juvenile recidivism and length of stay

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Juvenile recidivism and length of stay Kristin Parsons Winokur a , Alisa Smith b, , Stephanie R. Bontrager a , Julia L. Blankenship a a Justice Research Center, 2898 Mahan Drive, Suite 4, Tallahassee, FL 32308, United States b Department of Criminology, University of Tampa, 401 West Kennedy Boulevard, Tampa, FL 33606, United States Abstract Official data maintained by the Florida Department of Juvenile Justice of 16,779 juveniles released from commitment programs to the community or aftercare between July 1, 1998 and June 30, 2000 were examined in this study. No consistent relationship between length of confinement and recidivism was found. The effects of length of stay were mediated based on the risk level of the commitment facility and gender. The length of confinement was only significant for juveniles released from high-risk facilities and male offenders. More research must be conducted to further examine the positive and negative impact of confinement on juvenile re-offending. Future research must include in its analysis the effect of program quality and treatment. Both factors may significantly mediate the relationship between confinement and recidivism. © 2008 Published by Elsevier Ltd. The prison, the darkest region in the apparatus of justice, is the place where the power to punish, which no longer dares to manifest itself openly, silently organizes a field of objectivity in which punishment will be able to function openly as treatment and the sentence be inscribed among the discourses of knowledge.(Foucault, 1995, p. 256) Introduction The general purposes of punishment are deterrence, rehabilita- tion, retribution, and incapacitation (Carlsmith, Darley, & Robinson, 2002; Darley, Carlsmith, & Robinson, 2000). Punish- ment policies in the last two decades have been influenced by the get toughon crime movement and return to principles of the classical school. The rational choice perspective, developed during the 1980s, concentrates on offenders choosingcrime after calculating the costs and benefits of committing crime (Cornish & Clarke, 1986). One way to control the offenses of rational criminals is to increase the punishment (the cost of crime). Increasing punishment can be achieved through lengthen- ing periods of incapacitation. Prisons and jails perform incapacitation better than any other alternative method with the exception of banishment and death. Although juvenile delinquency courts purportedly remain institutions which concentrate on rehabilitation, the get toughon crime philosophy and rhetoric permeating the 1990s (Shichor, 2000) impacted juvenile justice policy (Feld, 1990) as well as the ideological beliefs of the juvenile court- room work group, e.g., the judges and juvenile probation officers (Bazemore & Feder, 1997a,b). In a study of Florida juvenile court judges, Bazemore and Feder (1997b, p. 108) found support for an increased emphasis on punishment in the juvenile justice system.These judges also favored incapacita- tion as a rationale for punishing juvenile offenders (Bazemore & Feder, 1997b). Despite a steady decline in the rate of juvenile arrests for violent crimes over the last decade (Snyder, 2005), legislation has resulted in an increasing number of youth being prosecuted as adults for their delinquent acts, the use of juvenile court sanctions by adult courts to impose lengthier prison sentences, and the placement of more juveniles in securefacilities for longer periods of time (Johnson, 2004; Merlo & Benekos, 2003; Puzzanchera, 2003; Sickmund, 2004). By 1999, 371 juvenile offenders per 100,000 juveniles in the United States were being held in juvenile offender facilities (Sickmund, 2004). There was a 24 percent increase in the number of ad- judicated juveniles in out-of-home placements from 1990 to 1999 (Puzzanchera, 2003), and in Florida, the percent of youth Available online at www.sciencedirect.com Journal of Criminal Justice 36 (2008) 126 137 Corresponding author. Tel.: +1 813 253 3333x7283; fax: +1 813 258 7237. E-mail address: [email protected] (A. Smith). 0047-2352/$ - see front matter © 2008 Published by Elsevier Ltd. doi:10.1016/j.jcrimjus.2008.02.001

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Page 1: Juvenile recidivism and length of stay

Available online at www.sciencedirect.com

36 (2008) 126–137

Journal of Criminal Justice

Juvenile recidivism and length of stay

Kristin Parsons Winokur a, Alisa Smith b,⁎, Stephanie R. Bontrager a, Julia L. Blankenship a

a Justice Research Center, 2898 Mahan Drive, Suite 4, Tallahassee, FL 32308, United Statesb Department of Criminology, University of Tampa, 401 West Kennedy Boulevard, Tampa, FL 33606, United States

Abstract

Official data maintained by the Florida Department of Juvenile Justice of 16,779 juveniles released from commitment programs to thecommunity or aftercare between July 1, 1998 and June 30, 2000 were examined in this study. No consistent relationship between length ofconfinement and recidivism was found. The effects of length of stay were mediated based on the risk level of the commitment facility and gender.The length of confinement was only significant for juveniles released from high-risk facilities and male offenders. More research must beconducted to further examine the positive and negative impact of confinement on juvenile re-offending. Future research must include in itsanalysis the effect of program quality and treatment. Both factors may significantly mediate the relationship between confinement and recidivism.© 2008 Published by Elsevier Ltd.

The prison, the darkest region in the apparatus of justice, isthe place where the power to punish, which no longer daresto manifest itself openly, silently organizes a field ofobjectivity in which punishment will be able to functionopenly as treatment and the sentence be inscribed amongthe discourses of knowledge. (Foucault, 1995, p. 256)

Introduction

The general purposes of punishment are deterrence, rehabilita-tion, retribution, and incapacitation (Carlsmith, Darley, &Robinson, 2002; Darley, Carlsmith, & Robinson, 2000). Punish-ment policies in the last two decades have been influenced by the“get tough” on crime movement and return to principles of theclassical school. The rational choice perspective, developedduring the 1980s, concentrates on offenders “choosing” crimeafter calculating the costs and benefits of committing crime(Cornish & Clarke, 1986). One way to control the offensesof rational criminals is to increase the punishment (the cost ofcrime). Increasing punishment can be achieved through lengthen-ing periods of incapacitation.

⁎ Corresponding author. Tel.: +1 813 253 3333x7283; fax: +1 813 258 7237.E-mail address: [email protected] (A. Smith).

