Volume 3, Issue 1 • Fall 2013

Table of Contents

Forword

The Impact of Juvenile Mental Health Court on Recidivism Among Youth

Gender-Specific Mental Health Outcomes of a Community-Based Delinquency Intervention

Predicting Recidivism Among Juvenile Delinquents: Comparison of Risk Factors for Male and Female Offenders

Building Connections Between Officers and Baltimore City Youth: Key Components of a Police–Youth Teambuilding Program

Internet-Based Mindfulness Meditation and Self-regulation: A Randomized Trial with Juvenile Justice Involved Youth

Assessing Youth Early in the Juvenile Justice System

A Jury of Your Peers: Recidivism Among Teen Court Participants

Commentary: Place-Based Delinquency Prevention: Issues and Recommendations

A Jury of Your Peers: Recidivism Among Teen Court Participants

Brenda Vose,
University of North Florida, Jacksonville, Florida

Kelly Vannan,
University of Central Florida, Orlando, Florida

Brenda Vose, Department of Criminology and Criminal Justice, University of North Florida; Kelly Vannan, Department of Criminal Justice, University of Central Florida.

Correspondence concerning this article should be addressed to: Brenda Vose, University of North Florida, Department of Criminology and Criminal Justice, 1 UNF Drive, Jacksonville, Florida 32224; E-mail: brenda.vose@unf.edu

Keywords: teen court, peer court, juvenile recidivism, juvenile delinquency, effective interventions

Abstract

Teen court programs have gained widespread popularity throughout the United States over the past 30 years. The rapid growth of teen courts has outpaced the rate of research, resulting in a knowledge gap concerning best practices and overall effectiveness of teen court programs. This study contributes to the existing literature by identifying variables associated with recidivism among 478 teen court participants in Duval County, Florida, between 2009 and 2011. In this study, 20.1% of program participants recidivated within 1 year of program completion, and males were four times more likely to recidivate than females. Although males recidivated at a significantly greater rate than females, there was no significant difference in the number of days it took males and females to recidivate. The number of sanctions imposed on youth in our study was not associated with recidivism. Limitations and policy implications of this study are explored.

Introduction

In 2009, approximately 1.9 million people under the age of 18 were arrested in the United States. The number of arrests of juveniles in 2009 was 17% lower than the number of arrests in 2000. In 2009, the number of juvenile arrests for violent index crimes was the lowest since 1980 (Puzzanchera & Adams, 2011). In spite of an overburdened juvenile justice system, juvenile arrest rates continue to decline. One explanation could be the increasingly popular use of diversion programs such as teen courts.

Teen courts are typically overseen by an adult judge but run by youth. The attorneys, jurors, and bailiffs are youth who work under the supervision of adult volunteer attorneys. Defendants are usually first-time, low-risk offenders referred to teen court by police, prosecutors, or school authorities (Garrison, 2001). Teen courts have experienced exponential growth since the 1990s. In 1991, there were 50 teen courts in operation in the United States; by 2006, there were 1,100 teen courts in operation. In 2000, traditional juvenile justice courts handled more than 1.6 million cases. During that time, teen courts handled 85,000 cases, alleviating traditional juvenile courts of 12% of their cases (Norris, Twill, & Kim, 2011).

Aside from lightening the burden of traditional courts, teen courts have other goals as well. Teen courts strive to teach juveniles accountability. Theoretical bases stem from labeling theories, social control, restorative justice, and, to some degree, reintegrative shaming. When agreeing to be diverted to teen court and complying with the imposed sanctions, usually given by a jury of youth peers, a juvenile offender can avoid establishing a criminal record.

Sanctions commonly imposed by teen courts are community service, apology letters, essays and book reports, teen court jury duty, educational workshops, restitution, jail tours, and curfews. The most widely used sanctions are community service, used by 99% of teen courts; apology letters, used by 86% of teen courts; and essays, used by 59% of teen courts (Dick, Geertsen, & Jones, 2003).

