Performance on the Stroop Predicts Treatment Compliance in Cocaine-Dependent Individuals

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Abstract
Treatment dropout is a problem of great prevalence and stands as an obstacle to recovery in cocaine-dependent (CD) individuals. Treatment attrition in CD individuals may result from impairments in cognitive control, which can be reliably measured by the Stroop color–word interference task. The present analyses contrasted baseline performance on the color-naming, word-reading, and interference subtests of the Stroop task in CD subjects who completed a cocaine treatment trial (completers: N=50) and those who dropped out of the trial before completion (non-completers: N=24). A logistic regression analysis was used to predict trial completion using three models with the following variables: the Stroop task subscale scores (Stroop model); the Hamilton depression rating scale (HDRS) scores (HDRS model); and both the Stroop task subscale scores and HDRS scores (Stroop and HDRS model). Each model was able to significantly predict group membership (completers vs non-completers) better than a model based on a simple constant (HDRS model p=0.02, Stroop model p=0.006, and Stroop and HDRS model p=0.003). Models using the Stroop preformed better than the HDRS model. These findings suggest that the Stroop task can be used to identify cocaine-dependent subjects at risk for treatment dropout. The Stroop task is a widely available, reliable, and valid instrument that can be easily employed to identify and tailor interventions of at risk individuals in the hope of improving treatment compliance.