0047-2352/$ - see front matter © 2008 Published by Elsevier Ltd.doi:10.1016/j.jcrimjus.2008.02.001

Prisons and jails perform incapacitation better than any otheralternative method with the exception of banishment and death.Although juvenile delinquency courts purportedly remaininstitutions which concentrate on rehabilitation, the “gettough” on crime philosophy and rhetoric permeating the1990s (Shichor, 2000) impacted juvenile justice policy (Feld,1990) as well as the ideological beliefs of the juvenile court-room work group, e.g., the judges and juvenile probationofficers (Bazemore & Feder, 1997a,b). In a study of Floridajuvenile court judges, Bazemore and Feder (1997b, p. 108)found “support for an increased emphasis on punishment in thejuvenile justice system.” These judges also favored incapacita-tion as a rationale for punishing juvenile offenders (Bazemore &Feder, 1997b). Despite a steady decline in the rate of juvenilearrests for violent crimes over the last decade (Snyder, 2005),legislation has resulted in an increasing number of youth beingprosecuted as adults for their delinquent acts, the use of juvenilecourt sanctions by adult courts to impose lengthier prisonsentences, and the placement of more juveniles in “secure”facilities for longer periods of time (Johnson, 2004; Merlo &Benekos, 2003; Puzzanchera, 2003; Sickmund, 2004). By 1999,371 juvenile offenders per 100,000 juveniles in the UnitedStates were being held in juvenile offender facilities (Sickmund,2004). There was a 24 percent increase in the number of ad-judicated juveniles in out-of-home placements from 1990 to1999 (Puzzanchera, 2003), and in Florida, the percent of youth

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127K.P. Winokur et al. / Journal of Criminal Justice 36 (2008) 126–137

placed in residential custody increased the overall commitmentrate by 9 percent from 1997 to 1999 (Sickmund, 2004).

The questions arise then, with increased numbers of juvenilesbeing sent to out-of-home placements: How long are juvenilesplaced in residential facilities and what impact does long-termincapacitation or placement have on subsequent recidivism? Al-though numerous studies examined the effectiveness of juvenileprograms in reducing recidivism, few had explored the relationshipbetween “incapacitation” or length of stay and juvenile recidivism;those that did, produced mixed and inconclusive results. NeitherSaake's (1972) study of length of time spent in a juvenile probationcamp school, nor Fagan's (1995) study of youths charged withrobbery or burglary, found that longer lengths of confinementreduced subsequent recidivism. Myner, Santman, Cappelletty, andPerlmutter (1998) argued that incarceration did not serve as adeterrent for juvenile offenders. They based this conclusion ontheir examination of the relationship between the length of firstconfinement and number of subsequent convictions among asample of male juvenile offenders. Myner et al. (1998) discoveredthat the longer the length of the initial incarceration, the greater thenumber of subsequent reconvictions. To explain this finding, theysurmised that youths may be learning criminal behavior from otherdelinquent juveniles, and additionally, that labeling delinquentsmay perpetuate criminal behavior. Similarly, the Virginia PovertyLaw Center (Budeiri, 1999) reviewed Virginia's juvenile offenderpopulation and asserted that incarcerating youths beyond the pointof rehabilitation may make youth more dangerous than they werewhen initially incarcerated andmay impede successful communityreintegration following release.

Others have reached opposing conclusions. Garrity's (1956)study of adult male parolees indicated that the effect of sentencelength varied by type of offender. Pro-social offenders exhibitedlow recidivism rates regardless of sentence length, while antisocialoffenders fared better with short sentences and those classified asmanipulative did better with longer sentences. Although focusedmore on intervention differences rather than length of stay,Gottfredson and Barton (1993) found recidivism to be muchhigher among noninstitutionalized youth than those who had beeninstitutionalized. In 1988, Maryland closed one of its two juvenilecorrectional institutions. Gottfredson and Barton (1993) studiedthe effect of institutionalization on the subsequent criminalbehavior of juveniles across three groups—a group committedto the Department of Juvenile Justice Services who were in theclosed correctional institution at the time of its closure, a groupcommitted to the Department of Juvenile Justice who completed astay at the institution prior to its closing, and a group referred to theDepartment of Juvenile Justice after the closure and who wouldprobably have been committed to the correctional institution.This latter group spent little time in an institutional setting andwasconsidered by the researchers to be noninstitutionalized youth. Incomparing the groups, Gottfredson and Barton (1993, p. 604)concluded that, “the alternatives available [for the noninstitutio-nalized (post-closing) group] were less effective in reducing crimethan institutionalization would have been.”

Meta-analyses of studies examining the effects of interven-tion programs on subsequent delinquency also found incon-sistent patterns that appeared dependent on how the amount of

treatment was measured and whether institutional or noninstitu-tional programs were evaluated (Lipsey, 1992, 1995; Lipsey &Wilson, 1998). In an update on a previously conducted meta-analysis, Lipsey and Wilson (1998) examined two hundredexperimental or quasi-experimental studies and found threemeasures of treatment duration that exhibited “strong, indepen-dent, but somewhat contradictory relationships with effect size”(p. 321). While total weeks of treatment was associated withlarger effect sizes for noninstitutionalized offenders, the meannumber of treatment hours per week was negatively correlatedwith effectiveness (Lipsey & Wilson, 1998). That is, fewercontact hours were associated with larger effects. This latterfinding was due to the small effects exhibited in low-intensityprograms that operate continuously or meet frequently, such aswilderness or challenge programs. For institutionalized juve-niles only two measures were strong positive predictors of effectsize: integrity of treatment implementation, i.e., the extent towhich there was monitoring to ensure that all juveniles receivedthe intended treatment and total weeks of treatment.

The inconclusive findings from these studies may beexplained by several factors. First was variation in themeasurement of “length of stay.” Some researchers measuredlength of stay as a purely incapacitation effect, i.e., in terms of thenumber of weeks of “treatment.” Others examined the frequencyof treatment contacts (e.g., the mean hours of contact per week ormean total number of contact hours). Differences in the “type” ofoffender may have mediated the effects of length of stay andsubsequent recidivism. Few studies, however, directly comparedthe impact of length of stay by the “risk” associated with thejuvenile. Similarly, prior research demonstrated significantdifferences between noninstitutionalized and institutionalizedyouths in terms of length of stay on recidivism. So, it is importantnot to combine these two groups into a single analysis maskingthe underlying effects of treatment duration on re-offending. Thisresearch was intended to fill a gap in current information onrecidivism and length of stay in juvenile offender facilities.