Teen courts vary as to how they operate. The most common model is the adult model, in which the roles of attorneys, jurors, and bailiffs are filled by youth, but the judge is an adult volunteer. The youth judge model is similar to the adult model, but the judge is a youth. The peer jury model is a more informal one in which there is no judge and no attorneys. Instead, youth jurors question the defendant and then impose sanctions. Finally, the tribunal model does not use a jury, but instead utilizes youth attorneys who argue before youth judges. The judges then impose sanctions (Garrison, 2001).

The Duval County Teen Court Program (DCTCP) utilizes the adult model. Teen participants are referred to DCTCP by the state attorney’s office, school officials and school resource officers, and the Jacksonville Sheriff’s Office (JSO). JSO officers may use their discretion to issue a civil citation to a juvenile rather than make a formal arrest. Unlike arrests, civil citations do not become part of a juvenile’s permanent record. Civil citations, and subsequent referral to DCTCP, are issued only to first-time offenders.

DCTCP utilizes many of the most common types of sanctions, among which are three educational programs: Focus on Females (FOF), Consequences of Crime, and Next Generation. Focus on Females is a class for female juveniles and their parents. Issues that are often gateways to delinquent or socially deviant behavior, such as drug use, fighting, improper use of social media, and even negative body image and sexual concerns, are discussed. Representatives from Planned Parenthood and inmates from the Duval County Jail are present in these classes to add information, insight, and authenticity to the discussions (Plotkin, n.d.). Consequences of Crime is the male-oriented counterpart of FOF, covering issues specific to boys and young men. Next Generation, a class for both genders, teaches parenting skills.

Although teen courts have become widely used diversion programs across the United States, few studies have been conducted on the effectiveness of specific sanctions and the overall effectiveness of these programs on recidivism. This study attempts to add to the body of existing literature on teen courts by examining variables associated with recidivism among teen court participants.

Literature Review

The studies reviewed in this paper attempt to shed light on the degree to which teen courts are effective tools of intervention with juveniles. The studies are organized into four sections: (a) the impact of sentence completion on recidivism; (b) how the recidivism rates of teen court participants compare to the recidivism rates of teens who participated in traditional juvenile courts or other alternative intervention programs; (c) the relationship of sanction type to recidivism; and (d) the relationship of extralegal factors (e.g., gender, age, race, socio-economic status, prior offenses) to recidivism.

The Impact of Sentence Completion on Recidivism

Most of the literature about the impact of sentence completion on recidivism has defined recidivism as re-arrest after sentence completion. The period in which re-arrests have been monitored for the purpose of operationalizing recidivism have varied from 5 months to 1 year after participants left the program, either with or without successful sentence completion (Garrison, 2001; Logalbo & Callahan, 2001). Two studies have monitored re-arrests from the time participants left their programs until they turned 18 years old (Forgays & DeMilio, 2005; Dick et al., 2003). One study used self-reports from teen court participants who completed the program. Specifically, researchers asked program participants if they had “broken the law since [they] were sent to teen court” (Dick et al., 2003, p. 39).

In every case, teens who completed their sentences recidivated at a lower rate than teens who did not complete their sentences (see Table 1). Minor, Wells, Soderstrom, Bingham, & Williamson (1999) reported a 36% (n = 24) recidivism rate among noncompleters compared to a 30% (n = 48) recidivism rate among completers (N = 226). Forgays and DeMilio (2005) found the recidivism rate among noncompleters was 100% (n = 2), compared to a rate of 13% (n = 3) among completers. However, a limitation of the study by Forgays and DeMilio (2005) was its small sample size (N = 26). Dick et al. (2003) reported a 49% recidivism rate among completers (n = 59). This is likely due to recidivism being measured by self-reports of any delinquent behavior rather than by re-arrests (Dick et al., 2003).

Table 1. Summary Findings from Previous Teen Court Research

Author Year N Includes Only First-Time Offenders Sentence Completion Measure of Recidivism (Mos. after Completion) Rate of Recidivism Among Completers Rate of Recidivism Among Non-Completers Overall Rate of Recidivism

Dick et al.

2003

120

100% (n=120)

Self-Report

49% (n=59)

N/A

49% (n=59)

Forgays & DeMilio

2005

26

No

92% (n=24)

Re-arrest to 18y/o

13% (n=3)

100% (n=2)

19% (n=5)

Garrison

2001

71

Yes

63% (n=45)

Re-arrest 12mos.

