We aimed to collect and meta-analyse the existing evidence regarding the performance of the Center for Epidemiologic Studies Depression (CES-D) for detecting depression in general population and primary care settings. Systematic literature search in PubMed and PsychINFO. Eligible studies were: a) validation studies of screening questionnaires with information on the accuracy of the CES-D; b) samples from general populations or primary care settings; c) standardized diagnostic interviews following standard classification systems used as gold standard; and d) English or Spanish language of publication. Pooled sensitivity, specificity, likelihood ratios and diagnostic odds ratio were estimated for several cut-off points using bivariate mixed effects models for each threshold. The summary receiver operating characteristic curve was estimated with Rutter and Gatsonis mixed effects models; area under the curve was calculated. Quality of the studies was assessed with the QUADAS tool. Causes of heterogeneity were evaluated with the Rutter and Gatsonis mixed effects model including each covariate at a time. 28 studies (10,617 participants) met eligibility criteria. The median prevalence of Major Depression was 8.8% (IQ range from 3.8% to 12.6%). The overall area under the curve was 0.87. At the cut-off 16, sensitivity was 0.87 (95% CI: 0.82–0.92), specificity 0.70 (95% CI: 0.65–0.75), and DOR 16.2 (95% CI: 10.49–25.10). Better trade-offs between sensitivity and specificity were observed (Sensitivity = 0.83, Specificity = 0.78, diagnostic odds ratio = 16.64) for cut-off 20. None of the variables assessed as possible sources of heterogeneity was found to be statistically significant. The CES-D has acceptable screening accuracy in the general population or primary care settings, but it should not be used as an isolated diagnostic measure of depression. Depending on the test objectives, the cut-off 20 may be more adequate than the value of 16, which is typically recommended.

Brain disorders represent a high burden in Europe and worldwide. The objective of this study was to provide specific estimates of the economic costs of brain disorders in Spain, based on published epidemiological and economic evidence. A cost-of-illness study with a societal perspective of 19 brain disorders was carried out. Cost data published between 2004 and 2012 was obtained from a systematic literature review. Direct healthcare, direct non-medical and indirect costs were considered, prioritizing bottom-up information. All costs were converted to Euro and to year 2010. The missing values were imputed with European estimates. Sensitivity analyses based on qualitative assessment of the literature and on a Monte Carlo simulation were performed. The review identified 33 articles with information on costs for 11 disorders (8 neurological, 3 mental). The average per–patient cost ranged from 36,946 € for multiple sclerosis to 402 € for headache. The societal cost of the 19 brain disorders in Spain in 2010 was estimated in 84 € billion. Societal costs ranged from 15 € billion for dementia to 65 € million for eating disorders. Mental disorders societal cost were 46 € billions (55% of the total), while neurological disorder added up to 38 € billion. Healthcare costs represented 37% of the societal costs of brain disorders, whereas direct non-medical constituted 29% and indirect costs 33%. Brain disorders have a substantial economic impact in Spain (equivalent to almost 8% of the country's GDP). Economic data on several important brain disorders, specially mental disorders, is still sparse.

Integrated care programmes are increasingly being put in place to provide care to older people who live at home. Knowledge of how to further develop integrated care and how to transfer successful initiatives to other contexts is still limited. Therefore, a cross-European research project, called Sustainable Tailored Integrated Care for Older People in Europe (SUSTAIN), has been initiated with a twofold objective: 1. to collaborate with local stakeholders to support and monitor improvements to established integrated care initiatives for older people with multiple health and social care needs. Improvements focus on person-centredness, prevention orientation, safety and efficiency; 2. to make these improvements applicable and adaptable to other health and social care systems, and regions in Europe. This paper presents the overall structure and approach of the SUSTAIN project. SUSTAIN uses a multiple embedded case study design. In three phases, SUSTAIN partners: (i) conduct interviews and workshops with stakeholders from fourteen established integrated care initiatives to understand where they would prefer improvements to existing ways of working; (ii) collaborate with local stakeholders to support the design and implementation of improvement plans, evaluate implementation progress and outcomes per initiative, and carry out overarching analyses to compare the different initiatives, and; (iii) translate knowledge and experience to an online roadmap. SUSTAIN aims to generate evidence on how to improve integrated care, and apply and transfer the knowledge gained to other health and social care systems, and regions. Lessons learned will be brought together in practical tools to inform and support policy-makers and decision-makers, as well as other stakeholders involved in integrated care, to manage and improve care for older people living at home.

Background There is increasing interest on whether the current global economic uncertainties have an influence on the population's mental health. In this paper, we examined the association of negative socioeconomic changes, job loss and household income reductions with incident mental disorders. The moderating effect of gender was assessed. Methods Data come from the Netherlands Mental Health Survey and Incidence Study-2 (NEMESIS-2), a representative population-based, longitudinal study. Individuals with a paid job and without a 12-month mental disorder at baseline were selected and reassessed 3 years later (2007–2009/2010–2012). Substantial household income reductions and not being at a paid job anymore were self-reported at follow-up. Multivariate logistic models were utilised to investigate the association between these negative socioeconomic changes and the incidence of mood, anxiety and substance use Diagnostic and Statistical Manual-IV disorders assessed by the Composite International Diagnostic Interview 3.0. Results After 3 years, 6% had lost their job, 11% had a substantial household income reduction and 12.2% had developed a mental disorder. Household income reductions increased the risk of any mental disorder (aOR=1.77), particularly the risk of mood (aOR=2.24). Job loss increased the risk of mood disorders (aOR=2.02). Gender modified the relationship: job loss increased the risk of any mental disorder among men (aOR=3.04) and household income reductions did so among women (aOR=2.32). Conclusions Negative socioeconomic changes occurring within a short time period significantly increased the risk of incident mental disorders, particularly of mood disorders. Effective interventions to alleviate the public mental health impact of negative socioeconomic changes on men and women are needed.