Effects of Drug Courts on Drug Abuse and Criminal Offending Research Paper

  • Length: 5 pages
  • Sources: 5
  • Subject: Sports - Drugs
  • Type: Research Paper
  • Paper: #73665541

Excerpt from Research Paper :

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 courts served the most "difficult to reach" clients, rather than demonstrating weak performance for certain courts across identical populations (Roman, Townsend and Bhati, 2003, p. 5). Drug courts with higher absolute volume also experienced significantly lower performance measured in recidivism than smaller courts, by up to 8% after two years (Roman, Townsend and Bhati, 2003, p. 6). The largest courts are located in the largest cities with also the highest severity of abuse (Roman, Townsend and Bhati, 2003, p. 7). Higher-risk offenders are starting to emerge as the most likely to improve compared to other drug court clients and similar conventional-court drug offenders (Huddleston, Marlowe and Casebolt, 2008, p. 5). Higher risk, more chronic drug offenders with longer abuse history have been found to achieve better drug-court outcomes the more frequently their required hearings took place (Huddleston, Marlowe and Casebolt, 2008, p. 4).

The skyrocketing numbers of methamphetamine offenders display both of these characteristics, rural concentration and more persistent and criminal dependence requiring longer and more intensive intervention (Huddleston, Marlowe and Casebolt, 2008, p. 16). Drug court seems to be the most successful tool corrections has ever employed for reducing long-term methamphetamine addiction (Huddleston, Marlowe and Casebolt, 2008, p. 16).

Likewise different clients with different demographic characteristics within the various severity classifications succeed at different rates. Roman, Townsend and Bhati find significant differences between gender, race, ethnicity and age groups across all study courts (2003, p. 7). Women have higher success rates than men, Whites are re-arrested less often than non-Black minorities, who experience lower recidivism rates than Blacks (Roman, Townsend and Bhati, 2003, p. 7). Age also correlates with higher success rates, with wide dispersion, where the youngest demonstrate significantly worse performance than the median age, while the oldest cohorts score far higher than the median. The USGAO research supports these findings (2005, p. 69). These results, however, hide meaningful difference between eligibility characteristics and reporting for different courts, and the authors caution against comparing reported outcomes across jurisdictions (Roman, Townsend and Bhati, 2003, p. 7).

While recidivism measures are becoming standardized and improving over time, courts' ability to assess ongoing drug abuse has been limited at best after supervision ends, and some results are based on self-reporting rather than more definitive testing like urinalysis. The USGAO reports mixed results at best due to the weakness of available information on relapse rates after graduation, which requires law enforcement to obtain expensive, questionable and misrepresentative voluntary participation (2005, p. 59). While relapse rates fell during-program for a majority of the studied courts when defined through urinalysis, self-reporting both contradicted the urinalysis results in some cases, and displayed contracticting results between the various drug courts such that no verifiable trend or correlation emerged (United States Government Accountability Office, 2005, p. 60). Higher frequency of judicial review seems to reduce relapse rates but the data is still inconclusive.

Goldkamp set out a list of recommendations that include core elements for unified definition, implementation and reporting over a decade ago (1999, pp. 168-172). The author's drug court typology identifies clear areas for development in dozens of detailed categories under headings aimed at factors within, between and across programs (Goldkamp, 1999, pp. 173-74). Goldkamp concludes the main challenge to researcher revolves around establishing internal validity in program design such that drug court effects on local outcomes can be measured (1999, p. 175). This will stimulate funding if "questions about the integrity of the treatment" (Goldkamp, 1999, p. 176) currently prevent expansion of successful programs. But this may be impossible given the vast differences between programs and unique situational factors.

This may have turned out to be the case seeing as how Marlowe, Heck, Huddleston and Casebolt (2006) repeat nearly identical recommendations over half a decade later (pp. 6-7). Supporting this further are even more detailed but often nearly identical admonitions from the first National Drug Court Conference in 1993 (1994, pp. xi-xiii). If courts had implemented the detailed recommendations set out at that conference, some of the "large body of weak evidence" (United States Government Accountability Office, 2005, p. i) may actually become useful. On the other hand, standardization…

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