The Prediction of Criminal Recidivism in Juveniles: A Meta-Analysis

Running Head: JUVENILE RECIDIVISM

The Prediction of Recidivism in Juvenile Sexual and Violent Offenders:

A Meta-Analysis

Ria J. Lee

Cindy C. Cottle

Kirk Heilbrun

MCP Hahnemann University

DRAFT

10-27-03

Please do not quote or cite without permission

Juvenile Recidivism 2

Abstract

We used meta-analysis to identify variables that are most strongly associated with

recidivism rates among juvenile offenders for two outcomes: sexual reoffending and violent

reoffending. A total of 9 published studies representing 1,160 participants met inclusion criteria

for sexual reoffending among juveniles. Among studies examining violent juvenile reoffending,

a total of 4 studies, representing 380 participants, met inclusion criteria. For sexual offense

recidivism, predictor variables were grouped into three categories: 1) offense history variables,

2) family/social factors, and 3) intervention variables. Among studies examining violent juvenile

offenders, only one used violent reoffending as an outcome variable; the remaining studies

focused on any reoffending among violent juvenile offenders. For the “any recidivism” outcome

among violent non-sexual offenders, only a single variable could be compared among studies – a

composite variable, encompassing various treatment interventions, which was created for this

meta-analysis. Effect sizes were calculated for this variable for both sexual and violent juvenile

offenders, respectively. For juvenile sexual reoffending, predictors were compared within and

across each of the three categories for their impact on reducing recidivism.

The delivery of treatment interventions was associated with a decrease in sexual

reoffending risk. Younger age and acquaintance-type relationship to the victim were also

positively related to sexual reoffense risk. For violent reoffending, the provision of specific

treatment interventions was effective in reducing recidivism when compared with the delivery of

standard services. Methodological considerations and the implications of these results are

discussed.


Predictors of Recidivism in Juvenile Sexual and Violent Offenders:

A Meta-Analysis

Violent and sexual offending present significant concerns for the public and considerable

challenges for the justice system in the United States. Juveniles have been the focus of many of

these concerns, particularly during the last decade. While persistent adolescent offenders

constitute only a minority of the offender population in the United States, they account for

disproportionately large rates of offending in certain respects. Offenders younger than 21 years

old accounted for 32% of all persons arrested in 1999 (FBI, 2000). The number of juveniles

arrested for violent crimes (including murder, robbery, and aggravated assault) has increased by

14.9% from 1989 to 1998, compared to an increase of only 2.6% in arrests for violent crimes

among adults (FBI, 1999). The Office of Juvenile Justice and Delinquency Prevention (OJJDP,

1998) reported that chronic violent offenders constituted about 15% of adolescent samples in two

longitudinal studies conducted in Denver, Colorado and Rochester, New York between 1987 and

1992, but were responsible for 75 and 82% of the violent offenses committed in the Rochester

and Denver samples, respectively (Huizinga, Loeber, & Thornberry, 1994; Huizinga, Loeber, &

Thornberry, 1993; OJJDP, 1998). These data also suggest that an earlier onset of violent crime

is associated with higher rates of chronic violent offending; for example, among those who

committed their first violent offenses before age ten, 39-62% became chronic violent offenders

(OJJDP, 1998). Clearly prevention or risk reducing interventions could have a particularly

important effect on rates of offending if they reduced the prevalence of chronic juvenile

offending. Gauging the strength of risk factors and protective factors for different kinds of

juvenile offending could thus have important implications for practice and policy as well as


ongoing research, possibly facilitating the design of more effective risk-reducing intervention

strategies for children and adolescents.

A review of the literature suggested that recidivism research in juvenile criminal justice

tends to focus on two major areas: prediction and intervention. Typically, the outcome measure

used by researchers falls into one of three categories of juvenile delinquency: general recidivism

(including all types of reoffending behavior), sexual recidivism (including only sexual

reoffending), or violent recidivism (including sexual recidivism but not property crime or drug

crime).

Meta-analysis is a useful tool for estimating the strength of relationships among

predictive or outcome variables across a number of studies. There are at least six important areas

to which meta-analysis can be applied in the investigation of juvenile offending. These areas

include: 1) predictors of general recidivism, 2) predictors of sexual recidivism, 3) predictors of

violent recidivism, 4) effects of interventions on general recidivism, 5) effects of interventions

on sexual recidivism, and 6) effects of interventions on violent recidivism (see Table 1).

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Several of these areas have already been addressed using meta-analysis. Predictors of

general recidivism have recently been examined (Cottle, Lee, & Heilbrun, 2001). The effect of

interventions on general recidivism in juvenile offenders has also been investigated (Lipsey,

1992), as has the impact of interventions on violent reoffending (Lipsey & Wilson, 1998).

