Microsoft Word - 16. Gallagher et al_16845_Impact of Drug Court on Recidivism_copyedit final


______________ 
John R. Gallagher, Ph.D., is an Assistant Professor in the Indiana University School of Social Work, South Bend campus; 
Eric Ivory, BS, is the Drug Court Coordinator; Jesse Carlton, BS, is the Adult Chief Probation Officer; and the Hon. Jane 
Woodward Miller, JD, is the Drug Court Judge, all in South Bend, IN. 

Copyright © 2014 Advances in Social Work Vol. 15 No. 2 (Fall 2014), 507-521 

The Impact of an Indiana (United States) Drug Court on Criminal 
Recidivism 

John R. Gallagher 
Eric Ivory 

Jesse Carlton 
Jane Woodward Miller 

Abstract: This study evaluated a drug court located in a metropolitan area of Indiana 
(United States), focusing specifically on identifying variables that predicted recidivism 
among drug court participants and comparing criminal recidivism patterns among drug 
court and probation participants. Drug court participants were most likely to recidivate 
if they were younger, had a violation within the first 30 days of the program, had a 
previous criminal record, and were terminated unsuccessfully from the program. 
Furthermore, drug court participants were less likely to recidivate than probationers who 
had similar offense and demographic characteristics. Implications for drug court 
practice, policy advocacy, and future research are discussed.  

Keywords: Drug court, logistic regression, criminal recidivism, substance use disorders, 
probation 

The National Survey on Drug Use and Health (NSDUH) is an annual survey that 
assesses the rate of illicit drug and alcohol use in the United States (Substance Abuse and 
Mental Health Services Administration [SAMHSA], 2013). There are several notable 
findings that came out of the 2012 survey. First, findings suggest that an estimated 24 
million Americans, or 9% of the population, used illicit drugs and 136 million 
Americans, or 52% of the population, used alcohol. Second, of all the Americans that 
used illicit drugs or alcohol, about 9%, or 22 million, met the diagnostic criteria for 
substance abuse or dependence; however, few actually received treatment for their 
substance use disorder. Specifically, of the 22 million Americans that needed substance 
abuse treatment, only 3 million received this type of intervention. Third, 34% of parolees 
and 37% of probationers met the diagnostic criteria for substance abuse or dependence, 
whereas only approximately 8% of their counterparts who were not on parole or 
probation met the same diagnostic criteria.  

As a result of the large criminal justice population that has experienced problems 
related to personal illicit drug and alcohol use and the apparent limited availability of 
substance abuse treatment, society has relied on the judicial system to offer rehabilitative 
services to arrestees to minimize their risk of reoffending. One of the ways that the 
criminal justice system has addressed the high rate of substance use disorders with their 
population has been through the development of drug courts. This article will 
conceptualize drug courts, present a review of the literature related to the effectiveness of 
drug courts, present findings that identify the most predictive factors of drug court 



ADVANCES IN SOCIAL WORK, Fall 2014, 15(2)  508 

participants’ recidivism during and after the program, discuss how drug court compares 
to traditional probation in regards to reducing criminal recidivism, and explore 
implications for drug court practice, policy advocacy, and future research. 

Indiana (United States) Drug Court 

This section provides an overview of the drug court evaluated for this study, which 
will be called the Indiana drug court. The Indiana drug court began in 1997 and the 
court’s mission is to “reduce repeated criminal behavior and reverse the destructive 
effects of drugs upon the individual abuser and health and public safety of the community 
at large” (St. Joseph County Drug Court, 2014, para. 3). The court’s philosophy is that 
“long-term sobriety involves not only quality substance abuse treatment, but also the 
prospect for an improved quality of life through better education, employability, and the 
support of a sober community” (St. Joseph County Drug Court, 2014, para. 4). In order to 
meet the program’s mission and philosophy, the drug court employs a multidisciplinary 
judicial team, commonly known as the drug court team. The drug court team consists of 
the judge, drug court coordinator, two drug court case managers, the chief of adult 
probation, a compliance officer, prosecuting attorneys, defense attorneys, a researcher, 
and local substance abuse treatment providers. The drug court team meets once a week to 
discuss the status of participants.  

The length of a drug court participant’s assignment ranges from 12 to 24 months (St. 
Joseph County Drug Court, 2014). During this timeframe, participants complete 
interventions consistent with the key components of a drug court (National Association of 
Drug Court Professionals [NADCP], 2004), such as attending substance abuse 
counseling, maintaining abstinence from illicit drug and alcohol use, submitting random 
urinalysis drug tests approximately 1 to 3 times a week, attending status hearings with the 
drug court judge approximately 1 to 4 times a month, and completing other interventions 
that the drug court team may assign due to individualized needs, such as HIV and AIDS 
education or budgeting classes. If participants are not employed at the time of admission 
into drug court, they are required to undergo vocational training while in the program. 
Similarly, if participants do not have at least a high school diploma or equivalent at 
admission, they are expected to work towards their GED during the program. In order to 
graduate from the program, participants must have completed their substance abuse 
counseling, been in the program for at least 12 months, have at least 6 months of 
consecutive negative drug tests, and pay all program fees, which include a $500.00 
program fee and the cost of drug testing. Based on a participant’s economic status, all or 
a portion of the program fee and drug testing fees can be waived by the drug court team. 
Prior to admission into drug court, participants plead guilty to the charges filed against 
them. Upon graduation, the charges are dismissed; however, if a participant is terminated 
from the program, he or she is convicted of the charge or charges and sentenced 
accordingly.  

