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.

中文翻译：

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住房环境和心理健康结果：分析视角的层次

本研究调查了感知住房环境对支持住房计划中严重精神疾病人群的选定幸福结果的影响。个人独立生活在自己的公寓中，并根据需要使用支持性心理健康服务。该研究将一个人的住房环境概念化为存在于公寓、邻里和周围社区层面的分析，这些分析共同形成了一个多维的住房环境结构。来自对严重精神病成年人样本的访谈的自我报告数据与 (a) 住房环境的观察者评级，(b) 周围社区的人口普查概况和 (c) 个案经理对客户功能的评级相结合，以探索支持性住房环境对福祉结果的影响。幸福感在这里被具体化为精神痛苦、康复导向、居住满意度和适应性功能的水平。分层回归模型假定公寓、社区和人口普查区级别变量是这些幸福领域的独特预测因子。结果表明，邻里层面的变量，尤其是与社会环境相关的变量，是理解幸福感差异的最有影响力的预测因素，公寓层面的变量也有助于理解住房环境的影响。人口普查区水平预测因子没有对幸福结果的差异做出大量解释。