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Predicting Pretrial Misconduct With Drug Tests of Arrestees: Evidence From Eight Settings

NCJ Number
163379
Journal
Journal of Quantitative Criminology Volume: 12 Issue: 3 Dated: (September 1996) Pages: 315-346
Author(s)
W Rhodes; R Hyatt; P Scheiman
Date Published
1996
Length
32 pages
Annotation
The research reported in this article questions whether the incremental predictive power that results from the drug testing of arrestees always improves predictions of pretrial misconduct.
Abstract
Identifying arrestees at high risk of pretrial misconduct is a major problem for the judiciary. Currently, some have argued that testing arrestees for recent drug use is one way to distinguish between those who will and those who will not commit pretrial misconduct. Using survival analysis to study time until rearrest and a probit model to analyze the occurrence of a failure to appear, the study found that urine test results have no consistent power to predict pretrial misconduct after accounting for defendant's criminal records, community ties, and other factors commonly considered by the court. These results are based on the analysis of eight data sets from different locales, time periods, and age groups. The authors acknowledge that the findings of this research do not settle the debate about the predictive value of pretrial drug testing, but they do provide additional data for the debate. They advise that considering how drug test results might be improved may be a fruitful strategy. In the authors' view, much of the ambiguity about the utility of drug testing derives from the fact that drug tests cannot separate high-rate and low-rate users. One approach that may do this is to use more than one urine test to make predictions. Drug-test results from two or more sequential arrests may be used to establish that the arrestee is a "problem user." Toberg et al. (1989) and Visher (1990) report that defendants who fail multiple drug tests during pretrial release are most likely to engage in pretrial misconduct. Retrospective drug tests may be equally useful. 4 tables and 47 references