Literature Review 

Since their inception in 1989, drug courts have seen tremendous growth. There are 
over 2,700 drug courts and 1,122 other problem-solving courts, such as mental health and 



Gallagher, Ivory, Carlton, Miller/IMPACT OF DRUG COURT ON RECIDIVISM 509

veterans courts, operating in the United States (NADCP, 2014a), and is it estimated that 
there are over 30 international drug treatment courts operating throughout 11 countries 
including Ireland, Australia, and the United Kingdom (NADCP, 2014b). In the United 
States, the proliferation of drug courts is partially explained by a growing trend where 
states, such as Texas, are beginning to mandate that certain counties have drug courts 
because policymakers view drug courts as an efficient and effective alternative to 
incarceration (Gallagher, 2012). Drug courts are perhaps the most researched criminal 
justice program, and as they continue to increase throughout the United States and 
internationally, drug court evaluations should continue to be a major part of the criminal 
justice, forensic social work, and addiction studies literature.  

Recent meta-analyses of drug court evaluations have suggested that drug courts are 
more effective than other types of criminal justice programs, such as traditional 
probation, at reducing criminal recidivism (Mitchell, Wilson, Eggers, & MacKenzie, 
2012; Shaffer, 2011). Mitchell et al. (2012) completed a meta-analytic review of 92 adult 
drug court evaluations and found that drug court participants were less likely than non-
participants to recidivate. Specifically, the average recidivism rate of drug court 
participants was 38%, compared to a recidivism rate of 50% for non-participants. It is 
also important to mention that Mitchell and colleagues found that the positive effect of 
drug court participation on recidivism lasted for three years following admission into the 
program. Shaffer (2011) calculated 82 effect sizes from drug court evaluations and found 
that drug court significantly reduced recidivism. The effect sizes suggested that drug 
court participants had a recidivism rate of 45.5%, whereas the recidivism rate for the 
comparison group would have been 54.5%. Overall, both meta-analyses provide evidence 
that the expansion of drug courts and continued funding of these programs is warranted. 

Meta-analyses offer valuable insight into the effectiveness of drug courts; however, 
the majority of studies evaluate single drug court programs. For example, an evaluation 
of the Douglas County (Omaha), Nebraska drug court found that drug court participants 
were significantly less likely to be rearrested than a comparable group of felony drug 
offenders (42% versus 61%) (Spohn, Piper, Martin, & Frenzel, 2001). Furthermore, 
Spohn and colleagues found that younger offenders, males, and those with a prior 
criminal record were more likely to be arrested during the follow-up period. In a similar 
evaluation of the Los Angeles County drug court, Fielding, Tye, Ogawa, Imam, and Long 
(2002) found that only 24% of drug court participants recidivated within the one year 
follow-up period, whereas 37% of participants from the drug diversion education 
program and 51% of felony defendants not in either program recidivated. Fielding and 
colleagues also note that graduating from drug court decreased the likelihood of 
recidivating; only 20% of graduates recidivated, compared to 33% of terminated 
participants. Brown (2011) completed a recent evaluation of a Wisconsin drug court and 
found that drug court participants were less likely to commit a new crime than a matched 
comparison group (30% versus 46%), and when a new crime was committed, drug court 
participants had a longer time to when they recidivated than the matched comparison 
group (614 days versus 463 days).  

While there is a large body of literature suggesting that drug courts are more effective 
than other types of criminal justice programs, it is important to mention that these 



ADVANCES IN SOCIAL WORK, Fall 2014, 15(2)  510 

findings are not universal (Bavon, 2001; Listwan, Sundt, Holsinger, & Latessa, 2003; 
Wolfe, Guydish, & Termondt, 2002). In an evaluation of the Tarrant County (Fort 
Worth), Texas drug court, Bavon (2001) found that about 13% of drug court participants 
and 17% of the comparison group were rearrested within one year after last contact with 
their respective programs, results that were statistically insignificant. Wolfe et al. (2002) 
also found in their evaluation of the San Mateo County, California drug court that drug 
court and non-drug court participants had equal likelihoods of recidivating. However, 
consistent with the findings from Fielding et al. (2002), Bavon (2001) and Wolfe et al. 
(2002) both found that, when comparing just drug court graduates and unsuccessfully 
terminated participants, graduates were noticeably less likely to recidivate than those who 
were terminated from the program. Wolfe and colleagues, for example, found that 53% of 
terminated participants and only 19% of graduates recidivated within the two year 
follow-up period.  

Methodologically, the present study contributes to the existing literature in several 
ways. First, the follow-up period to measure recidivism in this study is 36 months, which 
is noticeably longer than previous studies were the norm is to evaluate recidivism at a one 
(Fielding et al., 2002) or two year (Wolfe et al., 2002) follow-up period. Additionally, 
Mitchell et al. (2012) found in their meta-analysis of 92 adult drug court evaluations that, 
for the articles where the information was available (n = 79), 82% measured recidivism 
with a follow-up period of 24 months of less, further supporting the need to have a longer 
follow-up period to assess the long-term impact of drug court on recidivism.  

