Skip to main content

Alternative models of instant drug testing: evidence from an experimental trial

Abstract

Objective

This study describes and provides relapse and recidivism outcome findings related to an experimental trial evaluating the viability of frequent, random drug testing with consequences for use.

Methods

The sample consisted of 529 offenders released on parole. An experimental design with random assignment to one of three groups was employed. The Experimental Group received frequent, random drug testing with instant results, immediate sanctions, and referral for substance abuse treatment. Control Group I received frequent, random drug testing and treatment referral, but did not receive immediate test results or immediate sanctions. Control Group II followed standard parole practice. Members of this group were not tested on a random basis and did not receive immediate sanctions. Repeated measures ANOVA and survival analysis techniques were used to explore group differences.

Results

Frequent monitoring of drug use with randomized testing protocols, immediate feedback, and certain consequences is effective in lowering rates of relapse and recidivism. The effectiveness is particularly salient in the short term during the period of exposure to testing conditions.

Conclusions

The findings lend support to the use of randomized testing with swift and certain sanctions with parolees. Additional quality evidence is necessary to generalize and refine findings from this study and others that focus on sanction certainty. Future replications must consider the immediacy of test result and sanction execution as well as the length of exposure to randomized testing periods.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2

Notes

  1. The reason for the below average tests per week was that the initial protocol called for tests to be administered 7 days a week. However, weekend staffing issues at the local jail led to tests only being administered during the traditional working week. The protocol was revised to 5 days a week  prior to the start of the program. Test per week data use 7 as a denominator, which lowers calculated averages.

  2. As a check on the sensitivity of the results, random effect probit models were estimated. The random effect models allowed for individual variation in the response to the experimental conditions. There were no differences between the random effect and ANOVA models with regard to the experimental conditions. Identical results were obtained. The random effect models did caution the interpretation of the interaction effects of time for the proportion of participants with at least one positive and the main effects of time in the rate of positive testing. It is clear the group differences present at 6 months remain at 18 months for both indicators of relapse, which explains why the effect of time was not significant in the random effect models. As a result, the effect of time should be interpreted from the ANOVA models with this context in mind.

  3. Random effect probit models were also estimated to check the sensitivity of recidivism outcomes. Once again, identical results were obtained. There were no differences between the random effect and ANOVA models.

References

  • Andrews, D., & Bonta, J. (2006). The psychology of criminal conduct (4th ed.). Newark: Anderson.

    Google Scholar 

  • Andrews, D., Zinger, I., Hoge, R. D., Bonta, J., Gendreau, P., & Cullen, F. (1990). Does correctional treatment work? A clinically relevant and psychologically informed meta-analysis. Criminology, 28(3), 369–404.

    Article  Google Scholar 

  • Anglin, M. D., & Hser, Y. I. (1990). Treatment of drug abuse. In M. Tonry & J. Q. Wilson (Eds.), Drugs and crime (pp. 393–460). Chicago: University of Chicago Press.

    Google Scholar 

  • Aos, S., Phipps, P., Barnoski, R., & Lieb, R. (2001). The comparative costs and benefits of programs to reduce crime. Olympia: Washington State Institute for Public Policy.

    Google Scholar 

  • Aos, S., Miller, M., & Drake, E. (2006). Evidence-based adult corrections programs: What works and what does not. Olympia: Washington State Institute for Public Policy.

    Google Scholar 

  • Beck, A. J., & Shipley, B. E. (1989). Recidivism of prisoners released in 1983. Washington, DC: US Department of Justice, Office of Justice Programs, Bureau of Justice Statistics.

    Google Scholar 

  • Belenko, S. (2001). Research on drug courts: A critical review 2001 update. New York: The National Center on Addiction and Substance Abuse at Columbia University.

    Google Scholar 

  • Boyum, D. A., Caulkins, J. P., & Kleiman, M. A. R. (2010). Drugs, crime, and public policy. In J. Q. Wilson & J. Petersilia (Eds.), Crime and public policy (2nd ed., pp. 368–410). New York: Oxford University Press.

    Google Scholar 

  • Breslow, N. (1970). A generalized Kruskal-Wallis test for comparing k samples subject to unequal patterns of censorship. Biometrika, 57(3), 579–594.