Methods

Florida law

In Florida, adjudicated juveniles are generally sentenced to theDepartment of Juvenile Justice (FDJJ) for indeterminate periods oftime (youths placed in maximum-risk facilities must serve no lessthan eighteen months). The maximum length of stay, however,may not exceed the statutory maximum sentence for the crime ifcommitted by an adult. Another limitation is that juvenilesmaynotbe detained in facilities beyond their twenty-first birthday.1

Florida utilizes residential and nonresidential programs ina graduated system of increasing restrictiveness or securityand treatment duration. Nonresidential programs are designedfor youth determined by the court to be a minimum risk topublic safety and may be treated while remaining in thecommunity. Residential programs provide juvenile offenderswith a wide variety of treatment approaches and are dividedinto four security levels: low-risk, moderate-risk, high-risk,and maximum-risk. Low-risk youth are considered a low risk to

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128 K.P. Winokur et al. / Journal of Criminal Justice 36 (2008) 126–137

public safety, but require placement for treatment in aresidential setting. Juveniles adjudicated for offenses involvingfirearms, sexual offenses, life felonies and first degree feloniesare ineligible for placement in a low-risk residential program.Moderate-risk youth require close supervision and placement infacilities that are either environmentally secure, staff-secure,or are hardware-secure with walls, fencing, or locking doors.These facilities also have twenty-four-hour awake supervision,custody, care, and treatment of the juveniles. High-risk youthare considered to be a threat to public safety and require closesupervision. These facilities are hardware secure with perimeterfencing and locking doors and provide twenty-four-hour awakesupervision, custody, care, and treatment. Juveniles in thissetting are not permitted to have access to the community.Maximum-risk youth present the greatest threat to public safetyand require close supervision in a maximum-security residen-tial facility to protect the public. These programs includejuvenile correctional facilities and prisons with single-celloccupancy except during pre-release transition. The facilitiesare maximum-custody hardware-secure with perimeter securityfencing and locking doors, as well as twenty-four-hour awakesupervision, custody, care, and treatment. These youths are alsonot permitted access to the community.

Florida's residential and nonresidential juvenile programsprovide varying levels of restrictiveness and security for youthfuloffenders. They also offer a wide range of diverse treatmentoptions to meet the specific needs of the juveniles they serve.Treatment options include substance abuse programming, mentalhealth services, sexual behavior dysfunction intervention, gangbehavior modification and “boot camp” style training. In additionto treatment options, juvenile residential and nonresidential pro-grams also provide educational, prevocational, and vocationalservices. Treatment and education plans are individually designedto meet the mental health, behavioral, and education needs of theyouthful offender. This individualized approach to treatment isdesigned to maximize the rehabilitative impact of residential andnonresidential services.

The graduated nature of Florida's nonresidential andresidential programming provides an opportunity to not onlyexamine the impact of length of stay on subsequent recidivism,but also to explore the variability of this effect relative to theperceived seriousness, or public safety threat, posed by youth.Florida's centralized juvenile justice system provides a uniqueopportunity to study the impact of length of confinement, giventhe availability of juvenile and adult court recidivism data on allyouth released from both nonresidential and residential juvenileprograms in the state. In addition to the various security levels,there are a wide variety of programs, including state-operatedand contracted private providers providing a broad variationin lengths of stay ranging from under three months to overeighteen months.

Sample

The data for this analysis were compiled from official datamaintained by FDJJ in the Juvenile Justice InformationSystem (JJIS). The JJIS system was used to identify 16,779

juveniles released from commitment programs to the commu-nity or aftercare between July 1, 1998 and June 30, 2000.Demographic data for these youths were obtained from JJISand included sex, race, age at first offense, and age at the timeof program release. Measures of sex and race were binary, withone equal to male and Black, respectively.2 Age at first offenseand age at release were analyzed at the ratio level. Offensehistories were calculated based on data obtained from JJIS.Prior delinquency was operationalized, at the ratio level, as thenumber of prior referrals. Due to varying recidivism rates bygeographical locale, a variable measuring the judicial circuit inwhich the youth was adjudicated was categorized intonortheast, northwest, east, south, and west regions of Florida.Table 1 provides a snapshot of the juveniles examined in thisstudy.

The average youth in the sample was male (85 percent),White/other (53 percent), thirteen years of age at the time of his/her first offense, and roughly 16.5 years of age at programrelease, with four prior referrals, and an average length of stayof 6.3 months. As noted in Table 1, lengths of stay andrecidivism rates varied by residential/nonresidential status andsecurity level. The average length of stay for youths releasedfrom residential programs was approximately twenty-five dayslonger than that served by nonresidential youths. Among theresidential facilities, mean lengths of stay ranged from a lowof a little more than three months for low-risk programs to ahigh of nineteen months for maximum-risk, juvenile prisons.Recidivism rates were lowest for nonresidential releases(33 percent re-adjudicated/convicted) and maximum-risk, resi-dential programs (32 percent re-adjudicated/convicted), andhighest for low-risk and moderate-risk programs (each at44 percent re-adjudicated/convicted).3

Key variables

The primary independent variable of interest, length of stay,was operationalized as the number of months spent in theprogram. This measure was analyzed both at the ratio level and atthe ordinal level. Operationalizing length of stay at the ratio levelprovided an opportunity to test for a significant relationshipbetween time spent in residential and nonresidential programsand subsequent recidivism. Using an ordinal measurement oflength of stay potentially highlighted substantive differences inyouth outcomes based upon shorter or longer lengths of stay andprovided a more substantive policy-based interpretation of thedata. Treatment was “continuous,” that is, integrated into theprogram regimen, making length of stay and treatment durationequivalent. The impact of length of stay was examined whilecontrolling for demographic and prior delinquency variables.4

The dependent variable, recidivism, was defined as a sub-sequent juvenile adjudication, adjudicationwithheld, or adult con-viction for an offense that occurred within one year of a youth'srelease to the community or a conditional release program.5

Separate analyses of the effects of length of stay on recidivismwere examined for youth released from residential (institutional)and nonresidential (noninstitutional) programs. A total of fifty-five nonresidential programs and 185 residential programs were

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Table 1Descriptive statistics

Min Max Mean a S.D. Bivariatecorrelationwith recidivism

N

Sex (female=0,1=male)

0 1 0.85 0.36 0.122 ⁎⁎⁎ 16,779

Nonresidential 0 1 0.77 0.42 2,572Residential 0 1 0.86 0.34 14,207

Race (0=White/other, 1=Black)

0 1 0.47 0.50 0.115 ⁎⁎⁎ 16,779

Nonresidential 0 1 0.45 0.50 2,572Residential 0 1 0.48 0.50 14,207

Age at first offense 6.00 17.99 13.17 2.07 0.123 ⁎⁎⁎ 16,779Nonresidential 6.18 17.99 13.56 2.01 2,572Residential 6.00 17.99 13.10 2.07 14,207

Age at release 9.80 22.09 16.67 1.44 0.186 ⁎⁎⁎ 16,779Nonresidential 9.80 22.09 16.67 1.47 2,572Residential 10.35 21.80 16.67 1.43 14,207

Prior referrals 1 52 7.01 4.33 0.099 ⁎⁎⁎ 16,779Nonresidential 1 27 2.92 2.99 2,572Residential 1 52 7.38 4.42 14,207

