Skip to main content

Advertisement

Springer Nature Link
Log in

Simulated evidence on the prospects of treating more drug-involved offenders

  • Published:
Journal of Experimental Criminology Aims and scope Submit manuscript

Abstract

Despite a growing consensus among scholars that substance abuse treatment is effective at reducing offending, strict eligibility rules and budgetary considerations greatly limit the impact that current models of therapeutic jurisprudence can have on public safety in the United States. A question of pressing importance for U.S. drug policy is whether it is beneficial to expand application of this model to treat every offender in need and, if so, whether a set of evidence-based, going-to-scale strategies can be developed to prioritize participation. We use evidence from several sources to construct a synthetic dataset for answering the question: What are the benefits we can reasonably expect by expanding treatment to drug-involved offenders? We combine information from the National Survey on Drug Use and Health (NSDUH) and the Arrestee Drug Abuse Monitoring (ADAM) program to estimate the likelihood of various arrestee profiles having drug addiction or dependence problems. We use the same sources to also develop prevalence estimates of these profiles among arrestees nationally. We use information in the Drug Abuse Treatment Outcome Study (DATOS) to compute expected crime-reducing benefits of treating various types of drug-involved offenders under different treatment modalities. We find that annually nearly 1.5 million (probably guilty) arrestees in the U.S. are at risk of abuse or dependence and that treatment alone could avert several million crimes that these individuals would otherwise commit. Results vary by treatment modality and arrestee traits and those results are described herein.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
€32.70 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Netherlands)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. See, among others, Anglin and Perrochet (1998), Ball et al. (1983), Brownstein et al. (1992), Condon and Smith (2003), Dawkins (1997), DeLeon (1988a, b), Harrison and Gfroerer (1992), Inciardi et al. (1996), Inciardi (1992), Inciardi and Pottieger (1994), Johnson et al. (1985), MacCoun and Reuter (2001), Miller and Gold (1994), Mocan and Tekin (2004).

  2. We use the terms “probably guilty” and “likely to be convicted” interchangeably.

  3. The conditions for substance abuse disorder focus on the frequency of drug use, the use of drugs in particular situations, negative outcomes that can be linked to the use of drugs, pronounced use of drugs in the face of evidence that drugs are contributing to personal and interpersonal problems. By contrast, the conditions for substance dependency disorder are broader ranging, including physical symptomatology, such as tolerance and withdrawal, and patterns of behavior aimed at either reducing unsuccessfully the influence of drugs or allowing for greater amounts of drugs to be taken.

  4. Information theory builds on the pioneering work of Shannon (1948). He derived a measure of uncertainty—which he called Information Entropy—for quantifying a channel's capacity to communicate information. Faced with the problem of inferring individual features from aggregate properties, Edwin Jaynes, another pioneer in this field, proposed to use Shannon's Information Entropy as an agnostic criterion to maximize (since it measures uncertainty) in order to be very conservative in what we can (or cannot) infer from these aggregate properties (Jaynes 1957a, b). Viewing an experiment (or a sample or a training dataset) as a communication device, the Maximum Entropy procedure—as it has come to be known—is therefore a very general and powerful procedure for learning from statistical evidence

  5. Rhodes et al. (2007) show that the ADAM data can lead to biased prevalence point estimates if one were to use just the annual arrest rate. However, in our analysis, we are concerned only with recovering the relative prevalence, not the absolute prevalence and feel, therefore, that our procedure accurately reflects the distribution of arrests nationwide.

  6. For example, since DATOS is nearly 20 years old, newer evidence on the effects of treating drug-involved offenders can be used to replace or augment columns in the current synthetic dataset.

References

  • Abowd, J. M., & Woodcock, S. (2001). Disclosure limitation in longitudinal linked data. In P. Doyle, J. Lane, J. Theeuwes, & L. Zayatz (Eds.), Confidentiality, disclosure and data access: Theory and practical applications for statistical agencies (pp. 215–277). Amsterdam: North Holland.