    Article  Google Scholar 

  • Carns, T. W., & Martin, S. (2011). Anchorage PACE probation accountability with certain enforcement: A preliminary evaluation of the Anchorage pilot PACE project. Anchorage: Alaska Judicial Council.

    Google Scholar 

  • Carver, J. A. (2004). Drug testing: A necessary prerequisite for treatment and for crime control. In P. Bean & T. Nemitz (Eds.), Drug treatment: What works? (pp. 142–177). New York: Routledge.

    Google Scholar 

  • Center for Substance Abuse Research. (1994). Oregon STOP program for probationers. College Park: University of Maryland.

    Google Scholar 

  • Chandler, R. K., Fletcher, B. W., & Volkow, N. D. (2009). Treating drug abuse and addiction in the criminal justice system: improving public health and safety. Journal of the American Medical Association, 301(2), 183–190.

    Article  Google Scholar 

  • Chanhatasilpa, C., MacKenzie, D., & Hickman, L. (2000). The effectiveness of community-based programs for chemically dependent offenders: a review and assessment of research. Journal of Substance Abuse Treatment, 19(4), 383–393.

    Article  Google Scholar 

  • Cox, D. R. (1972). Regression models and life tables (with discussion). Journal of the Royal Statistical Society, Series B, 34, 187–220.

    Google Scholar 

  • D’Agostino, R. B. (1971). A second look at analysis of variance on dichotomous data. Journal of Educational Measurement, 8(4), 327–333.

    Article  Google Scholar 

  • Durlauf, S. N., & Nagin, D. S. (2011). Imprisonment and crime: can both be reduced? Criminology and Public Policy, 10(1), 13–54.

    Article  Google Scholar 

  • Fletcher, B. W., & Chandler, R. K. (2006). Principles of drug abuse treatment for criminal justice populations: A research-based guide. Washington, DC: National Institute on Drug Abuse.

    Google Scholar 

  • Fletcher, B. W., Lehman, W. E. K., Wexler, H. K., Melnick, G., Taxman, F. S., Young D. W. (2009). Measuring collaboration and integration activities in criminal justice and substance abuse treatment agencies. Drug and Alcohol Dependence, 103(Suppl. 1), S54–S64.

    Article  Google Scholar 

  • Friedmann, P. D., Rhodes, A. G., & Taxman, F. S. (2009). Collaborative behavioral management: integration and intensification of parole and outpatient addiction treatment services in the Step’n Out study. Journal of Experimental Criminology, 5, 227–243.

    Article  Google Scholar 

  • Gill, C. E. (2010). The effects of sanction intensity on criminal conduct: A randomized low-intensity probation experiment. Dissertation, University of Pennsylvania. (Publicly accessible Penn Dissertation Paper 121).

  • Glaze, L. E., Bonczar, T. P., & Zhang, F. (2010). Probation and parole in the United States, 2009. Washington, DC: US Department of Justice, Office of Justice Programs, Bureau of Justice Statistics.

    Google Scholar 

  • Gottfredson, D. C., Najaka, S. S., & Kearly, B. (2003). Effectiveness of drug treatment courts: evidence from a randomized trial. Criminology and Public Policy, 2(2), 171–196.

    Article  Google Scholar 

  • Haapanen, R., & Britton, L. (2002). Drug testing for youthful offenders on parole: an experimental evaluation. Criminology and Public Policy, 1(2), 217–244.

    Article  Google Scholar 

  • Harrell A., Kleiman M. A. R. (2001) Drug testing in criminal justice settings. In C. Leukefeld & F. Tims (Eds). Treatment of Drug Offenders: Policies and Issues (pp 149–171). New York: Springer,

  • Harrell, A., & Roman, J. (2001). Reducing drug use and crime among offender: the impact of graduated sanctions. Journal of Drug Issues, 31, 207–232.

    Article  Google Scholar 

  • Harrell, A., Mitchell, O., Hirst, A., Marlowe, D., & Merrill, J. (2002). Breaking the cycle of drugs and crime: findings from the Birmingham BTC demonstration. Criminology and Public Policy, 1(2), 189–216.

    Article  Google Scholar 

  • Hawken, A. (2010). Behavioral triage: A new model for indentifying and treating substance-abusing offenders. Journal of Drug Policy Analysis, 3(1), available at http://www.bepress.com/jdpa/vol3/iss1/art1.