6% (n=7)

58% (n=15)

31% (n=22)

Harrison et al.

2000

478

63% (n=300)

Re-arrest to 18y/o

26% (n=79)

32% (n=40)

25% (n=119)

Irons & Jones

2001

574

83% (n=475)

--

--

Logalbo & Callahan

2001

111

No

100% (n=111)

Re-arrest 5mos.

13% (n=14)

N/A

13% (n=14)

Minor et al.

1999

226

No

71% (n=160)

Re-arrest 12mos.

30% (n=48)

36% (n=24)

32% (n=72)

Norris et al.

2011

635

Yes

95% (n=603)

Re-arrest 1999-2006

20% (n=127)

Rasmussen

2004

648

No

92% (n=572)

Re-arrest 12mos.

12% (n=78)

Rasmussen & Diener

2005

38

62% (n=23)

Any negative contact w/police of at least the severity that would be referred to teen court

22% (n=8)

Seyfrit et al.

1987

52

No

100% (n=52) 

Re-offense No specified time

10% (n=5)

N/A

10% (n=5)

Stickle et al.

2008

56

No

85% (n=48)

Re-offenses 18mos. from referral date

32% (n=18)

32% (n=18)

Rasmussen (2004), on the other hand, did not find that sentence completion had any significant association with recidivism. Studying 648 participants of a teen court in a rural part of Illinois, Rasmussen (2004) found that race, type of referral agent (e.g., police, state’s attorney, municipal attorney), and length of time between referral and sentencing were variables associated with recidivism, whereas prior offense, severity of offense, and sentence completion were not. One explanation for the lack of significance between sentence completion and recidivism could be that this particular teen court allowed one, two, and even three time extensions for sentence completion (Rasmussen, 2004).

Recidivism Rates of Teen Courts Versus Traditional Juvenile Courts

One of the most prevalent criticisms of existing literature on teen courts is the lack of studies that have used comparison groups or nonequivalent comparison groups (Forgays & DeMilio, 2005). Most studies included in this review did not include a comparison group (Garrison, 2001; Harrison, Maupin, & Mays, 2001; Minor et al., 1999; Rasmussen, 2004). Two studies included comparison groups that were much smaller in number than the treatment groups: Logalbo and Callahan (2001) used a treatment group of 111 teen court participants and a comparison group of 65 self-selected local junior high school and high school students; Norris et al. (2011) used a treatment group of 635 teen court participants and a comparison group of randomly selected participants in preteen court diversion programs.

However, two studies did use appropriate comparison groups. Seyfrit, Reichel, & Stutts (1987) conducted a study using 52 teen court participants from a county in Georgia and a comparison group of 50 participants in a traditional juvenile court from a similar county, also in Georgia. The major difference was the racial composition of each population. The percentage of White participants in the experimental group was 92%; the percentage in the comparison group, 68%. Other characteristics of the groups were similar. Seyfrit et al. (1987) found no significant difference in the recidivism rates of the two groups, although the rates are distinct. The recidivism rate of teen court participants was 3% and that of the traditional court participants was 10%.

Stickle, Connell, Wilson, & Gottfredson (2008) utilized a sample group of teen court participants (n = 56) and a comparison group of traditional juvenile court participants (n = 51). This study is unique in design because the researchers used randomized assignment when placing offenders into each group. The groups were demographically matched. Recidivism was used as an outcome measure and was defined as any new offense within 18 months of referral to either court system. Repeat offenders were allowed into the study. Teen court participants recidivated at a higher rate (32%) than did the traditional court participants (26%).

Logalbo and Callahan (2001) could not address recidivism rates between the treatment and comparison groups because members of the comparison group had no history of delinquency. Differences in attitudes toward authority and knowledge of law-related matters were measured and analyzed between the two groups (Logalbo & Callahan, 2001). Norris et al. (2011) found that the sentence completion rate for teen court participants was 95% (n = 603), with an overall recidivism rate of 20% (n = 127). The comparison group experienced a sentence completion rate of 86% (n = 160) with an overall recidivism rate of 18% (n = 33).

