within the working limits described in other countries. According to the results obtained in this study, the diagnostic efficiency of the questionnaire is adequate to identify probable cases of psychiatric disorders in low prevalence populations. Regarding the factorial structure we found that both the five and the three factor models fit the data with acceptable goodness of fit indexes, the latter including an externalization and internalization dimension and perhaps a meaningful positive social dimension.Accordingly, we recommend studying whether these differences depend on sociocultural factors or are, in fact, due to methodological questions.

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      Most cited references 19

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      Psychometric properties of the strengths and difficulties questionnaire.

      To describe the psychometric properties of the Strengths and Difficulties Questionnaire (SDQ), a brief measure of the prosocial behavior and psychopathology of 3-16-year-olds that can be completed by parents, teachers, or youths. A nationwide epidemiological sample of 10,438 British 5-15-year-olds obtained SDQs from 96% of parents, 70% of teachers, and 91% of 11-15-year-olds. Blind to the SDQ findings, all subjects were also assigned DSM-IVdiagnoses based on a clinical review of detailed interview measures. The predicted five-factor structure (emotional, conduct, hyperactivity-inattention, peer, prosocial) was confirmed. Internalizing and externalizing scales were relatively "uncontaminated" by one another. Reliability was generally satisfactory, whether judged by internal consistency (mean Cronbach a: .73), cross-informant correlation (mean: 0.34), or retest stability after 4 to 6 months (mean: 0.62). SDQ scores above the 90th percentile predicted a substantially raised probability of independently diagnosed psychiatric disorders (mean odds ratio: 15.7 for parent scales, 15.2 for teacher scales, 6.2 for youth scales). The reliability and validity of the SDQ make it a useful brief measure of the adjustment and psychopathology of children and adolescents.
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        Using the Strengths and Difficulties Questionnaire (SDQ) to screen for child psychiatric disorders in a community sample.

        Child psychiatric disorders are common and treatable, but often go undetected and therefore remain untreated. To assess the Strengths and Difficulties Questionnaire (SDQ) as a potential means for improving the detection of child psychiatric disorders in the community. SDQ predictions and independent psychiatric diagnoses were compared in a community sample of 7984 5- to 15-year-olds from the 1999 British Child Mental Health Survey. Multi-informant (parents, teachers, older children) SDQs identified individuals with a psychiatric diagnosis with a specificity of 94.6% (95% Cl 94.1-95.1%) and a sensitivity of 63.3% (59.7-66.9%). The questionnaires identified over 70% of individuals with conduct, hyperactivity, depressive and some anxiety disorders, but under 50% of individuals with specific phobias, separation anxiety and eating disorders. Sensitivity was substantially poorer with single-informant rather than multi-informant SDQs. Community screening programmes based on multi-informant SDQs could potentially increase the detection of child psychiatric disorders, thereby improving access to effective treatments.
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          FACTOR: a computer program to fit the exploratory factor analysis model.

          Exploratory factor analysis (EFA) is one of the most widely used statistical procedures in psychological research. It is a classic technique, but statistical research into EFA is still quite active, and various new developments and methods have been presented in recent years. The authors of the most popular statistical packages, however, do not seem very interested in incorporating these new advances. We present the program FACTOR, which was designed as a general, user-friendly program for computing EFA. It implements traditional procedures and indices and incorporates the benefits of some more recent developments. Two of the traditional procedures implemented are polychoric correlations and parallel analysis, the latter of which is considered to be one of the best methods for determining the number of factors or components to be retained. Good examples of the most recent developments implemented in our program are (1) minimum rank factor analysis, which is the only factor method that allows one to compute the proportion of variance explained by each factor, and (2) the simplimax rotation method, which has proved to be the most powerful rotation method available. Of these methods, only polychoric correlations are available in some commercial programs. A copy of the software, a demo, and a short manual can be obtained free of charge from the first author.
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            Author and article information

            Affiliations
            [1 ]Teaching Unit of Psychiatry and Psychological Medicine, Department of Medicine, University of Valencia, Valencia, Spain
            [2 ]CIBERSAM, Instituto de Salud Carlos III, Madrid, Spain
            [3 ]Research Unit for the Analysis of Mortality and Health Statistics, University of Alicante, Alicante, Spain
            [4 ]Burriana Center of Mental Health, Burriana, Spain
            [5 ]Paterna Center of Mental Health, Paterna, Spain
            [6 ]CIBERSAM, Instituto de Salud Carlos III, Madrid, Spain
            [7 ]Department of Clinical Medicine, Universitat Miguel Hernández, Sant Joan d’Alacant, Spain
            Contributors
            Journal
            BMC Psychiatry
            BMC Psychiatry
            BMC Psychiatry
            BioMed Central
            1471-244X
            2013
            22 March 2013
            : 13
            : 95
            23522343
            3623874
            1471-244X-13-95
            10.1186/1471-244X-13-95
            Copyright © 2013 Gómez-Beneyto et al.; licensee BioMed Central Ltd.

            This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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