Second, this study utilizes a comparison group of offenders who were eligible for 
drug court but chose probation instead, and while it is common for drug court evaluations 
to use probationers as a comparison group (Krebs, Lindquist, Koetse, & Lattimore, 
2007), previous studies have typically developed comparison groups based on 
participants having a drug use history, not the fact that they met the admission criteria for 
drug court and chose to do another program. The method of developing a comparison 
group for this study, perhaps, may minimize selection bias.  

Third, this study assessed two variables that are theoretically associated with drug 
courts, yet not found in the previous research. A key component of the drug court model 
is to admit participants as soon as possible after an arrest; theoretically, this will improve 
outcomes because participants are more motivated to change following the arrest 
experience (NADCP, 2004). Therefore, this study included a variable labeled “arrest and 
admission”, defined as the total number of days from an individual’s arrest to admission 
into drug court. Next, the variable “first 30 days”, which measured whether a participant 
had a violation within the first 30 days of drug court participation, was added to the 
analysis because recent evidence has suggested that compliance within the first month of 
drug court can predict graduation outcomes (Newton-Taylor, Patra, & Gliksman, 2009); 
however, this variable has not been used to predict post-program recidivism outcomes. 

The other variables included in the analysis are consistent with those used in previous 
research that tested logistic models to predict recidivism and other drug court outcomes, 
such as graduation. Drug of choice, for example, was dichotomized as cocaine versus all 
other drugs because previous research has suggested that participants who identify 



Gallagher, Ivory, Carlton, Miller/IMPACT OF DRUG COURT ON RECIDIVISM 511

cocaine as a drug of choice are less likely to have successful drug court outcomes than 
those who identify other drugs of choice (Dannerbeck, Harris, Sundet, & Lloyd, 2006; 
Hickert, Boyle, & Tollefson, 2009).  

Methodology 

Design and Sample 

The research design used for this study was approved by the Institutional Review 
Board (IRB) at Indiana University. This study employs a nonequivalent comparison 
group, quasi-experimental design to evaluate a drug court located in Indiana; two 
research questions guided this evaluation. First, what variables most strongly predict 
recidivism among drug court participants? Second, do drug court participants have a 
lower rate of recidivism than probation participants? To identify the variables that 
predicted recidivism among drug court participants, data were collected on all drug court 
participants (n = 197) who graduated or were unsuccessfully terminated from the 
program from 2006 to 2009. To compare the recidivism patterns of drug court and 
probation participants, recidivism data were retrieved for the same sample of drug court 
participants and the electronic charts of probation participants. A list of all probationers 
(n = 995) who were arrested for a Class D Felony and completed their probation or had 
their probation revoked from 2006 to 2009 was generated. From this initial list, 194 
(19%) were included in the final sample because they had a Class D Felony that made 
them eligible for drug court but they had chosen probation instead. Based upon his 
experience as the drug court coordinator of the program evaluated in this study, one of 
the authors suggests that potential participants may be more likely to select probation 
over drug court because drug court tends to cost more than probation and drug court is 
more time consuming. Drug court, for example, typically requires drug testing 1 to 3 
times a week, whereas probationers may be drug tested only one time a month. 
Additionally, at the beginning of the program, drug court participants appear before the 
judge once a week while probationers typically only attend court once every several 
months. Criminal cases eligible for drug court include: (1) I.C.35-48-4-6 Possession of 
Cocaine or a narcotic drug, class D felony; (2) I.C. 35-48-4-7 Possession of a Controlled 
Substance, class D felony; (3) I.C. 35-48-4-8.3 Possession of Paraphernalia, class D 
felony; (4) I.C. 35-48-4-11 Possession of Marijuana, class D felony; (5) I.C. 35-48-4-13 
Maintaining a Common Nuisance, class D felony; and (6) I.C. 35-48-4-14 Acquiring 
Possession of a Controlled Substance by fraud, class D felony.  

Due to the quasi-experimental nature of this research design, participants were not 
randomly assigned to drug court or probation; therefore, selection bias may compromise 
the comparability between the groups in the study. To assess the comparability between 
the drug court and probation groups, demographic data, including gender, ethnicity, age, 
education status, and employment or student status, were collected and analyzed. This 
process of comparing the two groups is similar to that used in previous research (Brown, 
2011). The results of the comparison are noted in Table 1. There was no difference 
between the drug court and probation group in regards to gender, ethnicity, age, and 
employment or student status. The drug court group, however, was less likely to have a 



ADVANCES IN SOCIAL WORK, Fall 2014, 15(2)  512 

high school diploma or equivalent at admission than the probation group (41% versus 
54%).  

