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Applying a Time‐Patterned Typology of Homelessness Among Individuals with Mental Illness
Author(s) -
Brown Molly,
Chodzen Gia,
Mihelicova Martina,
Collins Kelly
Publication year - 2017
Publication title -
american journal of community psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.113
H-Index - 112
eISSN - 1573-2770
pISSN - 0091-0562
DOI - 10.1002/ajcp.12140
Subject(s) - typology , mental illness , mental health , multinomial logistic regression , psychiatry , population , psychology , health psychology , public health , substance abuse , housing first , demography , medicine , sociology , nursing , machine learning , anthropology , computer science
Identification of subgroups of the homeless populations, or typologies, has been an important research priority to guide homelessness services and policies. This study builds on previous typological research conducted in the general homeless population by focusing on individuals with mental illness to further delineate typologies within a more homogenous subset of the homeless population. A time‐patterned typology based on episodes of street and shelter homelessness over a four‐year period was applied to a sample of 246 individuals identified through mental health administrative records. Four groups were created based upon patterns of homelessness: 26.8% experienced homelessness for 4 years, 13.4% had one episode of homelessness but were no longer homeless at the end of the follow‐up, 48.4% had at least two episodes of homelessness, and 11.4% had a single episode of homelessness lasting 3 months or less. Findings from a multinomial logistic regression indicated that gender, presence of a psychotic disorder, substance abuse, and year of study enrollment significantly predicted group membership. Residential trajectories upon exit from homelessness and at the end of the four‐year follow‐up were examined. Implications for current policy and future research are discussed.