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- Title
A latent class analysis of self‐identified reasons for experiencing homelessness: Opportunities for prevention.
- Authors
Barile, John P.; Pruitt, Anna Smith; Parker, Josie L.
- Abstract
Abstract: Individuals experience homelessness due to a vast number of factors. Therefore, the methods used to prevent individuals from experiencing homelessness should match their diverse needs. This study utilized survey data obtained from 577 adults experiencing homelessness to identify self‐reported causes of homelessness. A latent class analysis was conducted in order to identify classes or subgroups of respondents with distinct patterns of reported causes of homelessness. A latent class analysis is a person‐centred statistical approach that is used to determine groups of individuals who share similar characteristics. Findings from this analysis identified 5 distinct classes based on individuals' responses to 19 potential vulnerabilities or events that contributed to experiencing homelessness. Individuals tended to cluster around issues associated with (a) disability or physical health issues (4%), (b) substance abuse or mental health issues (30%), (c) report major life changes (3%), (d) financial crises (7%), or (e) employment difficulties (55%). Significant group differences occurred across military veteran status, history of homelessness, depression, and health‐related quality of life. Results for these analyses suggest that individuals report notable differences in their reasons for becoming homeless and therefore require unique preventative solutions.
- Subjects
HOMELESSNESS; CLIMACTERIC; MENTAL depression; EXPERIENCE; MENTAL illness; PEOPLE with disabilities; QUALITY of life; SELF-evaluation; MILITARY personnel; STATISTICS; SUBSTANCE abuse; NET losses; DATA analysis; HEALTH equity; PSYCHOLOGICAL vulnerability; PSYCHOLOGY
- Publication
Journal of Community & Applied Social Psychology, 2018, Vol 28, Issue 2, p94
- ISSN
1052-9284
- Publication type
Article
- DOI
10.1002/casp.2343