Working plans of people with mental disorders employed in Italian social enterprises

Psychiatr Rehabil J. 2011 Summer;35(1):55-8. doi: 10.2975/35.1.2011.55.58.

Abstract

Objective: Social Enterprises (SEn) are innovative companies that help disadvantaged people (e.g., individuals with mental disorders) with the work integration process. This study explores the working plan patterns of people with mental disorders employed in SEn.

Methods: A cross-sectional design was adopted. One hundred and forty individuals with mental disorders employed in 19 Italian SEn filled out a battery of questionnaires.

Results: We identified three patterns of working plans: Cluster 1 (n = 39, 30%) showed a stronger intention to work in a competitive labor market; Cluster 2 (n = 16, 12.3%) showed a stronger intention to stop working; Cluster 3 (n = 75, 57.7%) showed a stronger intention to continue working at a SEn.

Conclusions and implications for practice: Most of the sample had a pattern of intentions to keep working, thereby demonstrating the effectiveness of the SEn approach to work integration. Future studies should explore the approach further. Indeed, these results seem important for implications for practice, suggesting that people with mental disorders inside SEn can improve their level of interpersonal skills and reinforce their vocational identity, and ultimately increase their chances of employment in the regular labor market.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Cluster Analysis
  • Cross-Sectional Studies
  • Employment, Supported / methods
  • Employment, Supported / psychology*
  • Employment, Supported / statistics & numerical data*
  • Female
  • Humans
  • Intention
  • Italy
  • Male
  • Mental Disorders / psychology*
  • Mental Disorders / rehabilitation*
  • Middle Aged
  • Rehabilitation, Vocational / methods
  • Rehabilitation, Vocational / psychology
  • Self Concept
  • Social Adjustment
  • Social Support
  • Surveys and Questionnaires
  • Work / psychology*
  • Work / statistics & numerical data*
  • Young Adult