Drug Courts: The Best Can Get Better
Drug Courts
Drug courts: the best can get better i
Drug Courts: The Best Solution
Can Get Better
It has taken nearly two decades for consensus to solidify but now most authors agree that drug courts reduce recidivism and long-term social cost. Huddleston, Marlowe and Casebolt argue that "no other justice intervention can rival the results produced by drug courts" (2008, p. 2). Drug courts are the most cost effective way we have found of improving addiction treatment results and reducing crime (Huddleston, Marlowe and Casebolt, 2008, p. 5). Congress agrees and asserts the economic benefits very likely far exceed what we are able to tally directly (United States Government Accountability Office, 2005, p. 74). This masks significant differences both within and between programs. Not all drug court programs are the same, and not all offenders respond the same within the same drug court (Roman, Townsend and Bhati, 2003, p. 1).
As of 2008, 59% of drug courts were post-conviction; 7% were diversionary, pre-plea models, and 19% were hybrids of both (Huddleston, Marlowe and Casebolt, 2008, p. 4). 78% of the 1174 U.S. drug courts at that time had postplea / probationary programs. Huddleston, Marlowe and Casebolt conclude this implies the trend has become to focus on "higher risk and higher need offender" populations (2008, p. 5). Programs have been studied widely enough that cross-study "meta-analysis" is beginning to deliver "definitive evidence" for both the effectiveness and cost savings from drug court programs (Huddleston, Marlowe and Casebolt, 2008, p. 5). The consensus is that drug courts reduce crime rates from 7-14% on average, with high results of 35% in crime reduction (Huddleston, Marlowe and Casebolt, 2008, p. 5). The United States Government Accountability Office (USGAO) found an average of 10-30% less recidivism for drug court participants compared to a control group of non-drug court offenders, with similar duration effects over time (2005, p. 45-46). Drug court clients also went longer before re-arrest and had lower re-conviction rates than similar offenders in traditional courts (United States Government Accountability Office, 2005, p. 49).
What these results ultimately point out, however, is the wide variation within these broader claims of success. Since differences arise comparing drug court systems in measuring recidivism by re-arrest, conviction or reincarceration (Roman, Townsend and Bhati, 2003, p. 12-13), different offender demographics and eligibility characteristics are often bundled into aggregate success rates. While program completion usually indicates lower recidivism rates, and compliance with program procedures indicates likelihood of completion, specific program components vary so widely and have such varying effects that no particular component emerges as the best design element beyond compliance with supervision mandates (United States Government Accountability Office, 2005, p. 49). The magic bullet for either recidivism or relapse has remained elusive because of the wide divergence between programs, which result in barriers to robust analysis.
The pattern of drug abuse coming into courts has been found to vary over rural, suburban and urban locations. Rural drug courts see more methamphetamine arrests; marijuana and alcohol are the primary problem drug in suburban areas, and crack/cocaine predominates in urban courts in 74% of states (Huddleston, Marlowe and Casebolt, 2008, p. 8). This is significant because the different drug choices indicate varying degrees of completion within and across different courts. Recidivism rates depend on which drug violators are identified as primarily using, correlated to the concentration of cocaine and/or heroin addiction compared to alcohol and marijuana offenses rather than individual drug court recidivism rates across uniform proportions of each (Roman, Townsend and Bhati, 2003, p. 5-6).
These averages mask differences between drug courts, however, although the majority were close to the average with the highest rates where...
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