Length of stay (months served) 16,779Nonresidential 0 21 6.30 3.40 0.122 ⁎ 2,572Residential

(all levels)0 35 7.08 4.17 0.056 14,207

Low-risk 0 12 3.18 2.42 2,368Moderate-risk 0 16 6.41 2.43 8,478High-risk 1 26 11.11 4.46 3,187Maximum-risk 2 35 19.24 4.35 174

Recidivism b 0 1 0.41 0.49 16,779Nonresidential 0 1 0.33 0.47 2,572Residential

(all levels)0 1 0.43 0.50 14,207

Low-risk 0 1 0.44 0.50 2,368Moderate-risk 0 1 0.44 0.50 8,478High-risk 0 1 0.40 0.49 3,187Maximum-risk 0 1 0.32 0.47 174

** pb .01.a Mean values for dichotomous variables correspond to the total

percentage of youths within the indicator attribute (equal to 1).b Recidivism is measured as whether youth is subsequently adjudicated/

convicted for a crime that occurs within one year of program release.⁎ pb .05.

⁎⁎⁎ pb .001.

129K.P. Winokur et al. / Journal of Criminal Justice 36 (2008) 126–137

included in the current analyses, representing all youths releasedfrom commitment programs in Florida during the study period.

Findings

Preliminary analyses

Forty-one percent of the youths released from Florida'sresidential and nonresidential commitment programs were re-adjudicated/convicted for an offense committed within one yearof program release. Table 2 presents mean lengths of stay (in

months) for youths released from nonresidential and residentialprograms broken down by sex, race, and age.

Overall, differences inmean length of stay among demographicgroups for nonresidential programs were minimal. For residentialprograms, there was a clear positive relationship between length ofstay and program security level. An inconsistent relationship,however, emerged within demographic characteristics of theyouth. Low-risk programs exhibited the greatest differences;males averaged over one month shorter lengths of confinementthan females, and the oldest youths spent half as many monthsin confinement as the youngest youths. Among each of theresidential security levels, youths who were ten years of age oryounger at the time of their first referral, were on average confinedslightly longer than those who were older when they committedtheir first offense. Similarly, youths twelve years of age andyounger at the time of release, exhibited the longest lengths of staywithin the moderate-risk and high-risk security levels. There wasvery little difference in mean length of stay by race.

Preliminary analyses demonstrated a small, but significantrelationship (0.122) between total months served and youthrecidivism from nonresidential programs. When this relation-ship was explored for youths released from residentialprograms, regardless of security level, the number of monthsa youth was confined was not significantly related to recidivism.Results are presented in Table 1.

Among demographic and legal variables, age at first offense,age at program release, and prior referrals exhibited thestrongest associations with recidivism. Review of the under-lying frequency distributions illustrated that both age at firstoffense and age at release were negatively related to whether ayouth was subsequently re-adjudicated/convicted; that is, theyounger the youth the more likely they were to recidivate.Furthermore, the more prior referrals a youth had, the morelikely he/she was to be re-adjudicated/convicted. Males weresignificantly more likely than females to be re-adjudicated/convicted, while Blacks were more likely to recidivate thanWhite/other youth.

Effects of varied lengths of stay

One question, important to policymakers and juvenilejustice professionals, was whether youthful offenders wereeffectively served in relatively short periods of confine-ment (zero to three months) as opposed to long-term confine-ment? In other words, was there a window of opportunity,which if surpassed, resulted in the detrimental effect of longerlengths of stay increasing the odds of recidivism? Table 3presents recidivism rates broken down by five length of staycategories.

Increased lengths of stay appeared to have very little effecton recidivism rates among youths released from low-risk andmoderate-risk residential programs. The rates within each of thefive categories fell within a roughly four-percentage point rangefor these youths. An interesting pattern emerged for the non-residential, minimum-risk releases, and youths discharged fromhigh-risk facilities. For these youths, recidivism rates werelower on the extremes, i.e., zero to three months and thirteen or

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Table 2Mean lengths of stay in months within security levels by sex, age, and race (total N)

Demographic characteristics Nonresidential Low-risk Moderate-risk High-risk Maximum-risk Total N

SexFemale 5.97 4.20 6.38 8.75 0.00

(600) (442) (1,089) (410) (0) (2,541)Male 6.30 3.18 6.41 11.11 19.24

(1,972) (1,926) (7,389) (2,777) (174) (14,238)

Age at first offense10 years or younger 6.27 3.99 6.61 11.54 19.68

(265) (319) (1,238) (568) (37) (2,427)11 to 12 years 6.15 3.70 6.44 11.26 19.51

(625) (671) (2,314) (1,040) (53) (4,703)13 years 6.46 3.20 6.44 10.89 19.29

(513) (504) (1,806) (656) (34) (3,513)14 years or older 6.31 2.49 6.29 10.83 18.58

(1,169) (874) (3,120) (923) (50) (6,136)

Age at release12 years or younger 5.67 5.93 6.62 17.33 0.00

(36) (71) (63) (3) (0) (173)13 years 5.34 5.04 6.14 11.29 0.00

(82) (165) (265) (24) (0) (536)14 years 5.71 3.65 6.21 10.34 0.00

(231) (383) (832) (135) (0) (1,581)15 years 6.18 3.13 6.39 10.83 19.67

(447) (509) (1,518) (381) (6) (2,861)16 years 6.17 2.87 6.49 10.92 20.00

(614) (544) (2,220) (707) (11) (4,096)17 years 6.58 2.48 6.42 11.10 18.68

(644) (500) (2,163) (943) (47) (4,297)18 years or older 6.64 2.53 6.45 11.44 18.68

(518) (196) (1,417) (994) (110) (3,235)

RaceBlack 6.31 3.48 6.41 11.13 19.50

(1,149) (1,050) (3,955) (1,673) (106) (7,933)White 6.29 2.94 6.42 11.11 18.82

(1,316) (1,247) (4,255) (1,432) (67) (8,317)Other 6.31 3.08 6.24 10.66 19.00

(107) (71) (268) (82) (1) (529)Overall mean 6.30 3.18 6.41 11.11 19.24Total N 2,572 2,368 8,478 3,187 174 (16,779)

Table 3Recidivism rates for youths released from nonresidential and residentialprograms by length of stay and security level

Security level Length of stay in months

0 to 3 4 to 6 7 to 9 10 to 12 13 or more х2

Statistic a

Nonresidential 28.4% 35.8% 32.0% 33.1% 26.3% 0.067⁎

(539) (1,029) (604) (263) (137)Low-risk 43.7% 43.5% 49.5% 40.4% 0.0% 0.034

(1,502) (621) (188) (57) (0)Moderate-risk 42.0% 44.7% 44.0% 42.1% 40.3% 0.022

(536) (4,906) (2,144) (656) (236)High-risk 20.3% 43.8% 39.6% 44.0% 37.9% 0.077⁎⁎

(59) (347) (968) (845) (968)a The chi-square based measure, Cramer's V, is reported here.

