Date of Award
Doctor of Philosophy (PhD)
Campbell, Todd C.
Griffin, Robert J.
Homelessness is a significant problem in the United States. Recent estimates suggest that nearly three million people experience homelessness over the course of a year. Further, the rates of substance abuse are considerably higher among the homeless than in the general population. Substance abuse treatment has been found to be effective in reducing substance use among those persons with substance use disorders, as well as ameliorating other consequences of substance abuse (e.g., reducing rates of crime associated with substance abuse and dependence). One of the more robust predictors of positive outcomes for substance abuse treatment is retention, which is defined as the length of time clients remain in treatment. However, while a considerable amount of research has been conducted regarding what predicts retention among non-homeless persons with substance use disorders, less is known about what predicts retention among homeless persons with substance use disorders.
The following study was conducted to determine if a set of pre-treatment biopsychosocial variables could effectively predict retention among a cohort of homeless men with substance use disorders who were seeking treatment in a substance abuse clinic, which was located in a homeless shelter for men. Path analysis was used to compare two predictive models of retention.
The results indicated that both models represented an adequate fit to the data, though each model explained approximately 15% of the variance in retention. In both models, initial severity of biopsychosocial issues and perceived consequences of substance abuse did appear to predict higher motivation for treatment, which itself appeared to predict greater length of time in treatment. However, nearly 85% of the variance in retention was not explained by either model. This suggests that the factors that lead homeless individuals to remain in substance abuse treatment over the long-term may be better accounted for by variables not in the model, such as during treatment process factors, rather than pre-treatment factors. Study implications, limitations, and directions for future research are discussed.