Forgays and DeMilio (2005) used a comparison group with an equal number of samples as the treatment group, but the sample size of each was very small (N = 26). The treatment group consisted of teen court participants; the comparison group consisted of randomly selected offenders who were processed through traditional juvenile court. Results show that among the 92% (n = 24) of teen court participants who successfully completed their sentences, three (13%) reoffended. Only 50% (n = 13) of the comparison group completed their sentences and, of those who completed their sentences, 38% (n = 5) reoffended (Forgays & DeMilio, 2005).

The studies utilizing comparison groups have yielded inconsistent results regarding recidivism rates of teen court participants and those of traditional juvenile court participants. Norris et al. (2011) found little difference between sentence completion and recidivism rates between the treatment and comparison groups, whereas Forgays & DeMilio (2005) found striking disparities in both completion and recidivism rates between groups.

The Relationship of Sanction Type to Recidivism

Several sanctions are common to almost any teen court. They are restitution, community service, teen court jury duty, apology letters, essays, curfews, and correctional facility tours (Greene & Weber, 2008; Williamson, Chalk, & Knepper, 1993; Zehner, 1997). The most popular sanctions are community service, used by 99% of teen courts; apology letters, used by 86% of teen courts; and essays, used by 59% of teen courts (Dick et al., 2003). Although several previous studies have examined whether teen court participants recidivate at lower rates than juveniles who are processed through traditional courts, few studies have explored which sanctions, or combination of sanctions, are associated with lower recidivism rates. Those studies that have explored such questions focus almost entirely on community service, perhaps due to the fact that community service is the most popular sanction.

Rasmussen (2004) found that teen court participants who were sentenced to community service had higher recidivism rates than participants not sentenced to community service. Dick et al. (2003) concluded participants who were sentenced to community service and/or writing assignments—either apology letters or essays—were significantly more likely to recidivate than participants who were not assigned these sanctions. Minor et al. (1999) found that participants sentenced to community service were less likely to complete their sentences. Although community service was not significantly related to recidivism, sentence completion has been found to be associated with lower recidivism rates (Minor et al., 1999; Forgays & DeMilio, 2005). Contrary to literature showing a positive relationship between community service and recidivism, two studies concluded that individuals assigned community service were less likely to reoffend than were individuals not assigned community service (Garrison, 2001; Harrison et al., 2001). Furthermore, Norris et al. (2011) found that the number of sanctions imposed on an individual was positively related to the individual’s likelihood of reoffending. Minor et al. (1999) found that youth who had a curfew imposed on them were 2.7 times more likely to reoffend than youth who did not have a curfew. One possible explanation is that curfews are not as directly related to an individual’s offense as are writing essays, apology letters, restitution, or community service.

Lipsey (1999) conducted a meta-analysis of studies on the effectiveness of rehabilitation with juveniles who committed serious offenses. The sample included 117 studies on the effects of intervention with noninstitutionalized juvenile offenders. Relevant selection criteria for sample studies were the following: juveniles had to have been ages 12 to 21 and received some sort of intervention; a comparison group, or at the very least a pretest-posttest method, had to have been used; juvenile participants had to have a record of serious offenses or a history of violent behavior; and referrals had to have come from a juvenile justice source. Sample groups of selected studies were made up mostly of males, with an average age range of 13 to 16 years, whose participation in the programs was mandatory. Programs were typically 10 to 30 weeks long and provided 10 or fewer contact hours per week.

The types of sanctions that Lipsey (1999) found to be associated with reduced recidivism were individual counseling, interpersonal skills, and behavioral programs. Sanctions that had the least effect were wilderness or challenge programs, early release from probation or parole, deterrence programs, and vocational programs. In fact, deterrence programs (mainly “shock incarceration”) and vocational programs (mainly vocational training, career counseling, interview skills, and job search) were found to have negative effect sizes (-0.06 and -0.18 respectively).

