The effect of service satisfaction and spiritual well-being on the quality of life of patients with schizophrenia.

Quality of life (QOL) has been considered an important outcome measure in psychiatric research and determinants of QOL have been widely investigated. We aimed at detecting predictors of QOL at baseline and at testing the longitudinal interrelations of the baseline predictors with QOL scores at a 1-year follow-up in a sample of patients living in Residential Facilities (RFs). Logistic regression models were adopted to evaluate the association between WHOQoL-Bref scores and potential determinants of QOL. In addition, all variables significantly associated with QOL domains in the final logistic regression model were included by using the Structural Equation Modeling (SEM). We included 139 patients with a diagnosis of schizophrenia spectrum. In the final logistic regression model level of activity, social support, age, service satisfaction, spiritual well-being and symptoms' severity were identified as predictors of QOL scores at baseline. Longitudinal analyses carried out by SEM showed that 40% of QOL follow-up variability was explained by QOL at baseline, and significant indirect effects toward QOL at follow-up were found for satisfaction with services and for social support. Rehabilitation plans for people with schizophrenia living in RFs should also consider mediators of change in subjective QOL such as satisfaction with mental health services

Por una clínica de resistencia: experimentaciones des-institucionalizantes en tiempos de la biopolítica

Objetivos: El artículo abre un debate acerca de los procesos de des-institucionalización en el campo de la salud mental, situándolo en el contexto de globalización de la sociedad mundial y las nuevas formas de poder y control que se le asocian

A Simulation-Based Multiobjective Optimization Approach for Health Care Service Management

Hospitals are huge and complex systems. However, for many years, the management was commonly focused on improving the quality of the medical care, while less attention was usually devoted to operation management. In recent years, the need of containing the costs while increasing the competitiveness along with the new policies of National Health Service hospital financing forced hospitals to necessarily improve their operational efficiency. In this paper, we focus on a management problem usually arising in health care. In particular, we deal with optimal resource allocation of a ward of a big hospital. To this aim, we propose a simulation-based optimization approach that makes use of a discrete-event simulation model, reproducing the hospital services and combined with a derivative-free multiobjective optimization method. The results obtained on the obstetrics ward of an Italian hospital are reported, showing the effectiveness of the new approach proposed