Table 1. Demographic Comparisons Between Drug Court and Probation Participants 

Variables Drug Court 

(n = 197) 

Probation 

(n = 194) 

χ² and t 
scores 

 

Gender 

 

Male = 73% (n = 143) 

Female = 27% (n = 54) 

 

Male = 72% (n = 140) 

Female = 28% (n = 54) 

 

χ² = 0.01 

 

 

Ethnicity 

 

White = 51% (n = 101) 

Black/Hispanic = 49% (n = 96) 

 

White = 51% (n = 98) 

Black/Hispanic = 49% (n = 96) 

 

χ² = 0.02 

 

 

Age 

 

Range = 18 to 57 years old 

Mean = 32 years old 

SD = 10.52 

 

Range = 18 to 69 years old 

Mean = 33 years old 

SD = 12.54 

 

t = 1.30 

 

 

Education * 

 

Have high school diploma or 
equivalent at admission = 41% 
(n = 80) 

Do not have high school 
diploma or equivalent at 
admission = 59% (n = 117) 

 

Have high school diploma or 
equivalent at admission = 54% 
(n = 105) 

Do not have high school 
diploma or equivalent at 
admission = 46% (n = 89) 

 

χ² = 7.16 

 

 

Employment 
or Student 

 

Employed or student at 
admission = 38% (n = 75) 

Not employed or student at 
admission = 62% (n = 122) 

 

Employed or student at 
admission = 42% (n = 81) 

Not employed or student at 
admission = 58% (n = 113) 

 

χ² = 0.72 

 

    
Note. *p < 0.05 

Variables and Analysis 

All data were recorded and analyzed using SPSS 21 software. There were twelve 
independent variables and one dependent variable for the logistic regression. The 
dependent variable was (0 = not rearrested, 1 = rearrested). The conceptualization and 
coding of the independent variables were as follows: gender (0 = male, 1 = female), 
ethnicity (0 = white, 1 = African American and Hispanic), age (age at time of admission 
into drug court), education (0 = have a high school diploma or equivalent at time of 
admission into drug court, 1 = do not have a high school diploma or equivalent at time of 
admission into drug court), employment or student (0 = employed or a student at time of 



Gallagher, Ivory, Carlton, Miller/IMPACT OF DRUG COURT ON RECIDIVISM 513

admission into drug court, 1 = not employed or a student at time of admission into drug 
court), drug of choice (0 = all other drugs, 1 = cocaine), positive drug tests (total number 
of positive drug tests while in drug court), first 30 days (0 = did not have a violation 
within the first 30 days of drug court, 1 = had a violation within the first 30 days of drug 
court), arrest and admission (total number of days between arrest and admission into drug 
court), mental health (0 = do not have a mental health diagnosis, 1 = have a mental health 
diagnosis), criminal history (0 = do not have a criminal history prior to the arrest that 
resulted in admission into drug court, 1 = have a criminal history prior to the arrest that 
resulted in admission into drug court), and outcome (0 = graduated drug court, 1 = 
terminated from drug court).  

Logistic regression was used to identify which variables significantly predict drug 
court participants’ recidivism. Multicollinearity was assessed by conducting correlations 
between all of the independent variables. If the phi coefficient was greater than .80, 
multicollinearity was suspected (Orme & Combs-Orme, 2009).  

Last, to compare the recidivism rates of drug court and probation participants, the 
percentage of drug court and probation participants who recidivated during and after their 
respective programs were collected through a government software program that tracks 
and records arrests, charges, and dispositions. Recidivism was defined as any new local 
(County) arrest for a felony or misdemeanor offense that resulted in charges being filed 
during drug court / probation and up to 36 months post drug court / probation discharge. 
The definition of recidivism was provided by the drug court and approved by the Indiana 
Judicial Center, which is an Indiana Supreme Court agency that certifies Indiana 
problem-solving courts. The recidivism data were collected in 2013 to assure a follow-up 
period of 36 months. 

Results 

For the drug court sample, chi-square tests of independence were used to determine if 
statistically significant differences existed in recidivism outcomes for the dichotomous 
variables of gender, ethnicity, education, employment or student, drug of choice, first 30 
days, mental health, criminal history, and outcome. The variables of gender (χ² = 0.64, p 
= .43), ethnicity (χ² = 1.10, p = .29), education (χ² = 1.20, p = .27), drug of choice (χ² = 
0.17, p = .68), and mental health (χ² = 1.88, p = .17) were not significantly related to 
recidivism. The variables of employment or student, first 30 days, criminal history, and 
outcome, however, did show statistically significant associations with recidivism.  

First, drug court participants who were neither employed nor a student at the time of 
admission were more likely to recidivate (54%) than participants who were employed or 
a student at time of admission (36%) (χ² = 6.10, p < 0.05). Second, drug court 
participants who had a violation within the first 30 days of the program were more likely 
to recidivate (65%) than participants who did not have a violation with the first 30 days 
of the program (35%) (χ² = 17.12, p < 0.05). Third, drug court participants who had a 
prior criminal history were more likely to recidivate (59%) than participants with no prior 
criminal history (30%) (χ² = 16.27, p < 0.05). Fourth, for the drug court sample (n = 197), 
108 (55%) participants graduated successfully form the program and 89 (45%) were 



ADVANCES IN SOCIAL WORK, Fall 2014, 15(2)  514 

terminated unsuccessfully. Drug court participants terminated from the program were 
more likely to recidivate (65%) than were those who graduated from the program (32%) 
(χ² = 21.01, p < 0.05).  

Multicollinearity statistics were not in the problematic area; therefore, all 
independent variables were included in the logistic regression analysis. The findings from 
the logistic regression analysis are noted in Table 2.  

