+1 Recommend
0 collections
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Factor structure and measurement invariance across various demographic groups and over time for the PHQ-9 in primary care patients in Spain


      Read this article at

          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.


          The Patient Health Questionnaire (PHQ-9) is a widely-used screening tool for depression in primary care settings. The purpose of the present study is to identify the factor structure of the PHQ-9 and to examine the measurement invariance of this instrument across different sociodemographic groups and over time in a sample of primary care patients in Spain. Data came from 836 primary care patients enrolled in a randomized controlled trial (PsicAP study) and a subsample of 218 patients who participated in a follow-up assessment at 3 months. Confirmatory factor analysis (CFA) was used to test one- and two-factor structures identified in previous studies. Analyses of multiple-group invariance were conducted to determine the extent to which the factor structure is comparable across various demographic groups (i.e., gender, age, marital status, level of education, and employment situation) and over time. Both one-factor and two-factor re-specified models met all the pre-established fit criteria. However, because the factors identified in the two-factor model were highly correlated ( r = .86), the one-factor model was preferred for its parsimony. Multi-group CFA indicated measurement invariance across different demographic groups and across time. The present findings suggest that physicians in Spain can use the PHQ-9 to obtain a global score for depression severity in different demographic groups and to reliably monitor changes over time in the primary care setting.

          Related collections

          Most cited references29

          • Record: found
          • Abstract: found
          • Article: not found

          Prevalence of mental disorders in Europe: results from the European Study of the Epidemiology of Mental Disorders (ESEMeD) project.

          To describe the 12-month and lifetime prevalence rates of mood, anxiety and alcohol disorders in six European countries. A representative random sample of non-institutionalized inhabitants from Belgium, France, Germany, Italy, the Netherlands and Spain aged 18 or older (n = 21425) were interviewed between January 2001 and August 2003. DSM-IV disorders were assessed by lay interviewers using a revised version of the Composite International Diagnostic Interview (WMH-CIDI). Fourteen per cent reported a lifetime history of any mood disorder, 13.6% any anxiety disorder and 5.2% a lifetime history of any alcohol disorder. More than 6% reported any anxiety disorder, 4.2% any mood disorder, and 1.0% any alcohol disorder in the last year. Major depression and specific phobia were the most common single mental disorders. Women were twice as likely to suffer 12-month mood and anxiety disorders as men, while men were more likely to suffer alcohol abuse disorders. ESEMeD is the first study to highlight the magnitude of mental disorders in the six European countries studied. Mental disorders were frequent, more common in female, unemployed, disabled persons, or persons who were never married or previously married. Younger persons were also more likely to have mental disorders, indicating an early age of onset for mood, anxiety and alcohol disorders.
            • Record: found
            • Abstract: found
            • Article: not found

            Psychometric comparison of PHQ-9 and HADS for measuring depression severity in primary care.

            The 2004 National Institute for Health and Clinical Excellence (NICE) guidelines highlight the importance of assessing severity of depression in primary care. To assess the psychometric properties of the Patient Health Questionnaire (PHQ-9) and the depression subscale of the Hospital Anxiety and Depression Scale (HADS-D) for measuring depression severity in primary care. Psychometric assessment. Thirty-two general practices in Grampian, Scotland. Consecutive patients referred to a primary care mental health worker completed the PHQ-9 and HADS at baseline (n = 1063) and at the end of treatment (n = 544). Data were analysed to assess reliability, robustness of factor structure, convergent/discriminant validity, convergence of severity banding, and responsiveness to change. Both scales demonstrated high internal consistency at baseline and end of treatment (PHQ-9 alpha = 0.83 and 0.92; HADS-D alpha = 0.84 and 0.89). One factor emerged each for the PHQ-9 (explaining 42% of variance) and HADS-D (explaining 52% of variance). Both scales converged more with each other than with the HADS anxiety (HADS-A) subscale at baseline (P<0.001) and at end of treatment (P = 0.01). Responsiveness to change was similar: effect size for PHQ-9 = 0.99 and for the HADS-D = 1. The HADS-D and PHQ-9 differed significantly in categorising severity of depression, with the PHQ-9 categorising a greater proportion of patients with moderate/severe depression (P<0.001). The HADS-D and PHQ-9 demonstrated reliability, convergent/discriminant validity, and responsiveness to change. However, they differed considerably in how they catergorised severity. Given that treatment decisions are made on the basis of severity, further work is needed to assess the validity of the scales' severity cut-off bands.
              • Record: found
              • Abstract: found
              • Article: not found

              An essay on measurement and factorial invariance.

