Predictors of successful housing in a housing first program. Issue 1 (2nd January 2021)

• Record Type: Journal Article
• Authors: Hanauer, Matthew; Watterson, Kelsey; Ragatz, Marie; Macy, Jon T.; Sinclair, Elaina; Suisman, Sara
• Is Part Of: Journal of social distress and the homeless. Volume 30:Issue 1(2021)
• Page Start: 84
• Page End: 89
• Publication Date: 2021-01-02
• Subjects: Housing first -- Bayesian -- homelessness -- logistic regression -- odds ratios; Social problems -- Psychological aspects -- Periodicals; Stress (Psychology) -- Social aspects -- Periodicals; Homelessness -- Periodicals; 362.505
• DOI: 10.1080/10530789.2020.1738636
• Languages: English
• ISSNs: 1573-658X

Abstract

ABSTRACT: Housing first models have become increasingly common for supporting persons experiencing homelessness. However, successful implementation of the housing first model can vary from program to program. To better understand what factors, influence whether a person experiencing homelessness can secure housing in a housing first model, we constructed a logistic Bayesian model. With data from 69 clients enrolled in a housing first program in Indiana, we tested demographic factors, depression, drug use, health status, hospital and acute care and outpatient visits, probation/parole status, and number of crimes committed as prospective predictors of securing housing six months later. We found that older participants, those who had recently utilized acute care services, and those with lower depression scores were more likely to secure housing after six months.