Table 2. Logistic Regression of Drug Court Participants’ Recidivism (n = 197) 

Independent Variables (IVs) b S.E. Wald df Sig. Exp (b) 

 
Gender -.268 .379 .498 1 .481   .765 

Ethnicity  .043 .352 .015 1 .903 1.044 

Age -.045 .017 6.870 1     .009*   .956 

Education -.274 .357 .587 1 .444   .761 

Employment or Student .470 .356 1.748 1 .186 1.600 

Drug of Choice -.247 .370 .447 1 .504   .781 

Positive Drug Tests -.003 .022 .015 1 .904   .997 

First 30 Days 1.221 .356 11.752 1    .001* 3.391 

Arrest and Admission .004 .007 .332 1 .565 1.004 

Mental Health .444 .508 .765 1 .382 1.559 

Criminal History .938 .375 6.270 1    .012* 2.554 

Outcome .846 .379 4.986 1    .026* 2.331 

 

Note. *p < 0.05. 

Note. -2 Log Likelihood (221.77). 

Note. Nagelkerke R Square (0.30). 

Note. Hosmer and Lemeshow Test (χ² = 8.86, p = .35). 

Note. Dependent variable was (0 = not rearrested, 1 = rearrested). 

As noted in Table 2, four of the twelve independent variables were statistically 
significant. First, for each year of increase in age, participants’ chances of recidivating 
decreases by about 4%. Second, participants who had a violation within the first 30 days 
of drug court were 3.4 times more likely to recidivate than those who did not have a 
violation during this timeframe. Third, participants with a criminal history were 2.6 times 
more likely to recidivate than participants who did not have a criminal history. Fourth, 
participants terminated from drug court were 2.3 times more likely to recidivate than 
were program graduates.  

A chi-square test of independence revealed a statistically significant difference in 
recidivism patterns between the drug court and probation groups (χ² = 18.26, p < 0.05). 



Gallagher, Ivory, Carlton, Miller/IMPACT OF DRUG COURT ON RECIDIVISM 515

Of all the drug court participants (n = 197), the majority (104; 53%) did not recidivate. 
Conversely, of all the probation participants (n = 194), the majority (133; 69%) did 
recidivate.  

Discussion 

This study adds to the existing literature by identifying the variables most predictive 
of drug court participants’ recidivating. Participants were most likely to recidivate if they 
were younger, had a violation within the first 30 days of the program, had a prior criminal 
history, and were terminated unsuccessfully from the program. Consistent with previous 
research (Brown, 2011; Krebs et al., 2007), younger participants are more likely to 
recidivate than older participants. Additional demographic variables, however, were not 
significant predictors of recidivating, including gender, education status, and employment 
or student status. While previous research has suggested that being female (Brown, 2011; 
Listwan, Shaffer, & Hartman, 2009; Wolfe et al., 2002) decreases the likelihood of 
rearrest, this study found no difference in recidivism patterns by gender. Similarly, no 
difference was found in the likelihood of recidivism for participants who were or were 
not employed or a student at the time of admission into drug court, which contradicts the 
findings from Listwan and colleagues (2009) and Shaffer, Hartman, Listwan, Howell, 
and Latessa (2011).  

Consistent with previous evaluations (Krebs et al., 2007; Listwan et al., 2009; Shaffer 
et al., 2011), this study found that education status was not a significant predictor of 
recidivism. Perhaps the variables of education and employment or student status did not 
reach statistical significance because they were only assessed at admission. Specifically, 
data were only collected on whether or not a participant had a high school diploma or 
equivalent or was employed or a student at the time they were admitted to drug court. 
This method of coding does not account for participants who increased their education or 
employment status while in drug court or by the time they graduated or were terminated 
from the program. Additionally, despite the evidence that identifying cocaine as a drug of 
choice may decrease the likelihood of successful drug court outcomes (Dannerbeck et al., 
2006, Hickert et al., 2009), this study did not find cocaine to be a predictor of recidivism. 
This finding is similar to Gallagher’s (2014) recent evaluation of a Texas drug court 
where equal recidivism rates were found among drug court participants who identified 
stimulants, including cocaine, and nonstimulants as drugs of choice.  

A noticeable strength of this study is that recidivism was measured up to 36 months. 
With the longer timeframe to measure recidivism, the results remained consistent with 
those from previous studies. Specifically, drug court participants were less likely to 
recidivate than probationers who had similar characteristics (Brown, 2011; Fielding et al., 
2002; Mitchell et al., 2012; Shaffer, 2011; Spohn et al., 2001). Although drug court 
participants were less likely to recidivate than probationers, there are important 
demographic variables that were not assessed when comparing the two groups and these 
variables may have impacted the results. For example, the variable of socioeconomic 
status was not available for this study. A majority of probation participants may have 
come from lower socioeconomic backgrounds and they may have chosen not to enroll in 
drug court because it was more expensive than probation. Consequently, the higher 



ADVANCES IN SOCIAL WORK, Fall 2014, 15(2)  516 

likelihood of recidivating for probation participants may be more associated with 
socioeconomics than with the type of intervention. 

