Prediction of community mental health service utilization by individual and ecological level socio-economic factors

Psychiatry Res. 2013 Oct 30;209(3):691-8. doi: 10.1016/j.psychres.2013.02.031. Epub 2013 Mar 23.

Abstract

Individuals with a more deprived socioeconomic status (SES) are more likely to have higher rates of psychiatric morbidity and use of psychiatric services. Such service use is also influenced by socioeconomic factors at the ecological level. The aim of this article is to investigate the influence of these variables on service utilization. All patients in contact with three Italian community psychiatric services (CPS) were included. Community and hospital contacts over 6 months were investigated. Socio-economic characteristics were described using a SES Index and two new Resources Accessibility Indexes. Low SES was found to be associated with more community service contacts. When other individual and ecological variables were controlled for, SES was negatively associated only with the number of home visits, which was about half the rate in deprived areas. An association between service utilization and the resources of the catchment area was also detected. The economic crisis in Europe is increasing inequality of access, so paying attention to SES characteristics at both the individual and the ecological levels is likely to become increasingly important in understanding patterns of psychiatric service utilization and planning care accordingly.

Keywords: Accessibility; Mental health service evaluation; Multilevel regression; Psychiatric epidemiology; Social determinants; Social psychiatry.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Community Mental Health Services / statistics & numerical data*
  • Female
  • Humans
  • Incidence
  • Italy
  • Male
  • Mental Disorders / economics*
  • Mental Disorders / epidemiology
  • Mental Disorders / therapy*
  • Middle Aged
  • Predictive Value of Tests
  • Prevalence
  • Regression Analysis
  • Social Environment*
  • Socioeconomic Factors
  • Young Adult