The Relationship of Extralegal Factors to Recidivism

Unfortunately, few studies have addressed extralegal factors in regard to teen court and recidivism. Studies that did address extralegal factors found that males recidivate at a higher rate than do females (Harrison et al., 2001; Norris et al., 2011). Age and race have also been shown to be related to recidivism; younger offenders recidivate at a higher rate than older ones, and Blacks are re-arrested at a higher rate than Whites (Rasmussen, 2004). Of interest is the finding by Harrison et al. (2001) that household income and those with whom a juvenile lived had no significant relation to recidivism.

Worth mentioning is the process by which jurors deliberate sentences. Greene and Weber (2008) and Beck (1997) found that jurors remain largely consistent in the structure of sanctions imposed on defendants regardless of differences between individual defendants. Variations of evidence presented or defendants’ statements and performance during the trial were not frequently reflected in variations in sentencing. Jurors put even less emphasis on extralegal factors.

Forgays, DeMilio, & Schuster (2004) concluded that jurors considered factors and sentences likely to be tailored by case. The sample group of jurors used in this study, however, was somewhat atypical in that they were high school students recruited by teachers. Of the 110 participants, only 6% (n = 7) had ever been adjudicated in a teen court. The participants of other, similar studies were teen court defendants who were serving on peer juries as part of their sentences.

In summary, existing literature on teen courts is scant. The studies that have been conducted vary widely in their methodology and type. While some examined sentence completion, others looked at the nature and severity of sanctions. Overall, the findings from past studies have been inconsistent; thus, more research is needed to better understand the relationship between participation in teen court and recidivism. This study focused on a teen court in Duval County, Florida, in the southeast region of the country. Using secondary data, variables associated with recidivism among teen court participants are analyzed and policy implications explored.

Method

Participants

The sample includes 478 juveniles who participated in the DCTCP between 2009 and 2011. More than one-half (69%) of the participants were males ranging in age from 11 to 18 years (M = 14.97, SD = 1.63). The majority of participants were Black (54%); the remaining participants were White (38.9%), Hispanic (4.4%), Asian (1%), or Other (1.7%). The offense for which the majority of participants were convicted was possession of less than 20 grams of marijuana (24.9%), followed by assault/battery (16.5%), affray/criminal mischief (13.6%), and petit theft (13.8%). All participants resided in Duval County, Florida for the duration of their DCTCP participation and study follow-up period.

The sanction imposed most often on participants was community service (97.9%). The number of hours assigned ranged from 0 to 55 (M = 16.38, SD = 9.97). Counseling was assigned in 24.3% of cases and drug tests were administered in 15.9% of cases. The sanction imposed least often was tutoring (2.5%).

Measures

Independent variables of interest included gender, age, race, school grade level, the type of offense for which the juvenile was referred to DCTCP, the type of sanction imposed (and, when applicable, length of the sentence, such as the number of community service hours assigned), and time at risk.

The study included two dependent variables. Recidivism, defined as any arrest for a new charge within 1 year after the participant’s release date, served as the primary dependent variable. The second dependent variable was time to failure. Time to failure is defined as the number of days between the offender being released from the program until the day the offender is rearrested. In this study, time to failure was used as the dependent variable when testing for a significant difference in time to failure across categories of gender.

Table 2. Demographic Characteristics of the Participants

Characteristic N %

Gender

 

 

Male

330

69.0

Female

148

31.0

Age at Intake

 

 

11

10

2.1

12

28

5.9

13

62

13.0

14

70

14.6

15

107

22.4

16

109

22.8

17

79

16.5

18

13

2.7

Mean (SD)

14.97 (1.63)

 

Race

 

 

Black

258

54.0

White

186

38.9

Hispanic

21

4.4

Asian

5

1.0

Other

8

1.7

Offense Type

 

 

Possession <20g Marijuana

119

24.9

Assault/Battery

79

16.5

Affray/Criminal Mischief

65

13.6

Petit Theft

66

13.8

Use of Drug/Alcohol/Tobacco

50

10.5

Multiple Class II Offenses

34

7.1

Truancy

12

2.5

Trespassing

9

1.9

Vandalism

2

0.4

Other

42

8.8

Sanctions

 

 

