Treatment Resistant Alcohol Use Disorder

Abstract

ABSTRACT Despite existing interventions that have shown some promise for people with alcohol use disorder (AUD), there is a sizable number of patients that fail to respond to or complete treatment. In the current study, we analyzed data from the Treatment Episode Data Set (TEDS) to create profiles that indicate who may be more likely to resist treatment-as-usual. For the analysis, chi-square and logistic regression were used to associate personal characteristics with being at high and low risk of treatment resistance. Characteristics that put someone at higher risk of resisting treatment-as-usual include being unemployed, homelessness (or a dependent living arrangement), using daily, being male, and co-occurring mental and substance abuse disorders. The results suggest that general demographic information at patients’ admission can be used to identify population groups where conventional strategies for standard AUD treatment may be insufficient. As such, the findings can help to inform, shape, and personalize treatment, leading to successful outcomes for the subgroup of individuals who will not benefit from typical AUD interventions.