NCJ Number
202298
Journal
Journal of Criminal Justice Volume: 31 Issue: 5 Dated: September/October 2003 Pages: 455-467
Date Published
September 2003
Length
13 pages
Annotation
This study used data from a drug-treatment follow-up study to determine the predictive utility of factors associated with latent trait and life-course models of criminal offending among a sample of serious drug users.
Abstract
In the theoretical model that underlies the hypotheses tested in this study, the latent variables of "aggression" and "risky" were anticipated to have a negative effect on the various social-bonding variables at 6 months after release from prison and a positive effect on the likelihood of being arrested and frequency of drug use 18 months after release. Data for this study were obtained from the Ongoing Studies Project for Those at Risk for Drug Use (1997). The project was designed to test the effects of various treatment modalities on Delaware State prison inmates. Data collection was ongoing, with the ultimate goal of following participants for 5 years. The sample consisted of 1,762 men and women. The analysis used a sample of 576 persons (452 males and 124 females), who completed baseline, 6-month, and 18-month interviews. All participants were convicted offenders with serious drug problems who were serving sentences in State prison at the start of the study. Two dependent variables were used to measure whether participants recidivated at the 18-month follow-up. Independent variables consisted of social-control and latent-trait variables. Separate structural equation models were estimated for each of the social-bond variables (married, school, and working). The findings showed that although "aggression" was negatively associated with social bonds and positively related to drug use and arrest, sensation-seeking ("risky") was not significant in predicting social bonds, and it was negatively associated with drug use. Employment and school were negatively associated with drug use and arrest, and marriage was not significant in predicting drug use and arrest. 1 table and 47 references