Community Service

468

97.9

Consequences of Crime

428

89.5

Jury Duty

413

86.4

Essay

264

55.2

Apology

223

46.7

Book Report

185

38.7

Counseling

116

24.3

Drug Test

76

15.9

Curfew

66

13.8

Focus on Females

46

9.6

Next Generation

21

4.4

Tutoring

12

2.5

Procedure

Data for this project were obtained from the DCTCP, Florida Department of Juvenile Justice, and the state attorney’s office. DCTCP files were examined during the fall of 2012, resulting in coded records for 478 teen court cases from January 2009 to January 2011. All participants successfully completed the teen court program, meaning they complied with all imposed sanctions, appeared at all court dates, and had not been re-arrested on new charges. Rejected cases were not included because the reasons for rejection were not available; thus, we were unable to determine whether rejected youth recidivated, did not have parental consent to participate in DCTCP, failed to comply with imposed sanctions and/or program rules, or were not accepted into the program for other reasons.

We obtained recidivism data for youth who had not yet turned 18 during the 1-year follow-up from the Florida Department of Juvenile Justice. We obtained recidivism data for those who turned 18 during the 1-year follow-up from the state attorney’s office because any new charges for these participants would have been processed in adult courts.

Upon satisfactory completion of a defendant’s sanctions, a DCTCP caseworker signed a certificate of completion. The certificate was dated, and that date became the defendant’s official release date from the program. The time at risk was calculated on an individual basis using the defendant’s official release date from the program as the beginning of the 1-year follow-up.

Results

Of the 478 program participants, 96 (20.1%) reoffended at least once during the year following the completion of DCTCP. Chi-square tests were conducted for demographic variables and offense type, in which recidivism was the identified dependent variable. The results suggest that gender is the only categorical variable associated with recidivism (χ2 = 5.766, df = 1, p = .016). Males were nearly four times as likely to recidivate than females (n = 76 vs. n = 20).

The number of sanctions per teen court participant ranged from 0 – 10 (M = 5.00, SD = 1.735). The number of sanctions assigned was not associated with likelihood of recidivism. Figure 1 shows the allocation of sanctions by gender. Jury duty, community service, and consequences of crime were the sanctions most commonly assigned to males and females. Despite the disparity in recidivism rates by gender, a closer look at the number of sanctions assigned by gender indicate that males (M = 5.43, SD = 1.697) received the same number of sanctions as females (M = 5.30, SD = 1.819).

Figure 1. Use of Available Teen Court Sanctions by Gender

Figure 1. Use of Available Teen Court Sanctions by Gender

Table 3 depicts the results for logistic regression analysis of sanction type and recidivism. Participation in Focus on Females and Next Generation were the only significant predictors of recidivism. The negative B coefficient for Focus on Females indicates participants were less likely to recidivate than subjects not assigned to Focus on Females. The positive B coefficient for Next Generation suggests participants were more likely to recidivate than those who did not participate in Next Generation.

Table 3. Logistic Regression for Sanctions and Recidivism

Predictor B S.E. Wald p Exp(B)

Tutoring

-.527

.83

.402

.526

.591

Apology

.061

.246

.061

.804

1.063

Drug Test

.183

.322

.325

.569

1.201

Book Report

-.059

.252

.055

.814

.943

Essay

.092

.258

.128

.72

1.097

Jail Tour

-.007

.252

.001

.979

.993

Focus on Females

-1.356

.621

4.778

.029*

.258

Consequences of Crime

-.941

.549

2.93

.086

.39

Curfew

.322

.325

.983

.321

1.38

Counseling

.338

.274

1.52

.218

1.402

Next Generation

1.042

.495

4.421

.036*

2.834

Community Service

.244

.839

.085

.771

1.277

Jury Duty

.51

.519

.963

.326

1.665

Constant

-1.405

.841

2.792

.095

.245

Model Chi-Square (df)

18.115 (13)

 

 

 

 

-2 Log Likelihood

460.478

 

 

 

 

Cox and Snell R2

.037

 

 

 

 

Nagelkerke R2

.059

 

 

 

 


*p < .05

A survival analysis and t-test for independent samples were conducted to determine whether there was a significant difference in the mean number of days it would take for males and females to recidivate. The results from the survival analysis are outlined in Table 4 and suggest patterns of reoffending among males and females. Just over 22% (22.4%) of all males in the sample (n = 76) reoffended within 60 days of release compared to 25% of the females (n = 20). Whereas 21% of male recidivists reoffended 120 to 180 days post-release, 30% of females reoffended 300 to 360 days post-release. Results of the t-test reveal no significant difference between males (M = 177, SD = 108.96) and females (M = 182.65, SD = 118.28), t(96) = 2.03, p = .840 with respect to time to fail.