130 K.P. Winokur et al. / Journal of Criminal Justice 36 (2008) 126–137

more months (significant at the 0.05 level or lower). Fig. 1provides a graphical representation of these findings. The datasuggested that for a subset of youths in nonresidential and high-risk programs, short lengths of stay were relatively effective,while another group required longer confinement periods inorder to respond positively. This relationship was exploredfurther using multivariate analyses.6

Multivariate analyses and varied lengths of stay

A significant relationship between length of stay andrecidivism was found for youths released from nonresidentialand high-risk residential programs in bivariate analyses. Thisrelationship was examined controlling for demographic andlegal variables using logistic regression analysis. The results arereported in Table 4.

The results shown in Panel A of Table 4 indicated that thenumber of months a youth was confined was significantly

related to the likelihood the youth recidivated, but only amongyouths released from residential (as opposed to nonresidentialprograms). Further modeling revealed that youth serving

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Fig. 1. Recidivism rates by length of stay and security level.

131K.P. Winokur et al. / Journal of Criminal Justice 36 (2008) 126–137

twelve months or less in a residential facility were more likely tosubsequently be re-adjudicated/convicted than youth confinedfor thirteen months or longer. In comparison to those confinedlonger, for example, the odds that youths committed for four tosix months were re-adjudicated was nearly 1.25 times greaterthan that of youths incarcerated for thirteen or more months.Holding all other individual level factors in the model constant,youths with four to six month stays had a 56 percent probabilityof recidivating following program release. The relative effects oflength of stay on recidivism were not as substantial as othersignificant variables in the model; for example, prior referrals orhaving the case processed in the northwest, northeast, or west, incomparison to the southern region of Florida. The overalllogistic model for residential program releases was significant atthe 0.001 level using the model chi-square statistic. The modelpredicted 63.1 percent of the responses correctly and had apseudo R2 equal to 0.11.

The multivariate analyses shown in Panel A demonstratedthat upon controlling for legal and demographic characteristics,length of stay had minimal effect on recidivism among youthsreleased from nonresidential facilities. Further modeling of thedichotomized length of stay measure was not indicative ofoutcome differences between short, moderate, and long-termnonresidential stays. As such, the analyses shifted to only thoseyouth released from residential programs. Given the signifi-cant influence of sex in initial logistic regression models, theanalysis turned to the impact of length of stay for male andfemale juvenile offender populations. The results are presentedin Table 5.

The findings for females released from residential programssuggested a pattern similar to that exhibited in Fig. 1, in whichrecidivism was decreased when length of stay was either short

(zero to three months) or extended (thirteen months or longer).While length of stay failed to reach statistical significancein the model for female offenders, it appeared to be a signifi-cant predictor within the model for male youths. Overall, thefindings for male offenders suggested that as the length of stayincreased the odds of recidivism became lower, or conversely,that shorter lengths of stay were associated with higher re-cidivism. The results presented in Panel B revealed thatmales with shorter residential stays (less than or equal totwelve months) had higher odds of recidivating within one yearwhen compared to those with stays over thirteen months. Theodds that a male youth recidivated, however, were only in-creased by roughly 10 percent when they were confined forone year or less, rather than thirteen months or longer. Similarto the overall recidivism predictors identified for residentialprograms in general, being younger at the time of programrelease, having more prior referrals, and being Black, all sig-nificantly increased the odds of males being re-adjudicated/convicted. Race was not a significant predictor of recidivismfor female juvenile offenders. Youth processed in the southernregion of the state, comprised primarily of the Miami/Dade area,were significantly less likely to be re-adjudicated withinone year of program release.7

Perhaps the most appropriate analysis of the effects of lengthof stay on recidivism in Florida was one that examined theeffects within security levels, as opposed to globally for allresidential programs. As illustrated earlier, there were four dis-tinct residential security levels in Florida's system: low-risk,moderate-risk, high-risk, and maximum-risk programs. Thelevel of security generally increased with the seriousness of theoffenders served at that level. Tables 6a and 6b present logisticregression analyses for each level.

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Table 5Logistic regression predicting recidivism among male and female juvenileoffenders released from residential commitment programs in Florida

Panel A a

Female Male

B S.E. Oddsratio

B S.E. Oddsratio

Continuous lengthof stay

−0.015 0.018 0.986 −0.012 ⁎⁎ 0.005 0.988

Panel B

Female Male

B S.E. Oddsratio

B S.E. Oddsratio

Ordinal length of stay b

0 to 3 months −0.102 0.317 0.903 0.228 ⁎⁎ 0.079 1.2564 to 6 months 0.287 0.274 1.333 0.212 ⁎⁎ 0.069 1.2367 to 9 months 0.083 0.280 1.086 0.202 ⁎⁎ 0.072 1.22310 to 12 months −0.049 0.316 0.953 0.208 ⁎ 0.082 1.231

Age at first offense(months)

0.037 0.039 1.038 0.006 0.011 1.006

Age at release(months)

−0.354 ⁎⁎⁎ 0.046 0.702 −0.304 ⁎⁎⁎ 0.016 0.738

Prior referrals 0.083 ⁎⁎⁎ 0.015 1.087 0.073 ⁎⁎⁎ 0.005 1.076Black 0.124 0.107 1.132 0.436 ⁎⁎⁎ 0.039 1.547Region c

Northwest 0.273 0.217 1.314 0.356 ⁎⁎⁎ 0.072 1.427Northeast 0.293 0.196 1.340 0.292 ⁎⁎⁎ 0.065 1.339East 0.043 0.205 1.044 0.108 1.114West 0.258 0.195 1.295 0.298 ⁎⁎⁎ 0.062 1.348

0.068Constant 3.487 0.729 3.617 0.252% correctpredictions

70.23% 62.10%

Nagelkerke(pseudo) R2

0.085 0.099

Chi-square (df) 119.61(12) ⁎⁎⁎

940.45(12) ⁎⁎⁎

Total N 1,938 12,241

a The model in Panel A controls for all of the covariants shown in Panel B.These covariant coefficients are not substantially different from those detailed inPanel B and are therefore not provided here, but are available upon request.

b Length of stay is an ordinal variable with the reference attribute equal tothirteen months or longer.

c Region is an ordinal variable with the reference attribute equal to thesouth region.

