[Treatment dropout in cocaine addicts]

The high rate of dropout from treatment programs is one of the most serious problems in the field of drug dependence. Early identification of predictors of dropout risk can provide useful information on the specific treatment needs of these types of patient. The aim of this study was to identify predictors of premature cessation of an outpatient treatment program for cocaine addicts. The study was carried out at public healthcare units in a Spanish city. Participants were 91 cocaine addicts admitted for treatment for their addiction, assessed by means of interview and various self-report measures. For identifying predictive variables the researchers used a factor analysis, a cluster analysis and a CHAID analysis. The variables that obtained predictive capacity were the MAST scores and the combined alcohol and drugs scores on the EuropASI. These three variables were grouped in a single factor which was called addictive severity. The predictive analysis showed that this factor had some degree of capacity for the prediction of dropout, but that it was not completely determinant. The results suggest the advantage of detecting at the admission stage those patients who might require more attention to their motivational aspects, greater treatment control and intensity, or the provision of complementary interventions.