  • Hawken, A., & Kleiman, M. A. R. (2009). Managing drug involved probationers with swift and certain sanctions: Evaluating Hawaii’s HOPE. Washington, DC: US Department of Justice.

    Google Scholar 

  • Hawken, A., & Kleiman, M. A. R. (2011). Washington intensive supervision program: Evaluation report. Seattle: Seattle City Council.

    Google Scholar 

  • Hoffman, P. B., & Beck, J. L. (1974). Parole decision-making: a salient factor score. Journal of Criminal Justice, 2(3), 195–206.

    Article  Google Scholar 

  • Honig, W. K., & Staddon, J. E. R. (1977). The handbook of operant behavior. Englewood Cliffs: Prentice-Hall.

    Google Scholar 

  • Inciardi, J. A., Martin, S. S., & Butzin, C. A. (2004). Five-year outcomes of therapeutic community treatment of drug-involved offenders after release from prison. Crime & Delinquency, 50(1), 88–107.

    Article  Google Scholar 

  • King, R. S., & Mauer, M. (2002). Distorted priorities: Drug offenders in state prisons. Washington, DC: The Sentencing Project.

    Google Scholar 

  • Kleiman, M. A. R. (1988). Street-level drug enforcement: examining the issues. Washington, DC: U.S. Department of Justice, National Institute of Justice.

    Google Scholar 

  • Kleiman, M. A. R. (2009). When brute force fails: How to have less crime and less punishment. Princeton: Princeton University Press.

    Google Scholar 

  • Kleiman, M., Tran, T.H., Fishbein, P., Magula, M., Allen, W., Lacy, G. (2003).Opportunities and barriers in probation reform: A case study in drug testing andsanctions. Oakland, CA: California Policy Research Center.

  • Knight, K., Simpson, D. D., & Hiller, M. L. (1999). Three-year reincarceration outcomes for in-prison therapeutic community treatment in Texas. The Prison Journal, 79(3), 337–351.

    Article  Google Scholar 

  • Landenberger, N. A., & Lipsey, M. W. (2005). The positive effects of cognitive-behavioral programs for offenders: a meta-analysis of factors associated with effective treatment. Journal of Experimental Criminology, 1(4), 451–476.

    Article  Google Scholar 

  • Langan, P. A., & Levin, D. J. (2002). Recidivism of prisoners released in 1994. Washington, DC: US Department of Justice, Office of Justice Programs, Bureau of Justice Statistics.

    Google Scholar 

  • Lattimore, P. K., & Visher, C. A. (2010). The multi-site evaluation of SVORI: Summary and synthesis. Research Triangle: RTI International.

    Google Scholar 

  • Lunney, G. H. (1970). Using analysis of variance with dichotomous dependent variable: an empirical study. Journal of Educational Measurement, 7(4), 263–269.

    Article  Google Scholar 

  • MacKenzie, D. L. (2000). Evidence-based corrections: identifying what works. Crime and Delinquency, 46(4), 457–471.

    Article  Google Scholar 

  • MacKenzie, D. L. (2006). What works in corrections: Reducing the criminal activities of offenders and delinquents. New York: Cambridge University Press.

    Book  Google Scholar 

  • Mallik-Kane, D., & Visher, C. A. (2008). Health and prisoner reentry: How physical, mental, and substance abuse conditions shape the process of reintegration. Washington, DC: Urban Institute.

    Google Scholar 

  • Martin, S. S., Butzin, C. A., Saum, C. A., & Inciardi, J. A. (1999). Three year outcomes of therapeutic community treatment for drug involved offenders in Delaware: from prison to work release to aftercare. The Prison Journal, 79(3), 294–320.

    Article  Google Scholar 

  • Mitchell, O., Wilson, D. B., & MacKenzie, D. L. (2007). Does incarceration-based drug treatment reduce recidivism? A meta-analytic synthesis of the research. Journal of Experimental Criminology, 3(4), 353–375.

    Article  Google Scholar 

  • Mitchell, O., Wilson, D. B., Eggers, A., & MacKenzie, D. L. (2012). Assessing the effectiveness of drug courts on recidivism: a meta-analytic review of traditional and non-traditional drug courts. Journal of Criminal Justice, 40(1), 60–71.

