Development of an actuarial static risk model suitable for automatic scoring for predicting juvenile recidivism

Objectives To test the feasibility of an actuarial model for juvenile offending suitable for automatic scoring. Design We identified a nationally representative sample of 936 young persons aged 13–17 (745 male, 191 female) who received a juvenile justice intake in 2002 in New Zealand. Methods Best‐subsets logistic regression and a formal model selection criterion were used to generate a predictive model for reoffending, and a conservative estimate of accuracy was obtained with cross‐validation. Results Recidivism during a 1‐year follow‐up was significantly higher for male (60.8%) compared to female (46.6%) delinquents. The model showed that young persons who were male, younger at their first social welfare intake, and had more prior court dates and a greater frequency of contact with police, were more likely to re‐offend. The accuracy of the model was moderately high (area under the receiver operating characteristic curve = .710). A model developed specifically for the female cases failed to provide a significant increase in predictive accuracy. Conclusions These results demonstrate the feasibility of an actuarial model for juvenile offending that is suitable for automatic scoring. Although male delinquents pose a higher absolute risk of juvenile offending than female delinquents, a common set of items related to history of contact with police and social welfare agencies provide a similarly accurate measure of relative risk for both sexes.