    Google Scholar 

  • Anglin, M. D., & Maugh, T. H. I. (1992). Ensuring success in interventions with drug using offenders. Annals, AAPSS, 521, 66–90.

    Google Scholar 

  • Anglin, M. D., & Perrochet, B. (1998). Drug use and crime: a historical review of research conducted by the UCLA Drug Abuse Research Center.

  • Anglin, M. D., Brecht, M. L., & Maddahian, E. (1990). Pre-treatment characteristics and treatment performance of legally coerced versus voluntary methadone maintenance admissions. Criminology, 27, 537–557.

    Article  Google Scholar 

  • Anglin, M. D., Longshore, D., & Turner, S. (1999). Treatment alternatives to street crime: an evaluation of five programs. Criminal Justice and Behavior, 26(2), 168–195.

    Article  Google Scholar 

  • Ball, J., Rosen, L., Flueck, J., & Nurco, D. (1982). Lifetime criminality of heroin addicts in the United States. Journal of Drug Issues, 3, 225–239.

    Google Scholar 

  • Ball, J. C., Shaffer, J. W., & Nurco, D. N. (1983). Day to day criminality of heroin addicts in Baltimore: a study in the continuity of offense rates. Drug and Alcohol Dependence, 12, 119–142.

    Article  Google Scholar 

  • Bhati, A. S., Roman, J. K., & Chalfin, A. (2008). To treat or not to treat: Evidence on the prospects of expanding treatment to drug-involved offenders. Washington: The Urban Institute.

    Google Scholar 

  • Blumstein, A. (2000). The replacement of drug offenders to diminish the effects of incarceration. Unpublished manuscript, Carnegie Mellon University.

  • Blumstein, A., & Cork, D. (1996). Linking gun availability to youth gun violence. Law and Contemporary Problems, 59, 5–24.

    Article  Google Scholar 

  • Boyum, D. A., & Kleiman, M. A. (2002). Substance-abuse policy from a crime-control perspective. In J. Q. Wilson & J. Petersilia (Eds.), Crime: Public policies for crime control (pp. 331–382). Oakland: Institute for Contemporary Studies.

    Google Scholar 

  • Brecht, M. L., & Anglin, D. M., Lu, T. H. (2003). Estimating drug use prevalence among arrestees using ADAM data: an application of logistic regression synthetic estimation procedure. NCJ 198829.

  • Brownstein, H. H., Shiledar Baxi, H., Goldstein, P. J., & Ryan, P. J. (1992). The relationship of drugs, drug trafficking, and drug traffickers to homicide. Journal of Crime and Justice, 15, 25–44.

    Google Scholar 

  • Caulkins, J. P., & Reuter, P. (1997). Setting goals for drug policy: harm reduction or use reduction? Addiction, 92, 1143–1150.

    Article  Google Scholar 

  • Chaiken, J. M., & Chaiken, M. R. (1990). Drugs and predatory crime. Crime and Justice, 13, 203–239.

    Article  Google Scholar 

  • Condon, J., & Smith, N. (2003). Prevalence of drug use: key findings from the 2002/2003 British Crime Survey, United Kingdom Home Office.

  • Cottler, L. B., Compton, W. M., Mager, D., Spitznagel, E., & Janca, A. (1992). Posttraumatic stress disorder among substance users from the general population. American Journal of Psychiatry, 149, 664–670.

    Google Scholar 

  • Dawkins, M. P. (1997). Drug use and violent crime among adolescents. Adolescence, 32, 395–405.

    Google Scholar 

  • Degenhardt, L., Conroy, E., Gilmour, S., & Collins, L. (2005). The effect of a reduction in heroin supply in Australia upon drug distribution and acquisitive crime. British Journal of Criminology, 45, 2–24.

    Article  Google Scholar 

  • DeLeon, G. (1988a). Legal pressure in therapeutic communities. Journal of Drug Issues, 18, 625–640.