⁎ pb .05.⁎⁎ pb .01.

⁎⁎⁎ pb .001.

Table 4Logistic regression predicting recidivism among juvenile offenders released fromnonresidential and residential commitment programs in Florida

Panel A a

Nonresidential Residential

B S.E. Oddsratio

B S.E. Oddsratio

Continuous lengthof stay

−0.003 0.014 0.997 −0.012 ⁎⁎ 0.005 0.988

Panel B

Nonresidential Residential

B S.E. Oddsratio

B S.E. Oddsratio

Ordinal length of stay b

0 to 3 months −0.129 0.230 0.879 0.197 ⁎⁎⁎ 0.077 1.2174 to 6 months 0.271 0.214 1.311 0.225 ⁎⁎⁎ 0.066 1.2527 to 9 months 0.080 0.221 1.083 0.185 ⁎⁎ 0.070 1.20410 to 12 months 0.194 0.243 1.214 0.182 ⁎ 0.079 1.200

Age at first offense(months)

0.057 ⁎ 0.029 1.059 0.009 0.011 1.009

Age at release(months)

−0.322 ⁎⁎⁎ 0.037 0.725 −0.310 ⁎⁎⁎ 0.015 0.734

Prior referrals 0.103 ⁎⁎⁎ 0.017 1.108 0.074 ⁎⁎⁎ 0.005 1.077Male 0.744 ⁎⁎⁎ 0.114 2.105 0.680 ⁎⁎⁎ 0.055 1.973Black 0.480 ⁎⁎⁎ 0.090 1.615 0.398 ⁎⁎⁎ 0.036 1.488Region c

Northwest 0.528 ⁎⁎ 0.206 1.696 0.339 ⁎⁎⁎ 0.068 1.404Northeast 0.136 0.130 1.146 0.292 ⁎⁎⁎ 0.061 1.340East 0.119 0.145 1.126 0.097 0.064 1.102West 0.049 0.130 1.050 0.287 ⁎⁎⁎ 0.059 1.332

Constant 2.285 0.575 3.013 0.240% correctpredictions

68.42% 63.07%

Nagelkerke(pseudo) R2

0.108 0.108

Chi-square (df) 206.01(13) ⁎⁎⁎

1195.21(13) ⁎⁎⁎

Total N 2,568 14,179a The model in Panel A controls for all of the covariants shown in Panel B.

These covariant coefficients are not substantially different from those detailed inPanel B and are therefore not provided here, but are available upon request.

b Length of stay is an ordinal variable with the reference attribute equal tothirteen months or longer.

c Region is an ordinal variable with the reference attribute equal to the southregion.

⁎ pb .05.⁎⁎ pb .01.

⁎⁎⁎ pb .001.

132 K.P. Winokur et al. / Journal of Criminal Justice 36 (2008) 126–137

For all levels, length of stay appeared to have no signifi-cant impact on the likelihood of re-adjudication/conviction,when demographic and legal variables were controlled. Panel Ademonstrates this finding for low, moderate, high, and maximum-risk residential releases. Further analyses incorporated dichot-omized lengths of stay and revealed a potential curvilinearrelationship between the duration of treatment and recidivism. Foryouth released from high-risk residential programs, their term ofincarceration did appear to be a significant predictor of their oddsto recidivate. This effect was somewhat unique. The graphical

representation of this effect in Fig. 1, as well as the combination ofnegative and positive coefficients for length of stay, suggested thata curvilinear relationship might exist between recidivism andlength of stay for this pool of relatively serious offenders. Youthreleased from high-risk programs after confinement for zero tothree months appeared less likely to recidivate than those confinedfor the longer, thirteen or more months. Moderate lengths of stay(four to six and ten to twelve months) appeared to have theopposite effect. The model was significant at the 0.001 level usingthe model chi-square statistic. The pseudo R2 was 0.12 and themodel accurately predicted whether youths were re-adjudicated/convicted for 59.56 percent of youths.

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Table 6aLogistic regression predicting recidivism by program security level for juvenileoffenders released from residential commitment programs in Florida

Panel A a

Low-risk Moderate-risk

B S.E. Oddsratio

B S.E. Oddsratio

Length of stay(ratio) b

−0.033 0.022 0.967 0.002 0.010 1.002

Panel B

Low-risk c Moderate-risk

B S.E. Oddsratio

B S.E. Oddsratio

Length of stay (ordinal) d

0 to 3 months 0.198 0.169 1.219 0.014 0.165 1.0144 to 6 months 0.104 0.168 1.110 0.086 0.141 1.0907 to 9 months – – – 0.090 0.145 1.09410 to 12 months – – – 0.066 0.160 1.069

Age at first offense(months)

0.018 0.029 1.018 0.024 0.014 1.024

Age at release(months)

−0.295 ⁎⁎⁎ 0.038 0.744 −0.318 ⁎⁎⁎ 0.020 0.728

Prior referrals 0.096 ⁎⁎⁎ 0.017 1.101 0.078 ⁎⁎⁎ 0.007 1.081Male 0.682 ⁎⁎⁎ 0.128 1.977 0.625 ⁎⁎⁎ 0.072 1.868Black 0.537 0.089 1.712 0.372 ⁎⁎⁎ 0.047 1.451Region e

Northwest 0.190 0.181 1.209 0.285 ⁎⁎⁎ 0.090 1.330Northeast 0.090 0.161 1.095 0.309 ⁎⁎⁎ 0.081 1.362East −0.076 0.166 0.927 0.067 0.085 1.069West 0.258 0.168 1.295 0.209 ⁎⁎ 0.075 1.232

Constant 2.650 0.543 3.168 0.330% correct

predictions55.96% 55.98%

Nagelkerke(pseudo) R2

0.129 0.101

Chi-square (df) 239.16(11) ⁎⁎⁎

664.20(13) ⁎⁎⁎

Total N 2,364 8,462

* pb .05.a The model in Panel A controls for all of the covariants shown in Panel B.

These covariant coefficients are not substantially different from those detailed inPanel B and are therefore not provided here, but are available upon request.

b There were no female offenders released from maximum-risk residentialprograms during the study period. Due to lack of variability in shorter lengths ofstay, the variable was measured only at the ratio level for maximum-risk youth.

c There were no low-risk residential offenders confined for longer thantwelve months and minimal variation on the ten to twelve month attribute;therefore the reference attribute for the low-risk logistic model was seven ormore months.

d Length of stay is an ordinal variable with the reference attribute equal tothirteen months or longer for moderate- through high-risk, and seven months orlonger for low-risk.

e Region is an ordinal variable with the reference attribute equal to the southregion.⁎⁎ pb .01.⁎⁎⁎ pb .001.