Table 4. Life Table for Sample and by Gender

  Full Sample Males Females

Exposure Months

Risk Set N Failed N Proportion Recidivated Risk Set N Failed N Proportion Recidivated Risk Set N Failed N Proportion Recidivated

1

96

10

.10

76

8

.11

20

2

.10

2

86

12

.14

68

9

.13

18

3

.17

3

74

4

.05

59

3

.05

15

1

.07

4

70

5

.07

56

4

.07

14

1

.07

5

65

13

.20

52

10

.19

13

3

.23

6

52

7

.13

42

6

.14

10

1

.10

7

45

2

.04

36

1

.03

9

1

.11

8

43

9

.21

35

8

.23

8

1

.13

9

34

7

.21

27

6

.23

7

1

.14

10

27

8

.30

21

8

.38

6

0

.00

11

19

10

.53

13

7

.54

6

3

.50

12

9

9

1.00

6

6

1.00

3

3

1.00

Discussion

There are three important findings from this study. First, gender is a significant predictor of recidivism among teen court participants, with males being four times more likely to recidivate than females. This finding is consistent with previous teen court research (Harrison et al., 2001; Norris et al., 2011). Interestingly, despite the discrepancy in rate of recidivism, there is no significant difference in the time to fail between genders. This implies that aftercare services need not be based on gender, but should focus on the risks/needs of the individual (Listwan, Cullen, & Latessa, 2006). Second, the number of sanctions imposed is not associated with the likelihood of recidivism. This finding may indicate that juveniles are being assigned sanctions based on availability rather than on the individual’s risk/needs (Vincent, Paiva-Salisbury, Cook, Guy, & Perrault, 2012). Finally, few of the sanctions imposed are associated with recidivism. As such, the available sanctions should be reviewed and the list of sanctions imposed should include only treatments that have been empirically demonstrated to reduce the likelihood of recidivism (see Lipsey, 1999).

Limitations

Perhaps the most significant limitation of this study is the lack of a control group with which the participants of DCTCP can be compared. Without such a group, conclusions cannot be made regarding the effectiveness of teen court compared to other juvenile justice programs. The proposed benefits of teen courts, such as the reduction of labeling and the social control of being adjudicated by teen peers, cannot be as meaningfully examined without a control group whose participants were not exposed to programs that offered similar considerations.

Attempts to establish a control group encountered several obstacles. The first was an overarching concern with confidentiality due to the fact that the study involved juveniles. Agencies dealing with juveniles appeared reluctant to grant access to data. The second obstacle was a scarcity of suitable comparison groups. The county in which the study took place is demographically unique compared to others in the region. Duval County is made up almost entirely by one city, Jacksonville. Jacksonville has a population of approximately 880,000 and covers a geographical area of 762 square miles. The city with the next largest population is Miami, home to approximately 414,000 people, less than half the number of residents in Jacksonville. Miami covers only 36 square miles, presenting a more ecologically dense environment. The cities differ by racial composition as well. Jacksonville, in brief, has a population that is 55.1% White, 30.7% Black, 7.7% Hispanic, and 6.5% other races. Miami’s population is largely Hispanic. Approximately 70% of its residents are Hispanic and 19.2% are Black. The racial compositions of Jacksonville and Miami are not comparable (United States Department of Commerce, 2013).

The one agency in Duval County from which suitable comparisons could have been drawn was faced with the third obstacle: the lack of electronically stored data. The majority of data collected for this study came from hard copies of records. Unfortunately, no system existed whereby one agency could electronically share data relevant to this study with another agency.