    Google Scholar 

  • DeLeon, G. (1988b). Legal pressure in therapeutic communities. In C. G. Leukfield & F. M. Tims (Eds.), Compulsory treatment of drug abuse: Research and clinical practice (NIDA Research Monograph 86, DHHS Publication No. ADM 88-1578) (pp. 160–177). Rockville: National Institute on Drug Abuse.

    Google Scholar 

  • Fan, J., & Yao, Q. (2003). Nonlinear time series: Nonparametric and parametric methods. New York: Springer-Verlag.

    Book  Google Scholar 

  • Farrington, D. (1986). Age and crime. In N. Morris & M. Tonry (Eds.), Crime and justice. Chicago: University of Chicago Press.

    Google Scholar 

  • Finigan, M. (1998). An outcome program evaluation of the Multnomah County S.T.O.P. Drug Diversion Program. West Linn: Northwest Professional Consortium.

    Google Scholar 

  • Flynn, P. M., Kristiansen, P. L., Porto, J. V., & Hubbard, R. L. (1999). Costs and benefits of treatment for cocaine addiction in DATOS. Drug and Alcohol Dependence, 57, 167–174.

    Article  Google Scholar 

  • Freeman, R. B. (1996). Why do so many young American men commit crimes and what might we do about it? Journal of Economic Perspectives, 10, 25–42.

    Google Scholar 

  • French, M. T., Zarkin, G. A., Hubbard, R. L., & Rachal, J. V. (1993). The effects of time in drug abuse treatment and employment on posttreatment drug use and criminal activity. American Journal on Drug and Alcohol Abuse, 19, 19–33.

    Article  Google Scholar 

  • Gilboa, I., & Schmeidler, D. (1995). Case-based decision theory. Quarterly Journal of Economics, 110, 605–639.

    Article  Google Scholar 

  • Gilboa, I., & Schmeidler, D. (1997). Act similarity in case-based decision theory. Economic Theory, 9, 47–61.

    Article  Google Scholar 

  • Gilboa, I., & Schmeidler, D. (2001). A theory of case-based decisions. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Gilboa, I., Lieberman, O., & Schmeidler, D. (2006). Empirical similarity. The Review of Economics and Statistics, 88(3), 433–444.

    Article  Google Scholar 

  • Goldkamp, J. S., & Weiland, D. (1993). Assessing the impact of Dade County’s felony drug court. Washington: U.S. Department of Justice, Office of Justice Programs, National Institute of Justice.

    Google Scholar 

  • Goldstein, P. (1985). The drug/violence nexus: a tripartite conceptual framework. Journal of Drug Issues, 14, 493–506.

    Google Scholar 

  • Golub, A., & Johnson, B. D. (1997). Crack’s decline: Some surprises across U.S. cities (p. 165707). Washington: U.S. Department of Justice, National Institute of Justice, NCJ.

    Google Scholar 

  • Goodman, L. A. (1962). The variance of the product of K random variables. Journal of the American Statistical Association, 57(297), 54–60.

    Article  Google Scholar 

  • Gottfredson, D. C., & Exum, M. L. (2002). The Baltimore City drug treatment court: one-year results from a randomized study. Journal of Research in Crime and Delinquency, 39(3), 337–356.

    Article  Google Scholar 

  • Gropper, B. A. (1985). Probing the links between drugs and crime. National Institute of Justice Research in Brief. Washington: U.S. Department of Justice, National Institute of Justice.

    Google Scholar 

  • Harrell, A., & Roman, J. (2001). Reducing drug use and crime among offenders: the impact of graduated sanctions. Journal of Drug Issues, 31(1), 207–232.

    Google Scholar 

  • Harrison, L., & Gfroerer, J. (1992). The intersections of drug use and criminal behavior: results from the national household survey on drug abuse. Crime and Delinquency, 38, 422–443.

    Article  Google Scholar 

  • Hart, T. C., & Rennison, C. (2003). Reporting crime to the police, 1992–2000. Special Report. Washington: Bureau of Justice Statistics. NCJ 195710.

