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Description
The author examines drug court as a means to reduce recidivism rates for individuals who are addicted to illegal substances. The thesis analyzes the best practices for drug courts in treating addiction and lowering recidivism. In conducting this analysis, the

The author examines drug court as a means to reduce recidivism rates for individuals who are addicted to illegal substances. The thesis analyzes the best practices for drug courts in treating addiction and lowering recidivism. In conducting this analysis, the author focuses on the Yuma County Drug Court Program (YCDC). After discussing the major components of the YCDC program, the author reaches several conclusions about the program. The author's conclusions are based in part on a study analyzing the recidivism rates for individuals who participated in YCDC from January 1, 2007 through December 31, 2010. The author concludes that an effective drug court program requires proper screening and assessment using validated assessment tools that ensure delivery of treatment to individuals with high substance abuse treatment needs. In addition, drug courts must include counseling in both sober individual and group settings, cognitive restructuring, life skills training, and frequent interaction with the drug court judge. The author also concludes that drug courts are more successful when they stress accountability and independence by requiring participants to maintain a stable residence and employment. In YCDC these practices lead to 48.4% of individuals participating in the 18-month program having no criminal justice involvement for a period of three years after their exit from the program. Other important outcomes showed that well over 90% of the participants' drug tests were negative and 87% of the participants were employed. The author concludes that the YCDC program provides a good model for drug courts seeking to lower recidivism.
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Details

Title
  • Drug Courts: A Method to Reduce Recidivism
Contributors
Date Created
2018-05
Resource Type
  • Text
  • Machine-readable links