Abstract
The objective of this study was to analyze the influence of the variables that predict cocaine abstinence on an outpatient program for the treatment of addiction to this substance. Participants were 80 patients (85% men and 15% women) selected at random from those receiving treatment at a Spanish health service outpatient unit. For detecting the predictor variables the authors carried out a chi-square automatic interaction detection (CHAID) analysis. Logistic regression analysis and discriminant analysis were performed to estimate the probability of abstinence according to/using the predictor variables detected by CHAID analysis. Abstinence rate after six months of treatment was 37.5%. The variable that best predicted abstinence was number of urine tests carried out over the course of treatment. The rest of the variables used did not have statistically significant influence. The mathematical model used correctly classified 80% of cases. A total of 31 tests were necessary for a probability of over 0.75 of being abstinent at six months. Regular screening for abstinence by means of objective tests helps to improve abstinence rates on cocaine-addiction treatment programs.
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