Table 6bLogistic regression predicting recidivism by program security level for juvenileoffenders released from residential commitment programs in Florida

Panel A a

High-risk Maximum-risk b

B S.E. Oddsratio

B S.E. Oddsratio

Length of stay(ratio)

−0.010 0.009 0.990 0.050 0.041 1.052

Panel B

High-risk

B S.E. Oddsratio

Length of stay (ordinal) c

0 to 3 months −0.748 ⁎ 0.338 0.473 – – –4 to 6 months 0.287 ⁎ 0.136 1.332 – – –7 to 9 months 0.123 0.099 1.131 – – –10 to 12 months 0.231 ⁎ 0.101 1.260 – – –

Age at first offense(months)

−0.033 0.022 0.968 0.099 1.007

Age at release(months)

−0.300 ⁎⁎⁎ 0.034 0.741 0.165 0.809

Prior referrals 0.065 ⁎⁎⁎ 0.008 1.067 0.091 0.036 1.096Male 0.749 ⁎⁎⁎ 0.125 2.114 – – –Black 0.422 ⁎⁎⁎ 0.079 1.525 0.372 ⁎⁎ 0.357 0.689Region d

Northwest 0.507 ⁎⁎⁎ 0.142 1.660 −0.075 0.748 0.927Northeast 0.361 ⁎⁎ 0.128 1.435 0.230 0.632 1.258East 0.302 ⁎ 0.130 1.353 −0.240 0.621 0.787West 0.445 ⁎⁎⁎ 0.123 1.561 0.288 0.606 1.333

Constant 3.252 0.557 1.200 3.076% correctpredictions

59.56% 69.94%

Nagelkerke(pseudo) R2

0.123 0.111

Chi-square (df) 302.68(13) ⁎⁎⁎

14.27(9)

Total N 3,180 173

a The model in Panel A controls for all of the covariants shown in Panel B.These covariant coefficients are not substantially different from those detailed inPanel B and are therefore not provided here, but are av ailable upon request.

b There were no female offenders released from maximum-risk residentialprograms during the study period. Due to lack of variability in shorter lengths ofstay, the variable was measured only at the ratio level for maximum-risk youth.

c Length of stay is an ordinal variable with the reference attribute equal tothirteen months or longer for moderate- through high-risk, and seven months orlonger for low-risk.

d Region is an ordinal variable with the reference attribute equal to thesouth region.

⁎ pb .05.⁎⁎ pb .01.

⁎⁎⁎ pb .001.

133K.P. Winokur et al. / Journal of Criminal Justice 36 (2008) 126–137

Examining this relationship further by transforming theindependent length of stay variable into total months squaredand cubed, significant coefficients were found, suggesting thatthe impact of length of stay on recidivism was curvilinear in

nature.8 Working from the equation presented in Table 7, theprobability of recidivism by race, gender, and region werecalculated and plotted in Charts 1 and 2 according to length ofstay for youth released from high-risk residential programs. Asshown in Charts 1 and 2, the probability of recidivism, holdingdemographic and legal factors constant, was lowest forjuvenile offenders receiving treatment in high-risk facilities

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Table 7Test of curvilinear effects of length of stay on recidivism for youth released fromhigh-risk residential programs in Florida

High-risk

B S.E. Odds ratio

Length of stay a

Total months 0.237 0.103 1.267Months squared −0.020 0.008 0.980Months cubed 0.000 0.000 1.001Age at release (months) b −0.322 0.031 0.725Prior referrals 0.070 0.007 1.073Male 0.771 0.125 2.162Black 0.433 0.078 1.542South c −0.421 0.106 0.657

Constant 2.879 0.660% correct predictions 62.26%Nagelkerke (pseudo) R2 0.118Chi-square (df) 291.50 (8)Total N 3,187

a Length of stay is measured here at the ratio level with two correspondingtransformation variables.b Age at first offense was removed from the high-risk model because it was

not a significant predictor of recidivism in any of the previous residentialprediction equations.c South is a dichotomous regional variable (0=non-south, 1=south).

134 K.P. Winokur et al. / Journal of Criminal Justice 36 (2008) 126–137

for periods of one to four months, or stays of seventeen totwenty months in duration. Conversely, the probability ofsubsequent delinquent adjudication or criminal conviction washighest for those released from high-risk programs after a six

Chart 1. Probability of recidivism by gender

to eleven month length of stay, or after any term beyondtwenty-three months. The difference between the lowest andhighest probability of recidivism for each comparisongroup demonstrated that there were substantial differences insubsequent re-offending associated with varying lengths ofstay.

Black male offenders from southern Florida, for instance,had a 27 percent probability of future adjudication or convictionif treated at high-risk facilities for one month. This probabilitynearly doubled to 48 percent if the length of stay reachedtwenty-six months. These findings suggested that treatmentduration significantly impacted recidivism for youths assignedto high-risk residential services. Additionally, lengths of stayless than one year in high-risk juvenile residential programsmay not be of sufficient duration to achieve the positive effectof reduced future delinquent offending. There was alsoevidence of “diminishing returns” with high-risk residentialtreatment effects leveling off for lengths of stay betweenseventeen and twenty months. In fact, lengths of stay beyond aterm of twenty months were related to a 9 to 15 percentincrease in the probability of recidivating for youth in high-riskcommitment programs. Extensive meta-analysis research hassupported these findings and generally indicated that littleevidence showed short-term interventions had an effect, andthose that were too lengthy might result in reduced effects asyouth gave up, co-mingled with high-risk youth, and/ordecreased bonds with pro-social family and friends (Andrews,1995; Lipsey, 1992, 1995).

Turning now to maximum-risk commitments, youth incar-cerated in juvenile facilities requiring a minimum stay ofeighteen months, appeared to respond differently to varying

and race: northern and central Florida.

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Chart 2. Probability of recidivism by gender and race: southern Florida.

135K.P. Winokur et al. / Journal of Criminal Justice 36 (2008) 126–137

lengths of stay. The ordinal scale used to evaluate the impact oflength of stay for lower security level programs, was unsuitablefor analysis with maximum-risk releases. Fig. 2 depicts thebivariate relationship between length of stay and recidivism foryouths released from maximum-risk facilities, i.e., as the

Fig. 2. Recidivism by length of stay for youths released

number of months incarcerated increased, the recidivism rate ofyouths released also increased. The logistic regression analysesin Panel A, however, demonstrated that the likelihood to be re-adjudicated/convicted was not significantly related to length ofstay for youth released from maximum-risk programs. Prior

from maximum-risk residential juvenile facilities.

