Clinicians have access to several risk assessment instruments to evaluate the risk or recidivism in sexual offenders. Nevertheless, we seem to have attained a ceiling in the predictive validity of these instruments with the traditional techniques of items agglomeration. In this study, we offer a different combination of predictors with the classification and regression trees, and it, by taking into account the type of sexual offenders. The classification trees are constructed from predictors contained in seven actuarial instruments (VRAG, SORAG, RRASOR, STATIC-99, STATIC-2002, RM2000, MnSOST-R). In general, the classification trees have a higher predictive accuracy than the actuarial instruments and point out that it's not the same predictors that should be considered according to the type of offenders and the type of recidivism. Furthermore, classification trees identify correctly more recidivists than the best actuarial tool. In spite of the contribution of this approach, other types of predictors should also be considered to augment predictive accuracy: dynamic predictors, protective predictors as well as measurements based on theories like those on attachment styles (Marshall, D. R., Barbaree, H. E., 1990. An integrated theory of the etiology of sexual offending. In: Marshall, W. L., Laws, D. R. L., Barbaree, H.E. (Eds.), Handbook of sexual assault. New York: Plenum Press, pp. 257-275.) and cognitive distortions (Ward, T., Keenan, T., Hudson, S. M., 2000. Understanding cognitive, affective, and intimacy deficits in sexual offenders: a developmental perspective. Aggression and Violent Behavior, 5, 41–62.).
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