Evaluating Interpersonal Associations and Substance Use Treatment Using Clinical Data Mining

Abstract

ABSTRACT This study evaluates the influence of positive interpersonal associations on treatment length of stay for clients with a substance use disorder. We used clinical data mining (CDM) methodology for this study. The clinical data we used is from client records at three substance use day treatment locations (N = 444). These sites operate under the same agency. We analyzed four measures of positive interpersonal associations including outside support systems, substance-using housing environments, 12-Step involvement, and sponsorship in a 12-Step program. Using 10 imputed datasets to run the model, we found these variables to not significantly influence treatment length of stay. However, there was a significant relationship between number of children each client had and length of stay. Results suggest that other factors may better account for varying time clients spend in treatment. Further research on the effect of other influences, such as interpersonal associations specifically within treatment, on a client’s length of stay is important.