Racial disparities in drug court outcomes is a concern for many drug courts and the 
National Association of Drug Court Professionals (NADCP) has recently encouraged 
drug courts to evaluate their programs to see if racial disparities exist (Marlowe, 2013). 
Therefore, the results for the Indiana drug court are promising because white and 
minority participants (African American/Hispanic) had equal likelihoods of recidivating, 
which is consistent with findings from an evaluation of a Nebraska drug court (Spohn et 
al., 2001). Researchers have speculated that drug courts in which minority participants 
are underrepresented are more likely to experience racial disparities in graduation and 
recidivism outcomes (Gallagher, 2013a). White and minority participants were equally 
represented in the Indiana drug court (each group made-up about 50% of the program), 
and this may possibly explain why the variable of ethnicity did not reach statistical 
significance.  

Interestingly, participants with no positive drug tests in drug court and those with 
multiple positive drug tests had equal odds of recidivating. Presumably, drug court 
participants who had positive drug tests would be more likely to recidivate because they 
were continuing to engage in illegal behaviors. However, these same participants would 
have also received multiple sanctions throughout the program because of the positive 
drug tests and these sanctions, consistent with the drug court model, would have been 
therapeutic in nature, as compared to punitive interventions. Perhaps having positive drug 
tests increased participants’ attendance in substance abuse treatment and the knowledge 
and skills they learned in treatment supported their recovery beyond drug court, hence 
lowering their risk of recidivism. Similarly, the variable of days between arrest and 
admission did not reach statistical significance, suggesting that shorter times between 
arrest and program entry do not result in better outcomes. This finding fails to support a 
key component of drug court; specifically, key component three recommends that drug 
courts enroll participants as soon as possible following an arrest, as this will result in 
better outcomes related to graduation and avoiding recidivism (NADCP, 2004).  

Of all the variables assessed in this study, the strongest predictor of recidivism was 
having a violation within the first 30 days of drug court. This finding adds to the existing 
literature because the level of participants’ compliance during the first month of drug 
court has not been commonly measured in previous research. Only two known studies 
have used this variable and these studies predicted completion outcomes, not recidivism. 
Newton-Taylor et al. (2009) found in the Toronto drug treatment court that participants 
who had better compliance within the first month of the program were more likely to 
graduate. Gallagher (2013b), however, found that compliance within the first 30 days of a 
Texas drug court had no impact of graduation.  

Limitations 

The findings from this study need to be interpreted within the context of the study’s 
limitations. The most noticeable limitation is that an experimental research design was 
not used. Randomly assigning arrestees to drug court or probation would have provided 



Gallagher, Ivory, Carlton, Miller/IMPACT OF DRUG COURT ON RECIDIVISM 517

maximum control for the threats to internal validity. As with all research that does not use 
random assignment, there is the potential for selection bias. While attempts were made to 
develop a probation group that had characteristics similar to those of the drug court 
group, the matching process was limited to the data available to the researchers. For 
example, probation participants were compared to the drug court group based on having 
similar arrests and comparisons were then assessed on several demographic variables. 
Last, while the findings from this study can inform other drug courts, they should only be 
generalized beyond the research sample with caution. While all drug court operate under 
the same ten key components (NADCP, 2004), the implementation of each component 
varies from court-to-court based on a community’s needs, the type of offenders the drug 
court serves, the political climate of the community, and the availability of resources in 
the area. Evaluation of individual drug courts is recommended to assess what predicts 
recidivism for a specific jurisdiction.  

Drug Court Practice 

One of the main characteristics of drug courts that differentiates them from probation 
is that drug court defendants appear before the judge for judicial status hearings more 
frequently. The Indiana drug court, for example, requires its participants to see the judge 
weekly at the beginning of the program and no less than once a month during the later 
phases of the program. For certain populations, however, drug court programs may 
require more intensive supervision. Participants in this study who had a criminal history 
were more likely to recidivate than their counterparts without a criminal history, and 
research has suggested that participants with personality disorders that increase their 
criminogenic risk factors, and likelihood of having a criminal history, benefit most from 
frequent contact with a judge (Festinger et al., 2002; Marlowe, Festinger, Dugosh, & Lee, 
2005). In order to improve outcomes in drug courts for those with criminal histories, it is 
recommended that assessment tools be used, like the Texas Christian University (TCU) 
Criminal Thinking Scales (Knight, Garner, Simpson, Morey, & Flynn, 2006), and that 
interventions be tailored to participants based on the findings from the assessment. 
Participants, for example, with multiple criminal thinking patterns and histories of 
criminal convictions may have improved outcomes if they appear before the judge at 
least two times per week. This recommendation of increasing judicial status hearings for 
high-risk participants is also associated with the finding that participants who had a 
violation within the first 30 days of drug court were more likely to recidivate than those 
that did not have a violation during this timeframe. Participants who see the judge more 
frequently may reduce their risk of having program violations, and based on this study, 
even delaying violations until after the first 30 days seems to result in lower recidivism 
rates. 

Policy Advocacy 

Drug courts throughout the United States continue to demonstrate effectiveness at 
reducing criminal recidivism; as a result, policymakers are beginning to establish laws 
that require certain counties to have drug courts and require drug courts to become 
certified through the state. Texas, for example, requires counties with a population of 



ADVANCES IN SOCIAL WORK, Fall 2014, 15(2)  518 

more than 200,000 to have a drug court program (Texas Legislature, 2007). In Indiana, 
drug courts are required to be certified through the state, which helps promote fidelity to 
the drug court model (Indiana General Assembly, 2010). Only five states (Colorado, 
Iowa, Kansas, Massachusetts, Ohio) have no drug court legislation or state appropriations 
dedicated to drug court (Huddleston & Marlowe, 2011).  

