Background: The mental health of the population consists of the three essential pillars of quality of life, economy, and society. Mental health services take care of the prevention and treatment of mental disorders and through them maintain, improve, and restore the mental health of the population. The purpose of this study is to describe the methodology for qualitative and quantitative evaluation and improvement of the mental health service system. Methods: This is a narrative review study that searches the literature to provide criteria, indicators, and methodology for evaluating and improving the quality of mental health services and the related qualitative and quantitative indicators. The bibliography was searched in popular databases PubMed, Google Scholar, CINAHL, using the keywords “mental”, “health”, “quality”, “indicators”, alone or in combinations thereof. Results: Important quality indicators of mental health services have been collected and presented, and modified where appropriate. The definition of each indicator is presented here, alongside its method of calculation and importance. Each indicator belongs to one of the eight dimensions of quality assessment: (1) Suitability of services, (2) Accessibility of patients to services, (3) Acceptance of services by patients, (4) Ability of healthcare professionals to provide services, (5) Efficiency of health professionals and providers, (6) Continuity of service over time (ensuring therapeutic continuity), (7) Efficiency of health professionals and services, (8) Safety (for patients and for health professionals). Discussion/Conclusions: Accessibility and acceptability of service indicators are important for the attractiveness of services related to their use by the population. Profitability indicators are important economic indicators that affect the viability and sustainability of services, factors that are now taken into account in any health policy. All of the indicators mentioned are related to public health, affecting the quality of life, morbidity, mortality, and life expectancy, directly or indirectly. The systematic measurement and monitoring of indicators and the measurement and quantification of quality through them, are the basis for evidence-based health policy for improvement of the quality of mental health services.

Background/Aim. The aim of this study is to examine the effects of perceived cognitive dysfunction and of depression, on self-reported QoL, in a Greek population sample of MS patients.Methods. One hundred outpatients diagnosed with MS completed the Short-Form-36 Health Survey (SF-36), as well as the Perceived Deficits Questionnaire (PDQ) and the Depression subscale of the Mental Health Inventory (MHI), as part of a clinical evaluation which included the Expanded Disability Status Scale (EDSS) estimation. Multiple linear regression was conducted to determine the best linear combination of age, gender, education, EDSS, depression, attention/concentration, retrospective memory, prospective memory, and planning/organization, for predicting QoL scores.Results. In the multivariate regression analysis models, EDSS (P<0.05), depression (P<0.001), perceived planning/organization (P<0.05), and perceived retrospective memory dysfunction (P<0.05) independently predict quality of life scores. Age, sex, education level, and perceived attention/concentration dysfunction, as well as perceived prospective memory dysfunction, do not independently predict quality of life scores.Conclusions. Perceived planning/organization impairment and perceived retrospective memory impairment in MS patients predict QoL independently of the severity of disease and the severity of depression and therefore should be considered in the assessment of patient health status as well as in the design of treatment interventions and rehabilitation.

To evaluate Quality of life (QoL) in chronic heart failure (CHF) in relation to Neuroticism personality trait and CHF severity. Thirty six consecutive, outpatients with Chronic Heart Failure (6 females and 30 males, mean age: 54 ± 12 years), with a left ventricular ejection fraction ≤ 45% at optimal medical treatment at the time of inclusion, were asked to answer the Kansas City Cardiomyopathy Questionnaire (KCCQ) for Quality of Life assessment and the NEO Five-Factor Personality Inventory for personality assessment. All patients underwent a symptom limited cardiopulmonary exercise testing on a cycle-ergometer, in order to access CHF severity. A multivariate linear regression analysis using simultaneous entry of predictors was performed to examine which of the CHF variables and of the personality variables were correlated independently to QoL scores in the two summary scales of the KCCQ, namely the Overall Summary Scale and the Clinical Summary Scale. The Neuroticism personality trait score had a significant inverse correlation with the Clinical Summary Score and Overall Summary Score of the KCCQ (r = -0.621, P < 0.05 and r = -0.543, P < 0.001, respectively). KCCQ summary scales did not show significant correlations with the personality traits of Extraversion, Openness, Conscientiousness and Agreeableness. Multivariate linear regression analysis using simultaneous entry of predictors was also conducted to determine the best linear combination of statistically significant univariate predictors such as Neuroticism, VE/VCO2 slope and VO2 peak, for predicting KCCQ Clinical Summary Score. The results show Neuroticism (β = -0.37, P < 0.05), VE/VCO2 slope (β = -0.31, P < 0.05) and VO2 peak (β = 0.37, P < 0.05) to be independent predictors of QoL. In multivariate regression analysis Neuroticism (b = -0.37, P < 0.05), the slope of ventilatory equivalent for carbon dioxide output during exercise, (VE/VCO2 slope) (b = -0.31, P < 0.05) and peak oxygen uptake (VO2 peak), (b = 0.37, P < 0.05) were independent predictors of QoL (adjusted R2 = 0.64; F = 18.89, P < 0.001). Neuroticism is independently associated with QoL in CHF. QoL in CHF is not only determined by disease severity but also by the Neuroticism personality trait.