Data on juveniles who did not complete DCTCP were not available. Therefore, completion of the program had to be treated as a constant, eliminating opportunities to analyze which variables influence successful program completion. Likewise, data on participants’ offense history or other misconduct were unavailable, except for the offense that resulted in the juvenile’s DCTCP referral. Literature has shown that one of the greatest risk factors for delinquent behavior is a history of antisocial behavior (Cottle, Lee, & Heilbrun, 2001; Olver, Stockdale, & Wong, 2011; Vieira, Skilling, & Peterson-Badali, 2009).

Finally, for this study recidivism was defined as any arrest for a new charge within 1 year of the participant’s release date. A study of particular interest in regard to recidivism rates was conducted by Dick et al. (2003), in which participants self-reported any reoffending within a 6 to 12 month time period post–teen court completion. Although only 12% of participants had been re-arrested during this time period, 49% admitted to some form of reoffending. Considering this finding, it is possible that DCTCP’s recidivism rates, which were measured only by re-arrests, would have been higher with a self-reported measure of any new offenses during the follow-up period.

Policy Implications

The rate of recidivism for DCTCP participants compares favorably to the recidivism rates reported in other studies of teen courts (Dick et al., 2003; Minor et al., 1999). Even so, the lack of association between the number of sanctions imposed and recidivism, and the fact that most sanctions were not associated with recidivism, gives cause for concern. Therefore, we suggest the adoption of an empirically validated risk/needs assessment instrument such as the Youth Level of Service Case Management Inventory (YLS/CMI) to aid in identifying the risk/need factors of program participants (see Hoge & Andrews, 2003).

Implementing a standardized risk/need instrument has been shown to influence the supervisory and treatment decisions of criminal justice practitioners. Vincent et al. (2012) concluded that use of a standardized risk assessment reduced the number of youth whom probation officers identified as likely to recidivate. Furthermore, the study found that use of risk-assessment instruments influences how youth are assigned to treatment services. Specifically, the use of risk-assessment instruments prompted practitioners to assign youth to services that matched their individual risk factors rather than assigning them to a smattering of available services that may or may not address their individual risks and needs (Vincent et al., 2012). Ultimately, the information provided by risk/needs assessment instruments can help criminal justice practitioners to more effectively and efficiently manage criminal justice resources (Borum, 2003; Hope, 2002).

In addition, teen courts should consider eliminating sanctions that have not been shown to reduce recidivism and implement treatment options based on best practices. Underwood, Sandor von Dresner, and Phillips (2006) thoroughly describe a number of effective treatment options for youth in the community, including but not limited to Multi-Systemic Therapy, Functional Family Therapy, and Big Brothers/Big Sisters of America. Moreover, Lipsey’s (1999) meta-analysis provides solid empirical support for cognitive-behavior programs and fails to find support for deterrence-based programs.

Finally, the DCTCP has an established network of local resources (e.g., criminal justice agencies, schools, community organizations, and volunteers). We recommend the program continue to foster and maintain relationships with local entities to maximize treatment options. Delivering the proper dosage of multi-modal treatment in the community based on individual risk/need factors will teach program participants pro-social skills and improve decision making (Gendreau, 1996; Van Voorhis, Braswell, & Lester, 2009). Collectively, these tools should be instrumental in helping youth desist from further criminal activity and reduce incidents of recidivism.

Conclusion

The growth in the number of teen court programs in the United States over the course of the last 30 years is indicative of the need for myriad community treatment options to serve and manage the juvenile offender population. The number of juveniles entering the juvenile justice system, coupled with the limited availability of criminal justice resources, requires policy makers, program administrators, and criminal justice practitioners to be judicious in their allocation of funding, oversight of program operations, and case management planning. To this end, implementing policies and procedures based on best practices is imperative for the delivery of effective treatment and reducing recidivism among juvenile offenders.

About the Authors

Brenda Vose, PhD, is an assistant professor in the Department of Criminology and Criminal Justice, University of North Florida, Jacksonville.

Kelly Vannan, MS, is a student in the Department of Criminal Justice, University of Central Florida, Orlando.

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