It is recommended that policy advocacy efforts focus on establishing drug court laws 
and funding in all states. Advocates can use the findings from this study and the evidence 
from previous research to support the development and expansion of drug courts in their 
communities. In this study, drug court participants were 22% less likely to recidivate than 
probation participants (47% versus 69%) and this finding is consistent with meta-
analyses of 92 (Mitchell et al., 2012) and 82 (Shaffer, 2011) drug courts that also found 
drug court to be more effective than similar programs, such as probation, at reducing 
recidivism for offenders with substance use disorders. Policymakers from the five states 
that do not have drug court laws or state appropriations may respond favorably to 
evidence from other states demonstrating that drug courts reduce recidivism, which 
naturally saves taxpayers money. In Indiana, for example, a statewide evaluation 
indicated that having drug courts saved state taxpayers 3.5 million dollars a year, and for 
every $1.00 invested in drug courts, there can be a return of $5.37 dollars (Wiest et al., 
2007). Additionally, as drug court laws continue to be amended and implemented, it is 
important that policymakers collaborate with professionals who have expertise in drug 
court programming to assure helpful laws are being created. It is important that laws 
require drug courts to offer participants culturally competent, evidence-based treatments 
to avoid negative unintended consequences, such as racial disparities in graduation and 
recidivism outcomes (Gallagher, 2012).  

Future Research 

The majority of drug court research has used quantitative methods to predict 
graduation and recidivism outcomes, and to compare the recidivism rate of drug court to 
that of other judicial programs. Often, the quantitative studies leave many questions 
unanswered. In this study, the data demonstrated that the risk factors for recidivating 
were being younger, having a violation within the first 30 days of drug court, having a 
criminal history, and being terminated unsuccessfully from the program. While these 
findings are informative, they do not offer insight into the challenges participants 
experience with being successful in drug court. With this said, it is recommended that 
future research use qualitative methods to answer some of the unanswered questions that 
arose from this study. For example, what are some of the challenges younger participants 
face that increase their risk of recidivating? Facilitating individual interviews with 
different age groups may allow researchers to compare and contrast the experiences of 
younger and older participants, which may offer an in-depth understanding on how drug 
court can be enhanced. This compare and contrast method can also be used to explore the 
barriers participants face in the first month of the program or the factors that contribute to 
higher recidivism rates for those with criminal histories. Terminated participants are a 
little more than 2 times more likely to recidivate than graduates; through the use of 



Gallagher, Ivory, Carlton, Miller/IMPACT OF DRUG COURT ON RECIDIVISM 519

qualitative methods, researchers may be able to capture the lived experiences of 
participants which may inform practice and improve graduation outcomes.  

Conclusion 

Findings from this study, coupled with the plethora of evidence from previous 
research, suggest that drug court is more effective than similar types of criminal justice 
programs at reducing criminal recidivism rates for offenders with substance use 
disorders. Participants from the Indiana drug court recidivated at a rate of 47%, whereas 
the recidivism rate for a comparable group of probationers was 69%. Additionally, drug 
court participants were most likely to recidivate if they were younger, had a violation 
within the first 30 days of the program, had a criminal history, and were terminated from 
the program. In order to improve outcomes for drug court participants, especially those 
more likely to recidivate, the use of assessment tools, such as the Texas Christian 
University (TCU) Criminal Thinking Scales, may help drug courts tailor interventions to 
participants’ needs. Furthermore, advocating for effective drug court laws throughout the 
United States is recommended to support the expansion of these valuable programs. Last, 
future research focused on the use of qualitative methods may help develop an in-depth 
understanding of drug court from participants’ lived experiences, such as focusing on the 
challenges participants face during the first 30 days of the program or the factors that 
may contribute to younger participants being more likely to recidivate.  

References 

Bavon, A. (2001). The effect of the Tarrant county drug court program on recidivism. 
Evaluation and Program Planning, 24, 13-22.  

Brown, R. (2011). Drug court effectiveness: A matched cohort study in the Dane County 
drug treatment court. Journal of Offender Rehabilitation, 50, 191-201.  

Dannerbeck, A., Harris, G., Sundet, P., & Lloyd, K. (2006). Understanding and 
responding to racial differences in drug court outcomes. Journal of Ethnicity in 
Substance Abuse, 5(2), 1-22. 

Festinger, D. S., Marlowe, D. B., Lee, P. A., Kirby, K. C., Bovasso, G., & McLellan, A. 
T. (2002). Status hearings in drug court: When more is less and less is more. Drug 
and Alcohol Dependence, 68, 151-157.  

Fielding, J. E., Tye, G., Ogawa, P. L., Imam, I. J., & Long, A. M. (2002). Los Angeles 
County drug court programs: Initial results. Journal of Substance Abuse Treatment, 
23, 217-224. 

Gallagher, J. R. (2012). A policy analysis framework for drug courts. Southwest Journal 
of Criminal Justice, 8, 2-16. 

Gallagher, J. R. (2013a). African American participants’ views on racial disparities in 
drug court outcomes. Journal of Social Work Practice in the Addictions, 13, 143-162.  

Gallagher, J. R. (2013b). Drug court graduation rates: Implications for policy advocacy 
and future research. Alcoholism Treatment Quarterly, 31(2), 241-253.  