    Google Scholar 

  • Heckman, J. J. (2005a). The scientific model of causality. Sociological Methodology, 35, 1–97.

    Article  Google Scholar 

  • Heckman, J. J. (2005b). Rejoinder: response to Sobel. Sociological Methodology, 35, 135–162.

    Google Scholar 

  • Holloway, K. R., Bennett, T. H., & Farrington, D. P. (2006). The effectiveness of drug treatment programs in reducing criminal behavior: a meta-analysis. Psichothema, 18(3), 620–629.

    Google Scholar 

  • Hora, P. F., Schma, W. G., & Rosenthal, J. (1999). Therapeutic jurisprudence and the drug treatment court movement: revolutionizing the criminal justice system’s response to drug abuse and crime in America. Notre Dame Law Review, 74(2), 439–527.

    Google Scholar 

  • Huang, T. M., Kecman, V., & Kapriva, I. (2006). Kernel based algorithms for mining huge data sets: Supervised, semi-supervised, and unsupervised learning. Berlin: Springer-Verlag.

    Google Scholar 

  • Hubbard, R. L., Craddock, S. G., Flynn, P. M., Anderson, J., & Etheridge, R. M. (1997). Overview of 1-year follow-up outcomes in the Drug Abuse Treatment Outcome Study (DATOS). Psychology of Addictive Behaviors, 11, 261–278.

    Article  Google Scholar 

  • Inciardi, J. A. (1987). Heroin use and street crime. In C. D. Chambers, A. Inciardi, D. M. Petersen, H. A. Siegel, & O. Z. White (Eds.), Chemical dependencies: Patterns, costs, and consequences. Athens: Ohio University Press.

    Google Scholar 

  • Inciardi, J. A. (1992). The war on drugs II: The continuing epic of heroin, cocaine, crack, crime, AIDS, and the public policy. Mountain View: Mayfield Publishing Co.

    Google Scholar 

  • Inciardi, J. A., & Pottieger, A. E. (1994). Crack cocaine use and street crime. Journal of Drug Issues, 24, 273–292.

    Google Scholar 

  • Inciardi, J. A., Martin, S. S., Butzin, C. A., Hooper, R. M., & Harrison, L. D. (1996). An effective model of prison-based treatment for drug-involved offenders. Journal of Drug Issues, 27(2), 261–278.

    Google Scholar 

  • Jaynes, E. T. (1957a). Information theory and statistical mechanics. Physics Review, 106, 620–630.

    Article  Google Scholar 

  • Jaynes, E. T. (1957b). Information theory and statistical mechanics II. Physics Review, 108, 171–190.

    Article  Google Scholar 

  • Johnson, B. D., Goldstein, P. J., Preble, E., Schmeidler, J., Lipton, D. S., Spunt, B., et al. (1985). Taking care of business: The economics of crime by heroin users. Lexington: Lexington Books.

    Google Scholar 

  • Kaplan, E. H., & Johri, M. (2000). Treatment on demand: an operational model. Health Care Management Science, 3(3), 171–183.

    Article  Google Scholar 

  • Karberg, J., & James, J. (2005). Substance dependence, abuse, and treatment of jail inmates, 2002. Washington: U.S. Department of Justice, Office of Justice Programs, Bureau of Justice Statistics.

    Google Scholar 

  • Kleiman, M. A. R. (1997). Coerced abstinence: a neo-paternalistic drug policy initiative. In L. A. Mead (Ed.), The new paternalism. Washington: Brookings Institution Press.

    Google Scholar 

  • Lewis, B. F., & Ross, R. (1994). Retention in therapeutic communities: challenges for the nineties. In F. M. Tims, G. De Leon, & N. Jainchill (Eds.), Therapeutic community: Advances in research and application (pp. 99–116). Washington: Government Printing Office.

    Google Scholar 

  • Lipsey, M. W., & Cullen, F. T. (2007). The effectiveness of correctional rehabilitation: a review of systematic reviews. Annual Review of Law and Social Science, 3, (in press).

