Abstract
This study examines the effects of perceived housing environment on selected well-being outcomes of a seriously mentally ill population in supported housing programs. Individuals live independently in their own apartments and use supportive mental health services as needed. The study conceptualizes one's housing environment as existing at the apartment, neighborhood and the surrounding community levels of analysis that, taken together, form a multi-dimensional construct of housing environment. Self-report data from interviews with a sample of seriously mentally ill adults is paired with (a) observer ratings of housing environments, (b) census profiles of the surrounding community and (c) case manager ratings of clients' functioning in order to explore the effects of supported housing environments on well-being outcomes. Well-being is operationalized here as levels of psychiatric distress, recovery orientation, residential satisfaction, and adaptive functioning. Hierarchical regression models posit that apartment, neighborhood and census tract level variables are unique predictors of these domains of well-being. Results show that neighborhood level variables, especially those relating to the social environment, are the most influential predictors for understanding variance in well-being, with apartment level variables also contributing to understanding of housing environment effects. The census tract level predictors did not contribute a significant amount of explanation of the variance in well-being outcomes. Implications for supported housing programs and the role of ecological levels of analysis in conceptualizing and measuring housing environment influence are discussed.