Investment in innovative mental health care services requires the use of scarce resources that could be used in alternative ways. Economic evaluation is essential to ensure that such an investment is appropriately compared with investment elsewhere.

A non-systematic review of mental health evaluations identifies key methodological issues pertaining to economic studies.

Economic evaluations require the measurement and combination of costs and outcomes, and clarity about how this measurement is undertaken is required. Regarding costs, important considerations relate to the perspective to be taken (e.g., health service or societal), method of measurement (patient self-report or use of databases) and valuation (actual costs, fees or expenditure). Decision makers frequently need to compare evidence both within and between clinical areas and therefore there is a tension between the use of condition specific and generic outcome measures. Quality-adjusted life years are frequently used in economic evaluations, but their appropriateness in mental health care studies is still debated.

Economic evaluations in the area of mental health care are increasing in number and it is essential that researchers continue to develop and improve methods used to conduct such studies.

Previous studies have attempted to forecast the costs of mental health care, using clinical and individual variables; the inclusion of ecological measures could improve the knowledge of predictors of psychiatric service utilisation and costs to support clinical and strategic decision-making.

Using a Psychiatric Case Register (PCR), all patients with an ICD-10 psychiatric diagnosis, who had at least one contact with community-based psychiatric services in the Verona Health District, Northern Italy, were included in the study (N = 4558). For each patient, one year's total cost of care was calculated by merging service contact data with unit cost estimates and clinical and socio-demographic variables were collected. A socio-economic status (SES) index was developed, as a proxy of deprivation, using census data. Multilevel multiple regression models, considering socio-demographic and clinical characteristics of patients as well as socioeconomic local characteristics, were estimated to predict costs.

The mean annual cost for all patients was 2,606.11 Euros; patients with an ongoing episode of care and with psychosis presented higher mean costs. Previous psychiatric history represented the most significant predictor of cost (36.99% R2 increase) and diagnosis was also a significant predictor but explained only 4.96% of cost variance. Psychiatric costs were uniform throughout the Verona Health District and SES characteristics alone contributed towards less than 1% of the cost variance.

For all patients of community-based psychiatric services, a comprehensive model, including both patients' individual characteristics and socioeconomic local status, was able to predict 43% of variance in costs of care.

This study was conducted in order to evaluate the effects of mental health and quality of life (QOL) in children and adolescents living in residential and foster care.

Two hundred and sixteen children and adolescents, aged 8–18 years, from residential and foster care participated. QOL was assessed using the Pediatric Quality-of-Life Inventory (PedsQL), levels of anxiety and depressive symptoms using the screen for child anxiety-related emotional disorders (SCARED) questionnaire and the short mood and feeling questionnaire (SMFQ), and general mental health through use of the strengths and difficulties questionnaire (SDQ).

The children and adolescents from residential care had significantly low QOL and more frequently had mental health problems. A stepwise linear regression was performed to test the associations between the SCARED, SMFQ and SDQ scores, and PedsQL (QOL). Anxiety, depressive symptoms and general mental difficulties account for significant variations in QOL (p < 0.001).

Mental health problems have significant negative effects on the QOL of children and adolescents living in residential and foster care.

Although stigma in relation to mental health has been defined as including components of knowledge, attitudes and behaviour, no psychometrically tested instrument to assess behavioural discrimination at the population level has been developed. This paper presents details of the development and psychometric properties of the Reported and Intended Behaviour Scale (RIBS), an instrument based on the Star Social Distance Scale, to assess reported (past and current) and intended (future) behavioural discrimination among the general public against people with mental health problems.

Three studies were carried out to evaluate psychometric properties of the RIBS (Study 1, n = 92; Study 2, n = 37; Study 3, n = 403). Adults aged 25–45 in socio-economic groups: B, C1 and C2 (middle-income groups) took part in development and testing of the RIBS.

Internal consistency and test–retest reliability is moderate/substantial. Strong consensus validity was found, as rated by service users/consumers and international experts in stigma research.

Use of a behavioural outcome may be important to evaluate the effectiveness of interventions intended to reduce stigma and/or discrimination related to mental illness. The RIBS was found to be a brief, feasible and psychometrically robust measure for assessing mental health-related reported and intended behavioural discrimination.

Previous work suggests that the Dutch variant of assertive community treatment (ACT), known as Function ACT (FACT), may be effective in increasing symptomatic remission rates when replacing a system of hospital-based care and separate community-based facilities. FACT guidelines propose a different pattern of psychiatric service consumption compared to traditional services, which should result in different costing parameters than care as usual (CAU).

South-Limburg FACT patients, identified through the local psychiatric case register, were matched with patients from a non-FACT control region in the North of the Netherlands (NN). Matching was accomplished using propensity scoring including, among others, total and outpatient care consumption. Assessment, as an important ingredient of FACT, was the point of departure of the present analysis.

FACT patients, compared to CAU, had five more outpatient contacts after the index date. Cost-effectiveness was difficult to assess.

Implementation of FACT results in measurable changes in mental health care use.