              Analysis of subgroups such as different ethnic, language, or education groups selected from among a parent population is common in health disparities research. One goal of such analyses is to examine measurement equivalence, which includes both qualitative review of the meaning of items as well as quantitative examination of different levels of factorial invariance and differential item functioning. The purpose of this essay is to review the definitions and assumptions associated with factorial invariance, placing this formulation in the context of bias, fairness, and equity. The connection between the concepts of factorial invariance and item bias (differential item functioning) using a variant of item response theory is discussed. The situations under which different forms of invariance (weak, strong, and strict) are required are discussed. Establishing factorial invariance involves a hierarchy of levels that include tests of weak, strong, and strict invariance. Pattern (metric or weak) factorial invariance implies that the regression slopes are invariant across groups. Pattern invariance requires only invariant factor loadings. Strong factorial invariance implies that the conditional expectation of the response, given the common and specific factors, is invariant across groups. Strong factorial invariance requires that specific factor means (represented as invariant intercepts) also be identical across groups. Strict factorial invariance implies that, in addition, the conditional variance of the response, given the common and specific factors, is invariant across groups. Strict factorial invariance requires that, in addition to equal factor loadings and intercepts, the residual (specific factor plus error variable) variances are equivalent across groups. The concept of measurement invariance that is most closely aligned to that of item response theory considers the latent variable as a common factor measured by manifest variables; the specific factors can be characterized as nuisance variables. Invariance of factor loadings across studied groups is required for valid comparisons of scale score or latent variable means. Strong and strict invariance may be less important in the context of basic research in which group differences in specific factors are indicative of individual differences that are important for scientific exploration. However, for most applications in which the aim is to ensure fairness and equity, strict factorial invariance is required. Health disparities research often focuses on self-reported clinical outcomes such as quality of life that are not observed directly. Latent variable models such as factor analyses are central to establishing valid assessment of such outcomes.

                Author and article information

                Role: Funding acquisitionRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Writing – review & editing
                Role: ConceptualizationRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: Editor
                PLoS One
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                23 February 2018
                : 13
                : 2
                : e0193356
                [1 ] Mental Health Centre, University Hospital “Marqués de Valdecilla”- IDIVAL, Santander, Spain
                [2 ] Faculty of Psychology, University Siglo 21, Córdoba, Argentina
                [3 ] Department of Basic Psychology, Faculty of Psychology, University of Valencia, Valencia, Spain
                [4 ] Castilla La Nueva Primary Care Centre, Health Service of Madrid, Madrid, Spain
                [5 ] Department of Psychology, University of Córdoba/ Maimónides Institute for Research in Biomedicine of Cordoba-IMIBIC/Reina Sofía University Hospital, Córdoba, Spain
                [6 ] Department of Basic Psychology, Autonomous University of Barcelona, Bellaterra, Barcelona, Spain
                [7 ] Department of Psychology, Ulm University, Ulm, Germany
                [8 ] Department of Basic Psychology, University Complutense of Madrid, Madrid, Spain
                King's College London, UNITED KINGDOM
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                ¶ Membership of the PsicAP Research Group is provided in the Acknowledgments

                Author information
                © 2018 González-Blanch et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                : 24 April 2017
                : 2 February 2018
                Page count
                Figures: 1, Tables: 4, Pages: 16
                The study was supported by grants from the Secretaría de Estado de Investigación, Desarrollo e Innovación (PSI2012-36589), the Fundación Mutua Madrileña (AP105162012), and the Psicofundación (Spanish Foundation for the Promotion, Scientific and Professional Development of Psychology; PSIC-001) all awarded to Dr. Antonio Cano-Vindel. Further support was provided by a grant from the Valdecilla Biomedical Research Institute - IDIVAL (INNVAL16/08) awarded to Dr. González-Blanch. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
                Research Article
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Mood Disorders
                Medicine and Health Sciences
                Health Care
                Primary Care
                Biology and Life Sciences
                Social Sciences
                Social Sciences
                Labor Economics
                Medicine and Health Sciences
                Diagnostic Medicine
                People and places
                Geographical locations
                European Union
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Factor Analysis
                Physical Sciences
                Statistics (Mathematics)
                Statistical Methods
                Factor Analysis
                Medicine and Health Sciences
                Drug Therapy
                Custom metadata
                These data have been collected as a sub-study of a large Randomized Clinical Trial conducted in Spanish primary care centers. This is a multi-center Randomized Clinical Trial with medication (No EUDRACT: 2013-001955-11 and Protocol Code: ISRCTN58437086) promoted by the Psicofundación and approved by the Corporate Clinical Research Ethics Committee of Primary Care of Valencia (CEIC- APCV) (as the national research ethics committee coordinator) and the Spanish Medicines and Health Products Agency (AEMPS). Due to restrictions on sharing individual-level data by the Corporate Clinical Research Ethics Committee of Primary Care of Valencia (CEIC-APCV), data cannot be publicly available. Requests for data may be sent to the Psicofundación at the following address: Psicofundación; Calle del Conde de Peñalver, 45; 28006 Madrid, Spain; Telf:+34 914 44 90 20; secop@ 123456cop.es .



                Comment on this article