  • Loader, C. (1999). Local regression and likelihood. New York: Springer-Verlag.

    Google Scholar 

  • Longshore, D., Urada, D., Evans, E., Hser, Y., Prendergast, M., Hawken, A., et al. (2004). Evaluation of the substance abuse and crime prevention act report. Department of Alcohol and Drug Programs California Health and Human Services Agency. Los Angeles: UCLA Integrated Substance Abuse Programs.

    Google Scholar 

  • MacCoun, R. J., & Reuter, P. (2001). Drug war heresies: Learning from other vices, times, and places. New York: Cambridge University Press.

    Google Scholar 

  • MacCoun, R. J., Kilmer, B., & Reuter, P. (2003). Research on drug-crime linkages: the next generation. In Toward a drugs and crime research agenda for the 21st century. National Institute of Justice Special Report.

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

    Book  Google Scholar 

  • Manski, C. F., Pepper, J. V., & Thoms, Y. F. (1999). Assessment of two cost-effectiveness studies on cocaine control policy. Washington: National Academy Press.

    Google Scholar 

  • Marlowe, D. B., Festinger, D. S., & Lee, P. A. (2004). The judge is a key component of drug court. National Drug Court Institute Review, 4(2), 1–34.

    Google Scholar 

  • Miller, N. S., & Gold, M. S. (1994). Criminal activity and crack addiction. The International Journal of Addictions, 29, 1069–1078.

    Google Scholar 

  • Mocan, H. N., & Tekin, E. (2004). Guns, drugs and juvenile crime: evidence from a panel of siblings and twins. IZA Discussion Paper No. 932.

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

    Google Scholar 

  • Nagin, D. S. (2005). Group based models of development. Boston: Harvard University Press.

    Google Scholar 

  • Nagin, D. S., & Paternoster, R. (1991). On the relationship of past and future participation in delinquency. Criminology, 29, 163–190.

    Article  Google Scholar 

  • National Institute on Drug Abuse. (1999). Principles of drug addiction treatment: A research-based guide. Rockville: NIDA. NIH Publication No. 99-4180.

    Google Scholar 

  • Nurco, D. N., Kinlock, T. W., & Hanlon, T. E. (1990). The drugs crime connection. In J. A. Inciardi (Ed.), Handbook of drug control in the United States (pp. 71–90). Westport: Greenwood Press.

    Google Scholar 

  • Pagan, A., & Ullah, A. (1999). Nonparametric econometrics. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Peters, R. H., & Murrin, M. R. (2000). Effectiveness of treatment-based drug courts in reducing criminal recidivism. Criminal Justice and Behavior, 27(1), 72–96.

    Article  Google Scholar 

  • Piquero, A. R., Farrington, D. P., & Blumstein, A. (2003). The criminal career paradigm. In M. Tonry (Ed.), Crime and justice: A review of research, vol. 30 (pp. 359–506). Chicago: University of Chicago Press.

    Google Scholar 

  • Raghunathan, T. E., Reiter, J. P., & Rubin, D. B. (2003). Multiple imputation for statistical disclosure limitation. Journal of Official Statistics, 19(2003), 1–19.

    Google Scholar 

  • Reiter, J. (2002). Satisfying disclosure restrictions with synthetic data sets. Journal of Official Statistics, 18, 531–544.

    Google Scholar 

  • Reiter, J. (2003) Releasing multiply-imputed, synthetic public use microdata: An illustration and empirical study. Journal of the Royal Statistical Society, Series A.

  • Reuter, P., MacCoun, R., & Murphy, P. (1990). Money from crime. Santa Monica: RAND.

    Google Scholar 

  • Rhodes, W., Layne, M., Johnston, P., & Hozik, L. (2000). What America’s users spend on illegal drugs: 1988–1998. Washington: Office of National Drug Control Policy.