ADVANCES IN SOCIAL WORK, Fall 2014, 15(2)  520 

Gallagher, J. R. (2014). Predicting criminal recidivism following drug court: Implications 
for drug court practice and policy advocacy. Journal of Addictions & Offender 
Counseling, 35, 15-29.  

Hickert, A. O., Boyle, S. W., & Tollefson, D. R. (2009). Factors that predict drug court 
completion and drop out: Findings from an evaluation of Salt Lake County’s adult 
felony drug court. Journal of Social Service Research, 35(2), 149-162. 

Huddleston, W., & Marlowe, D. B. (2011). Painting the current picture: A national 
report on drug courts and other problem-solving court programs in the United 
States. Alexandria, VA: National Drug Court Institute [NDCI].  

Indiana General Assembly. (2010). House Enrolled Act No. 1271. Retrieved from 
http://www.in.gov/legislative/bills/2010/HE/HE1271.1.html 

Knight, K., Garner, B. R., Simpson, D. D., Morey, J. T., & Flynn, P. M. (2006). An 
assessment for criminal thinking. Crime & Delinquency, 52, 159-177.  

Krebs, C. P., Lindquist, C. H., Koetse, W., & Lattimore, P. K. (2007). Assessing the 
long-term impact of drug court participation on recidivism with generalized 
estimating equations. Drug and Alcohol Dependence, 91, 57-68.  

Listwan, S. J., Shaffer, D. K., & Hartman, J. L. (2009). Combating methamphetamine use 
in the community: The efficacy of the drug court model. Crime & Delinquency, 55, 
627-644. 

Listwan, S. J., Sundt, J. L., Holsinger, A. M., & Latessa, E. J. (2003). The effect of drug 
court programming on recidivism: The Cincinnati experience. Crime & Delinquency, 
49, 389-411. 

Marlowe, D. B., Festinger, D. S., Dugosh, K. L., & Lee, A. P. (2005). Are judicial status 
hearings a “key component” of drug court? Six and twelve months outcomes. Drug 
and Alcohol Dependence, 79, 145-155.  

Marlowe, D. B. (2013).Achieving racial and ethnic fairness in drug courts. Court Review, 
49, 40-47. 

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, 60-71.  

National Association of Drug Court Professionals [NADCP]. (2004). Defining drug 
courts: The key components. Retrieved from 
https://www.ncjrs.gov/pdffiles1/bja/205621.pdf 

NADCP. (2014a). About National Association of Drug Court Professionals (NADCP). 
Retrieved from http://www.nadcp.org/learn/about-nadcp 

NADCP. (2014b). About International Association of Drug Treatment Courts (IADTC). 
Retrieved from http://www.nadcp.org/about-us?q=about-us 



Gallagher, Ivory, Carlton, Miller/IMPACT OF DRUG COURT ON RECIDIVISM 521

Newton-Taylor, B., Patra, J., & Gliksman, L. (2009). Toronto drug treatment court: 
Participant intake characteristics as predictors of “successful” program completion. 
Journal of Drug Issues, 39, 965-987. 

Orme, J. G., & Combs-Orme, T. (2009). Multiple regression with discrete dependent 
variables. New York: Oxford University Press.   

Shaffer, D. K. (2011). Looking inside the black box of drug courts: A meta-analytic 
review. Justice Quarterly, 28, 493-521. 

Shaffer, D. K., Hartman, J. L., Listwan, S. J., Howell, T., & Latessa, E. J. (2011). 
Outcomes among drug court participants: Does drug of choice matter? International 
Journal of Offender Therapy and Comparative Criminology, 55, 155-174.  

Spohn, C., Piper, R. K., Martin, T. J., & Frenzel, E. D. (2001). Drug courts and 
recidivism: The results of an evaluation using two comparison groups and multiple 
indicators of recidivism. Journal of Drug Issues, 31, 149-176.  

St. Joseph County Drug Court. (2014). St. Joseph County drug court program. 
[Brochure]. South Bend, Indiana: Author.  

Substance Abuse and Mental Health Services Administration. (2013). Results from the 
2012 National Survey on Drug Use and Health: Summary of national findings. 
Retrieved from 
http://www.samhsa.gov/data/NSDUH/2012SummNatFindDetTables/NationalFinding
s/NSDUHresults2012.htm#ch7.1.7 

Texas Legislature. (2007). H.B. No. 530. Retrieved from 
http://www.capitol.state.tx.us/tlodocs/80R/billtext/html/HB00530I.htm 

Wiest, K. L., Carey, S. M., Martin, S. J., Waller, M. S., Cox, A. A., & Linhares, R. 
(2007). Indiana drug courts: A summary of evaluation findings in five adult 
programs. Portland, OR: NPC Research.  

Wolfe, E., Guydish, J., & Termondt, J. (2002). A drug court outcome evaluation 
comparing arrests in a two year follow-up period. Journal of Drug Issues, 32, 1155-
1171.  

Author note 
Address correspondence to: John R. Gallagher, Ph.D., Assistant Professor, School of 
Social Work, Indiana University-South Bend, 1700 Mishawaka Avenue, Northside Hall 
420, P.O. Box 7111, South Bend, IN 46634-7111. Email: johngall@iupui.edu