    Article  Google Scholar 

  • Mumola, C. J., & Karberg, J. C. (2006). Drug use and depdenence, state and federal prisoners, 2004. Washington, DC: US Department of Justice, Office of Justice Programs, Bureau of Justice Statistics.

    Google Scholar 

  • National Research Council (2008). Parole, Desistance from crime, and community integration. Committee on Community Supervision and Desistance from Crime. Committee on Law and Justice, Division of Behavioral and Social Sciences and Education. The National Press, Washington, DC.

  • O’Connell, D., Visher, C. A., Martin, S., Parker, L., & Brent, J. (2011). Decide your time: testing deterrence theory’s certainty and celerity effects on substance-using probationers. Journal of Criminal Justice, 39(3), 261–267.

    Article  Google Scholar 

  • Office of Justice Programs. (2011). Demonstration and evaluation of HOPE: An innovative probation program. Retrieved from http://www.ojp.usdoj.gov/funding/hopesol.htm.

  • Pearson, F. S., Lipton, D. S., Cleland, C. M., & Yee, D. S. (2002). The effects of behavioral/cognitive-behavioral programs on recidivism. Crime and Delinquency, 48(3), 476–496.

    Google Scholar 

  • Perry, A. E., Darwin, Z., Godfrey, C., McDougall, C., Lunn, J., Glanville, J., & Coulton, S. (2009). The effectiveness of interventions for drug-using offenders in the courts, secure establishments and the community: a systematic review. Substance Use and Misuse, 44(3), 374–400.

    Article  Google Scholar 

  • Prendergast, M. L. (2009). Interventions to promote successful re-entry among drug-abusing parolees. Addiction Science and Clinical Practice, 5(1), 4–13.

    Article  Google Scholar 

  • Prendergast, M., Podus, D., Finney, J., Greenwell, L., & Roll, J. (2006). Contingency management for treatment of substance use disorders: a meta-analysis. Addiction, 101(11), 1546–1560.

    Article  Google Scholar 

  • Sherman, L. W., Gottfredson, D., MacKenzie, D., Eck, J., Reuter, P., & Bushway, S. (1997). Preventing crime: What works, what doesn't, and what's promising. A report to the United States Congress. College Park, MD: University of Maryland.

    Google Scholar 

  • Skinner, B. F. (1938). The behavior of organisms. New York: Appleton, Century, Crofts.

    Google Scholar 

  • Solomon, A. L., Osborne, J., Winterfield, L., Elderbroom, B., Burke, P., Stroker, R. P., Rhine, E. E., & Burrell, W. D. (2008). Putting public safety first: 13 parole supervision strategies to enhance reentry outcomes. Washington, DC: Urban Institute.

    Google Scholar 

  • Sourcebook of Criminal Justice Statistics. (2011). Adults on probation, in jail or prison, and on parole. Retrieved from http://www.albany.edu/sourcebook/pdf/t612009.pdf.

  • Tarone, R. E., & Ware, J. (1977). On distribution-free tests for equality of survival distributions. Biometrika, 64(1), 156–160.

    Article  Google Scholar 

  • Taxman, F. S. (2008). No illusions: offender and organizational change in Maryland’s proactive community supervision efforts. Criminology and Public Policy, 7(2), 275–302.

    Article  Google Scholar 

  • Taxman, F. S., Soule, D., & Gelb, A. (1999). Graduated sanctions: stepping into accountable systems and offenders. The Prison Journal, 79(2), 182–205.

    Article  Google Scholar 

  • Wexler, H. K., Melnich, G., Lowe, L., & Peters, J. (1999). Three-year reincarceration outcomes for Amity in-prison therapeutic community and aftercare in California. The Prison Journal, 79(3), 321–336.

    Article  Google Scholar 

  • Wodahl, E. J., Garland, B., Culhane, S. E., & McCarty, W. P. (2011). Utilizing behavioral interventions to improve supervision outcomes in community-based corrections. Criminal Justice and Behavior, 38(4), 386–405.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Eric Grommon.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Grommon, E., Cox, S.M., Davidson, W.S. et al. Alternative models of instant drug testing: evidence from an experimental trial. J Exp Criminol 9, 145–168 (2013). https://doi.org/10.1007/s11292-012-9168-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11292-012-9168-6

Keywords

  • Community supervision
  • Conditions evaluation
  • Corrections
  • Parolees
  • Prisoner reentry
  • Substance use