    Google Scholar 

  • Rhodes, W., Kling, R., & Johnston, P. (2007). Using booking data to model drug user arrest rates: a preliminary to estimating the prevalence of chronic drug use. Journal of Quantitative Criminology, 23, 1–22.

    Article  Google Scholar 

  • Roman, C. G., Ahn-Redding, H., & Simon, R. J. (2005). Illicit drug policies, trafficking and use the world over. New York: Lexington Books.

    Google Scholar 

  • Rossman, S. B., Zweig, J., & Roman, J. (2007). A portrait of adult drug courts. Washington: The Urban Institute.

    Google Scholar 

  • Senjo, S., & Leip, L. A. (2001). Testing therapeutic jurisprudence theory: an empirical assessment of the drug court process. Western Criminology Review, 3, 1.

    Google Scholar 

  • Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27, 379–423.

    Google Scholar 

  • Silverman, B. W. (1986). Density estimation for statistics and data analysis. London: Chapman and Hall.

    Google Scholar 

  • Simpson, D. D., Joe, G. W., & Brown, B. S. (1997). Treatment retention and follow-up outcomes in the Drug Abuse Treatment Outcome Study (DATOS). Psychology of Addictive Behaviors, 11, 294–307.

    Article  Google Scholar 

  • Simpson, D. D., Joe, G. W., Fletcher, B. W., Hubbard, R. L., & Anglin, M. D. (1999). A national evaluation of treatment outcomes for cocaine dependence. Archives of General Psychiatry, 56, 507–514.

    Article  Google Scholar 

  • Simpson, D. D., Joe, G. W., & Broome, K. M. (2002). A national 5-year follow-up of treatment outcomes for cocaine dependence. Archives of General Psychiatry, 59, 538–544.

    Article  Google Scholar 

  • Slobogin, C. (1995). Therapeutic jurisprudence: five dilemmas to ponder. Psychology, Public Policy and Law, 1, 193–196.

    Article  Google Scholar 

  • Soble, M. E. (2005). Discussion: the scientific model of causality. Sociological Methodology, 35, 99–133.

    Article  Google Scholar 

  • Speckert, G. R., & Anglin, M. D. (1986). Narcotics and crime: a causal modeling approach. Journal of Quantitative Criminology, 2, 3–28.

    Article  Google Scholar 

  • Stewart, D., Gossop, M., Marsden, J., & Rolfe, A. (2000). Drug misuse and acquisitive crime among clients recruited to the National Treatment Outcome Research Study (NTORS). Criminal Behaviour and Mental Health, 10, 10–20.

    Article  Google Scholar 

  • United Nations Office of Drug Control and Crime. (2003). Global Illicit Drug Trends.

  • United Nations Office of Drug Control and Crime. (2005). World Drug Report.

  • Vito, G. F. (1989). The Kentucky Substance Abuse Program: a private program to treat probationers and parolees. Federal Probation, 65–72.

  • Wexler, D. B., & Winick, B. J. (1991). Therapeutic jurisprudence as a new approach to mental health law policy analysis and research. University of Miami Law Review, 979.

  • Wilson, D. B., Mitchell, O., & MacKenzie, D. L. (2006). A systematic review of drug court effects on recidivism. Journal of Experimental Criminology, 2(4), 459–487.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Maxarth LLC, 509 Cedar Spring Street, Gaithersburg, MD, 20877, USA

    Avinash Singh Bhati & John K. Roman

Authors
  1. Avinash Singh Bhati
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. John K. Roman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Avinash Singh Bhati.

Additional information

This research was supported by a grant from the National Institute of Justice. Views expressed here are the authors’ and do not reflect the official position of policies of the Department of Justice, Maxarth LLC, nor the Urban Institute, its trustees, or funders.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bhati, A.S., Roman, J.K. Simulated evidence on the prospects of treating more drug-involved offenders. J Exp Criminol 6, 1–33 (2010). https://doi.org/10.1007/s11292-010-9088-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11292-010-9088-2

Keywords

Search

Navigation