This study examines the program- and individual-level factors that impact the success of drug court clients in terms of: (1) graduation; and (2) not being arrested while participating in the court program. The data consist of 848 individuals in nine drug courts. This paper discusses how different individual- and program-level factors impact the success of drug court participants. The findings suggest that individual- and program-level factors are both important in predicting program graduation and arrest during drug court participation, while controlling for participant demographics. Clients’ education, drug/alcohol usage, program staffing, and clinical standards impact program graduation while criminal history, drug/alcohol usage, number of program hours offered, program staffing, and use of rewards and sanctions predict in-program arrest. Models combining both program- and individual-level factors performed better than either alone, leading to recommendations that agencies should emphasize improving program quality while targeting clients’ needs to achieve greater success.
AndrewsD. A.BontaJ. (2000). The level of service inventory-revised. Multi-Health Systems.
2.
AndrewsD. A.BontaJ.HogeR. D. (1990). Classification for effective rehabilitation: Rediscovering psychology. Criminal Justice and Behavior, 17(1), 19–52. https://doi.org/10.1177%2F0093854890017001004
3.
AosS.PhippsP.BarnoskiR.LiebR. (2001). The comparative costs and benefits of programs to reduce crime, Version 4.0. Washington State Institute for Public Policy. Available at https://eric.ed.gov/?id=ED453340
BelenkoS.FabrikantN.WolffN. (2011). The long road to treatment: Models of screening and admission into drug courts. Criminal Justice and Behavior, 38(12), 1222–1243. https://doi.org/10.1177%2F0093854811424690
6.
BourgonG.ArmstrongB. (2005). Transferring the principles of effective treatment into a “real world” prison setting. Criminal Justice and Behavior, 32(1), 3–25. https://doi.org/10.1177%2F0093854804270618
7.
BravemanP.GottliebL. (2014). The social determinants of health: It’s time to consider the causes of the causes. Public Health Reports, 129(1_Suppl 2), 19–31. https://doi.org/10.1177%2F00333549141291S206
CaudyM. S.TangL.AinsworthS. A.LerchJ.TaxmanF. S. (2013). Reducing recidivism through correctional programming: Using meta-analysis to inform the RNR simulation tool. In F. S. Taxman, & A. Pattavina (Eds.), Simulation strategies to reduce recidivism (pp. 167–193). Springer.
DannerbeckA.HarrisG.SundetP.LloydK. (2006). Understanding and responding to racial differences in drug court outcomes. Journal of Ethnicity in Substance Abuse, 5(2), 1–22. https://doi.org/10.1300/J233v05n02_01
13.
DeVallK. E.LanierC. L. (2012). Successful completion: An examination of factors influencing drug court completion for white and nonwhite male participants. Substance Use & Misuse, 47(10), 1106–1116. https://doi.org/10.3109/10826084.2012.680171
14.
FestingerD. S.MarloweD. B.LeeP. A.KirbyK. C.BovassoG.McLellanA. T. (2002). Status hearings in drug court: When more is less and less is more. Drug and Alcohol Dependence, 68(2), 151–157. https://doi.org/10.1016/S0376-8716(02)00187-4
GallagherJ. R.NordbergA.DeranekM. S.IvoryE.CarltonJ.MillerJ. W. (2015). Predicting termination from drug court and comparing recidivism patterns: Treating substance use disorders in criminal justice settings. Alcoholism Treatment Quarterly, 33(1), 28–43. https://doi.org/10.1080/07347324.2015.982451
17.
GibbsB. R.LytleR.WakefieldW. (2019). Outcome effects on recidivism among drug court participants. Criminal Justice and Behavior, 46(1), 115–135. https://doi.org/10.1177%2F0093854818800528
18.
GutierrezL.BourgonG. (2012). Drug treatment courts: A quantitative review of study and treatment quality. Justice Research and Policy, 14(2), 47–77. https://doi.org/10.3818%2FJRP.14.2.2012.47
19.
HarrellA.CavanaghS.RomanJ. (1999). Findings from the evaluation of the DC superior court drug intervention program. Urban Institute.
KearleyB.GottfredsonD. (2020). Long term effects of drug court participation: Evidence from a 15-year follow-up of a randomized controlled trial. Journal of Experimental Criminology, 16(1), 27–47. https://doi.org/10.1007/s11292-019-09382-1
22.
KishL. (1965). Sampling organizations and groups of unequal sizes. American Sociological Review, 30(4), 564–572. https://doi.org/10.2307/2091346
23.
KobusK. (2009). Examining the impact of drug court participation for moderate and high risk offenders. [UNLV Theses, Dissertations, Professional Papers, and Capstones, University of Nevada, Las Vegas]. ProQuest Dissertations Publishing. https://doi.org/10.34917/2533958
MarloweD. B. (2003). Integrating substance abuse treatment and criminal justice supervision. Science & Practice Perspectives, 2(1), 4–14. https://doi.org/10.1151%2Fspp03214
27.