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Notes

1. One exception to this general principle exists if the juvenile offendermeets the criteria for “habitual” juvenile offender and then may be detained in ajuvenile facility until the age of twenty-two.

2. Measures of ethnicity were not available in the data.3. This finding is not surprising as youth confined in maximum-risk

juvenile prisons are on average considerably older than their counterparts inlower risk programs, and this therefore may in part be due to a maturationeffect.

4. The study would be enhanced by the inclusion of measures of treatmentcharacteristics in the prediction models. The variability of treatment servicesamong residential and nonresidential programs, however, makes the operatio-nalization of universal treatment measures difficult. Further, data of this typewere not uniformly recorded and stored during the study time period.

5. Two alternative measures of recidivism were examined: rearrest withinone year of release and juvenile or adult re-incarceration within one year ofrelease. For both measures, the effect of length of stay was not appreciablydifferent from that found using re-adjudication/conviction as the dependentvariable. This is also the same definition officially used by the FloridaDepartment of Juvenile Justice for internal research analyses and reporting.

136 K.P. Winokur et al. / Journal of Criminal Justice 36 (2008) 126–137

referral was the only significant predictor of recidivism for thehighest security level releases.

Conclusion and policy implications

Florida data revealed no consistent relationship between lengthof confinement and recidivism. Length of stay was significant atthe bivariate level for nonresidential and high-risk programreleases, however, in multivariate analyses the effects of length ofstay were only significant for youths released from high-riskfacilities. Time served in low-risk, moderate-risk, and maximum-risk programs was unrelated to recidivism, after controlling fordemographic and legal variables. In comparing female and malejuvenile offenders, the effects of length of stay were significantonly in the logistic model for males. Shorter lengths of stay formales increased the odds of subsequent adjudication or convictionfor an offense within one year of program release.

The impact of months served for high-risk offenders wasvaried. The shortest lengths of stay within this security levelresulted in decreased chances for recidivism. Intermediate periodsof confinement and very long stays were associated with highprobability of recidivism. In comparison, the probability of futureadjudication or conviction for high-risk commitments withseventeen to twenty months of treatment was similar to theprobability of those receiving one to four months of services.A number of competing explanations for these findings werehypothesized. The curvilinear association between length of stayand recidivismmay indicate that youthswho responded positivelyto the program were released quickly. Alternatively, they mayhave reached the jurisdictional age limit of the juvenile justicesystem and were therefore released prior to what would be con-sidered a typical program completion. Research has shown thatmaturation impacts the likelihood that youths desist fromfurther involvement in criminal activity and may explain lowerrates of recidivism. It may also be likely, as Garrity (1956) andothers noted, that the impact of length of stay is mediated by theseriousness of the offender. A comparison of the characteristicsof youths released after relatively short lengths of stay relativeto those incarcerated longer in high-risk facilities, suggested thatoffender seriousness was indeed related to time served. A smallerpercentage of youth committed for zero to three months werethirteen years of age or younger at the time of their first offense,than their counterparts confined for thirteen months or longer.Those incarcerated longer were also generally older at the timeof release, and a much larger percentage of these youths weremales in comparison to those released sooner.

The positive impact of longer lengths of stay for high-riskoffenders may be due to the fact that facilities at this level havea design length of stay ranging from nine to twelve months.Longer months served at this level may positively impactoutcomes if youth continued in the program longer than thedesigned length of stay. As Lipsey (1992, 1995) points out,however, these effects were likely due to duration of treatmentrather than mere incarceration effects. In addition, evidencesuggesting a linear or curvilinear relationship in which certainlengths of stay have the effects of reducing recidivism, may bedue to variations in the type of programming received (e.g.,

the organization, staffing, and administration of the program)as well as the program's fidelity to evidenced-based treatmentpractices (Lipsey & Wilson, 1998).

Identifying a relationship between treatment duration and re-cidivism may require examining other aspects of juvenile justiceprogramming. Lipsey andWilson (1998) found that treatment typeand the characteristics of the program were important factors indetermining effect sizes. Future research should include measuresof program quality, such as those provided by the CorrectionalProgram Assessment Inventory (Andrews, 1994, 1995), andspecific information about the treatment modality employed toassess whether the impact of length of stay is dependent onprogram characteristics. Programs employing ineffective treat-ment modalities would not be expected to decrease recidivismthrough longer lengths of stay. Rather, increasing the length ofconfinement under these circumstances may lead to increasedrecidivism. Studying high quality programs employing treatmentmethods shown to be effective (e.g., cognitive behavioralapproaches) may enable researchers to identify the point atwhich further treatment produces diminishing returns. Likewise,an examination that compares outcomes relative to offendercharacteristics may also provide a better understanding of whyvarying length of stay intervals produce different outcomes. Someyouths may be better served in a relatively short period of time incertain program models, while others may need longer treatmentintervals to attain similar outcomes. Future research shouldthoroughly address these issues with an eye toward discerningpotential threshold and diminishing returns effects, as well as acurvilinear relationship between length of stay and juvenilerecidivism.

Acknowledgements

This project was funded by the National Center for JuvenileJustice under subcontract No. 70099-010 grant No. 19990JN-FX-K002, Office of Juvenile Justice and Delinquency Preven-tion, “National Juvenile Justice Data Analysis Project.”

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6. Youths committed to maximum-risk juvenile prisons were omitted fromTable 3 as 95 percent had lengths of stay greater than thirteen months; thosewith shorter sentences typically did not complete program services and werereleased due to reaching the maximum age of juvenile court jurisdiction.Sentence lengths for youths released from maximum-risk programs generallyranged from eighteen to thirty-five months.

7. While the focus of this article is on length of stay, it should be noted thatthis finding is not necessarily indicative that youth in the southern part of the stateare less likely to recidivate. Rather, interviews with juvenile probation officers,attorneys and juvenile court judges suggest that this finding is reflective of thegreater severity of cases presenting in the Miami area and a correspondinglyhigher threshold for prosecution; or as some have termed it, a ‘local legal culture’that is less likely to move forward on violations of probation or less seriousoffenses, which comprises the majority of re-offending by youth.

8. The previous multivariate analyses were not indicative of a linear orcurvilinear relationship between length of stay and recidivism for youthreleased from nonresidential or low, moderate, or maximum-risk residentialprograms. For this reason, further modeling to test for potential curvilineareffects of length of stay were only conducted for high-risk residential releases.

137K.P. Winokur et al. / Journal of Criminal Justice 36 (2008) 126–137

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