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      Psychometric Properties of the Dutch Depression Stigma Scale (DSS) and Associations with Personal and Perceived Stigma in a Depressed and Community Sample

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          Abstract

          Background

          Research on depression stigma is needed to gain more insight into the underlying construct and to reduce the level of stigma in the community. However, few validated measurements of depression stigma are available in the Netherlands. Therefore, this study first sought to examine the psychometric properties of the Dutch translation of the Depression Stigma Scale (DSS). Second, we examined which demographic (gender, age, education, partner status) and other variables (anxiety and knowledge of depression) are associated with personal and perceived stigma within these samples.

          Methods

          The study population consisted of an adult convenience sample ( n = 253) (study 1) and a community adult sample with elevated depressive symptoms ( n = 264) (study 2). Factor structure, internal consistency, and validity were assessed. The associations between stigma, demographic variables and anxiety level were examined with regression analyses.

          Results

          Confirmatory factor analysis supported the validity and internal consistency of the DSS personal stigma scale. Internal consistency was sufficient (Cronbach’s alpha = .70 (study 1) and .77 (study 2)). The results regarding the perceived stigma scale revealed no clear factor structure. Regression analyses showed that personal stigma was higher in younger people, those with no experience with depression, and those with lower education.

          Conclusions

          This study established the validity and internal consistency of the DSS personal scale in the Netherlands, in a community sample and in people with elevated depressive symptoms. However, additional research is needed to examine the factor structure of the DSS perceived scale and its use in other samples.

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          Most cited references24

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          The increasing burden of depression

          Recent epidemiological surveys conducted in general populations have found that the lifetime prevalence of depression is in the range of 10% to 15%. Mood disorders, as defined by the World Mental Health and the Diagnostic and Statistical Manual of Mental Disorders, 4th edition, have a 12-month prevalence which varies from 3% in Japan to over 9% in the US. A recent American survey found the prevalence of current depression to be 9% and the rate of current major depression to be 3.4%. All studies of depressive disorders have stressed the importance of the mortality and morbidity associated with depression. The mortality risk for suicide in depressed patients is more than 20-fold greater than in the general population. Recent studies have also shown the importance of depression as a risk factor for cardiovascular death. The risk of cardiac mortality after an initial myocardial infarction is greater in patients with depression and related to the severity of the depressive episode. Greater severity of depressive symptoms has been found to be associated with significantly higher risk of all-cause mortality including cardiovascular death and stroke. In addition to mortality, functional impairment and disability associated with depression have been consistently reported. Depression increases the risk of decreased workplace productivity and absenteeism resulting in lowered income or unemployment. Absenteeism and presenteeism (being physically present at work but functioning suboptimally) have been estimated to result in a loss of $36.6 billion per year in the US. Worldwide projections by the World Health Organization for the year 2030 identify unipolar major depression as the leading cause of disease burden. This article is a brief overview of how depression affects the quality of life of the subject and is also a huge burden for both the family of the depressed patient and for society at large.
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            Effect of web-based depression literacy and cognitive-behavioural therapy interventions on stigmatising attitudes to depression: randomised controlled trial.

            Little is known about the efficacy of educational interventions for reducing the stigma associated with depression. To investigate the effects on stigma of two internet depression sites. A sample of 525 individuals with elevated scores on a depression assessment scale were randomly allocated to a depression information website (BluePages), a cognitive-behavioural skills training website (MoodGYM) or an attention control condition. Personal stigma (personal stigmatising attitudes to depression) and perceived stigma (perception of what most other people believe) were assessed before and after the intervention. Relative to the control, the internet sites significantly reduced personal stigma, although the effects were small. BluePages had no effect on perceived stigma and MoodGYM was associated with an increase in perceived stigma relative to the control. Changes in stigma were not mediated by changes in depression, depression literacy or cognitive-behavioural therapy literacy. The internet warrants further investigation as a means of delivering stigma reduction programmes for depression.
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              Public conceptions of mental illness: labels, causes, dangerousness, and social distance.

              The authors used nationwide survey data to characterize current public conceptions related to recognition of mental illness and perceived causes, dangerousness, and desired social distance. Data were derived from a vignette experiment included in the 1996 General Social Survey. Respondents (n = 1444) were randomly assigned to 1 of 5 vignette conditions. Four vignettes described psychiatric disorders meeting diagnostic criteria, and the fifth depicted a "troubled person" with subclinical problems and worries. Results indicate that the majority of the public identifies schizophrenia (88%) and major depression (69%) as mental illnesses and that most report multicausal explanations combining stressful circumstances with biologic and genetic factors. Results also show, however, that smaller proportions associate alcohol (49%) or drug (44%) abuse with mental illness and that symptoms of mental illness remain strongly connected with public fears about potential violence and with a desire for limited social interaction. While there is reason for optimism in the public's recognition of mental illness and causal attributions, a strong stereotype of dangerousness and desire for social distance persist. These latter conceptions are likely to negatively affect people with mental illness.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                8 August 2016
                2016
                : 11
                : 8
                : e0160740
                Affiliations
                [1 ]Department of Clinical Neuro and Developmental Psychology, Section clinical psychology, Faculty of Behavioural and Movement Sciences, Vrije Universiteit, Amsterdam, the Netherlands
                [2 ]EMGO+ institute for Health Care and Research, Vrije Universiteit Medical Centre, Amsterdam, the Netherlands
                [3 ]Statistics Netherlands (CBS), Den Haag, the Netherlands
                [4 ]Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, the Netherlands
                [5 ]National Institute for Mental Health Research, The Australian National University, Acton, Canberra, Australia
                Iranian Institute for Health Sciences Research, ISLAMIC REPUBLIC OF IRAN
                Author notes

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

                • Conceptualization: AMB KvZ PC CJMH AMK.

                • Formal analysis: AMB AMK PC LBM.

                • Investigation: AMB AMK CJMH.

                • Methodology: AMB KvZ PC CJMH AMK KMG LBM.

                • Project administration: AMB CJMH.

                • Resources: AMB AMK KMG KvZ.

                • Supervision: AMK PC.

                • Writing - original draft: AMB AMK KvZ.

                • Writing - review & editing: KvZ PC CJMH LBM KMG AMK.

                ‡ These authors also contributed equally to this work.

                Article
                PONE-D-15-50004
                10.1371/journal.pone.0160740
                4976889
                27500969
                5232630e-5e09-4693-9983-0473a914331c
                © 2016 Boerema 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.

                History
                : 16 November 2015
                : 25 July 2016
                Page count
                Figures: 0, Tables: 11, Pages: 16
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001826, ZonMw;
                Award ID: 50-51510-98-009
                Award Recipient :
                Funded by: Australian National Medical and Health Research Council (NHMRC)
                Award ID: 1059620
                Award Recipient :
                ZonMW funded study 2 (Grant number 50-51510-98-009). KMG is supported by Australian National Medical and Health Research Council (NHMRC) Fellowship No. 1059620. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
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                Medicine and Health Sciences
                Mental Health and Psychiatry
                Mood Disorders
                Depression
                Research and Analysis Methods
                Mathematical and Statistical Techniques
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                Factor Analysis
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                Factor Analysis
                People and Places
                Demography
                Biology and Life Sciences
                Psychology
                Psychometrics
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                Research and Analysis Methods
                Research Assessment
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                Social Sciences
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                Physical Sciences
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