MarloweD. B. (2013). Who should drug treatment courts serve? Maximizing their outreach and potential impact. In CooperC. S. (chief Ed.), Drug treatment courts: An international response to drug dependent offenders. American University and Inter-American Drug Abuse Control Commission.
28.
MarloweD. B.FestingerD. S.DugoshK. L.LeeP. A. (2005). Are judicial status hearings a “key component” of drug court?: Six and twelve months outcomes. Drug and Alcohol Dependence, 79(2), 145–155. https://doi.org/10.1016/j.drugalcdep.2005.01.019
MendozaN. S.TrinidadJ. R.NochajskiT. H.FarrellM. C. (2013). Symptoms of depression and successful drug court completion. Community Mental Health Journal, 49(6), 787–792. https://doi.org/10.1007/s10597-013-9595-5
31.
MitchellO.WilsonD. B.EggersA.MacKenzieD. 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. https://doi.org/10.1016/j.jcrimjus.2011.11.009
32.
National Association of Drug Court Professionals. (1997). Defining drug courts: The key components (NCJ No. 205621). Author.
33.
National Association of Drug Court Professionals. (2018a, revision). Adult drug court best practice standards, volume I. http://nadcp.org/standards
34.
National Association of Drug Court Professionals. (2018b, revision). Adult drug court best practice standards, volume II. Available at http://nadcp.org/standards
PetersR. H.KremlingJ.BekmanN. M.CaudyM. S. (2012). Co-occurring disorders in treatment-based courts: Results of a national survey. Behavioral Sciences & the Law, 30(6), 800–820. https://doi.org/10.1002/bsl.2024
37.
PiqueroA. R.JenningsW. G.DiamondB.ReingleJ. M. (2015). A systematic review of age, sex, ethnicity, and race as predictors of violent recidivism. International Journal of Offender Therapy and Comparative Criminology, 59(1), 5–26. https://doi.org/10.1177%2F0306624X13514733
38.
PrendergastM. L.PearsonF. S.PodusD.HamiltonZ. K.GreenwellL. (2013). The Andrews’ principles of risk, needs, and responsivity as applied in drug treatment programs: Meta-analysis of crime and drug use outcomes. Journal of Experimental Criminology: Online First, 9, 275–300. https://doi.org/10.1007/s11292-013-9178-z
39.
R Core Team. (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing. Available at http://www.R-project.org/
40.
RaudenbushS. W.BrykA. S. (2002). Hierarchical Linear Models: Applications and Data Analysis Methods (Second, Vol. 1). Sage Publications.
41.
RamezaniN.BhatiA.MurphyA.RouthD.TaxmanF. (under review). Assessing the reliability and validity of the Risk-Need-Responsivity (RNR) program tool.
42.
RamezaniN.BrenoA. J.MackeyB. J.ViglioneJ.CuellarA.E.JohnsonJ. E.TaxmanF. S. (under review). Confronting mass incarceration: Association between jail population size and access to community care.
43.
RempelM.GreenM.KralsteinD. (2012). The impact of adult drug courts on crime and incarceration. Journal of Experimental Criminology, 8(3), 165–192. https://doi.org/10.1007/s11292-012-9143-2
44.
RollJ. M.PrendergastM.RichardsonK.BurdonW.RamirezA. (2005). Identifying predictors of treatment outcome in a drug court program. The American Journal of Drug and Alcohol Abuse, 31(4), 641–656. https://doi.org/10.1081/ADA-200068428
45.
RomanJ.TownsendW.BhatiA. S. (2003). Recidivism rates for drug court graduates: Nationally based estimates, final report. Caliber Associates and the Urban Institute. Available at https://www.ojp.gov/pdffiles1/201229.pdf
46.
SechrestD. K.ShicorD. (2001). Determinants of graduation from a day treatment drug court in California: A preliminary study. Journal of Drug Issues, 31(1), 129–147. https://doi.org/10.1177/002204260103100108
SolomonP.DraineJ.MarcusS. C. (2002). Predicting incarceration of clients of a psychiatric probation and parole service. Psychiatric Services, 53(1), 50–56. https://doi.org/10.1176/appi.ps.53.1.50
49.
TaxmanF. S.BelenkoS. (2012) Organizational change – technology transfer processes: A review of the literature. In TaxmanF. S.BelenkoS. (Eds.), Implementing evidence-based practices in community corrections and addiction treatment (pp. 91–128). Springer Series on Evidence-Based Crime Policy. Springer. https://doi.org/10.1007/978-1-4614-0412-5_4
50.
TaxmanF. S.PattavinaA. (Eds.). (2013). Simulation strategies to reduce recidivism: Risk Need Responsivity (RNR) modeling for the Criminal Justice System. Springer. https://doi.org/10.1007/978-1-4614-6188-3
51.
TaxmanF. S.SmithL.RudesD. S. (2020). The legacy of intensive supervision programs. In HuebnerB. M.TaxmanF. S.LattimoreP. K. (Eds.), Handbook on moving corrections and sentencing forward: Building on the record (pp. 61–78). Taylor & Francis.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
