Abstract: Predictors of Housing and Time to Housing for Homeless Individuals Enrolled in a Coordinated Housing Program (Society for Social Work and Research 25th Annual Conference - Social Work Science for Social Change)

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Predictors of Housing and Time to Housing for Homeless Individuals Enrolled in a Coordinated Housing Program

Wednesday, January 20, 2021
* noted as presenting author
Aubrey Jones, PhD, Assistant Professor, University of South Dakota, Sioux Falls
David Patterson, Ph.D., Professor and Director, University of Tennessee, Knoxville, Knoxville, TN
Lisa Higginbotham, MSSW, Program Manager, University of Tennessee, Knoxville, Knoxville, TN
R. Chris Smith, MSSW, LCSW, Knox-HMIS, University of Tennessee
In January 2019, the Point in Time (PIT) survey identified 429,303 homeless individuals and families in the United States. Homelessness is a pernicious public health concern that is the result of various systematic issues including: poverty, decline in public assistance and lack of affordable housing. In 2012, the US Department of Housing and Urban Development (HUD) required that all Continuums of Care (CoCs) develop and maintain a coordinated entry system (CES). In 2018, a CoC in a midsized southeastern city developed a system that enabled individuals and families experiencing homelessness to seek services through multiple access points. Using a housing first approach, the CoC developed and implemented the Coordinated Housing Assessment Match Plan (CHAMP) to assess the needs of individuals and families coping with homelessness and expedite housing services to appropriately address their level of need.

The purpose of this study is to examine the predictors of housing for persons and families experiencing homelessness and to determine predictors of time to housing for homeless persons and families participating in CHAMP.

All data were retrieved from a community coordinated housing program database. Data from the community-university partnership were de-identified and collected from May 2018 - May 2019.

Descriptive statistics were generated in SPSS. A binary logistic regression was used to identify predictors of housing and a cox-regression survival analysis was then conducted to examine the factors which predict time to housing.

The final sample (N = 306) was comprised of primarily non-Hispanic individuals with an average age of 40.78 years old. Over half (58%) were individuals aged 25 years or older and 35% were families. Unaccompanied youth (24 years of age or younger) accounted for 7.2% of the sample. Results from the survival analysis suggest our model is a significant [X2(12) = 91.28 p < .001] improvement in fit relative to the null (N = 306). VI-Type (individuals, family, youth), disability status, exit destination, and whether individuals had a case manager or prioritization score were all significant. Families were more likely to be housed and experienced shorter days to housing compared to individuals (b= .602 s.e..161p < .001). Average days to housing for each VI-type is reported: Individuals (x̄ = 86.77, SD = 81.14); Families x̄ = 49.88, SD = 51.76); Youth x̄ = 48.32, SD = 77.70). Those able to rent without using a subsidy experienced shorter length in time to housing (b= 1.09 s.e. = .276, p < .001, x̄ = 39.22, SD = 45.97), while those able to arrange to live with friends or family also experience shorter length of time to housing (b =.596 s.e. .257, p = .021, x̄ = 62.40, SD = 53.13).

This is the first study to our knowledge to assess predictors of time to housing using a coordinated entry system. The results of this study highlight the challenges and factors affecting time to housing among homeless individuals and families. The results inform the efforts of the grand challenge to eradicate homelessness and have implications for housing policy and social work practice.