However, there has been insufficient empirical research to date on the impact of interventions for

juvenile sexual offenders, in that few studies in this area have employed comparison or control


groups that would facilitate their use in meta-analysis. We were able to locate only four such

published studies (Borduin, Henggeler, Blaske, & Stein, 1990; Kahn & Chambers, 1991;

Worling & Curwen, 2000; and Hagan & Cho, 1996), probably too few for meaningful meta-

analysis. The remaining areas in Table 1 – the prediction of violent recidivism and the

prediction of sexual recidivism – have apparently not been addressed through meta-analysis. In

this article, we will describe two meta-analyses, one for each of these respective areas. The

studies included in the analyses were further divided into (1) violent, non-sexual reoffending,

and (2) non-violent, sexual reoffending, to allow identification of predictors that could

distinguish the two areas. Violent sexual reoffending obviously represents an area of overlap

between these two kinds of recidivism . Similarly, sexual reoffending behavior can

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be either violent (“hands-on”) or non-violent (“hands-off”) in nature.1

METHOD

Participants

Computer searches of the databases PsychLit, PsychInfo, MedLine, Ebsco, Elsevier, and

Educational Resources Information Center (ERIC) were conducted to locate published articles

from 1980 to 2000 using the following key words: sexual recidivism, sexual offending, sexual

assault, violence, violent behavior, violent offending, prediction of violence, juvenile

delinquency, juvenile crime, recidivism, criminal behavior, psychopathy, rearrest, and court

1 An abbreviated discussion of the results in this paper, as well as the results of other meta-analyses of juvenile offending, is provided in Heilbrun, Lee & Cottle (in press).


transfers, waivers, and certification. We required that a study consider juveniles between the

ages of 7 and 211 who had at least one prior arrest for a sexual or violent crime, and provide data

on subsequent offending (defined by either official records or self-report) resulting in

reincarceration, rearrest, or revocation of parole, in order to be selected for meta-analysis.

Published studies investigating sexual recidivism among juveniles and any recidivism

among violent juvenile offenders were reviewed. A total of nine published studies were

identified as meeting criteria for inclusion in the meta-analysis for sexual reoffending. Four

studies were identified as meeting criteria for inclusion in the meta-analysis for reoffending

among violent juvenile offenders. Official records were used by the majority of the twelve

studies to obtain recidivism data. However, two studies (Henggeler, Melton, & Smith, 1992 and

Henggeler, Melton, Brondino, Scherer, & Hanley, 1997) used the Self-Reported Delinquency

Scale (SRD; Elliot, Ageton, Huizinga, Knowles, & Canter, 1983), in addition to official records,

to obtain recidivism data. Studies used in the meta-analysis are identified in the References

section with an accompanying asterisk (*).

Recidivism Among Juvenile Sexual Offenders

The mean sample size of the studies investigating juvenile sexual offenders was 128.9,

with a range of 16 – 221 (see Table 2). The mean outcome period was 54.2 months, with an

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associated range of 24 to 228 months. The recidivism rates for these outcome periods were

reported for sexual reoffending (mean = 14.3%), nonsexual reoffending (mean = 41.0%), and

any reoffending (mean = 48.7%). The total reoffense rate reported in this meta-analysis is not a


reflection of the summation of the sexual and nonsexual reoffending rates. This resulted because

some studies (e.g., Dolan, Holloway, Bailey, & Kroll, 1996; Kahn & Chambers, 1991; Lab,

Shields, & Schondel, 1993) did not report a recidivism rate for nonsexual reoffending, and others

(e.g., Borduin, Henggeler, Blaske, & Stein, 1990; Dolan, Holloway, Bailey, & Kroll, 1996;

Smith & Monastersky, 1986) did not report a recidivism rate for any reoffending. This suggests

that the percentage of juveniles who were rearrested for a nonsexual offense or for any offense

reported in this meta-analysis is an underestimate of the true rates of recidivism among the

participants.

The majority of the 1,160 participants were male (96.9%); the mean age was 14.6 years.

A total of 73.4% of the participants were Caucasian, 12.3% were African American, and 14.3%

were classified as “other.” Several studies did not report the gender, age, and/or racial

background of the participants (see Table 3).

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Recidivism Among Juvenile Violent Offenders

The mean sample size of the studies investigating violent juvenile offenders was 95.0,

with a range of 60-155. The mean outcome period was 17.6 months, with an associated range of

14 to 24 months. The recidivism rate for violent reoffending (23.0%) was reported by only one

of the studies included in this meta-analysis. The mean recidivism rate for general recidivism

among all four studies was 34.9% (see Table 4).


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Insert Tables 4 and 5 About Here

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The majority of the 380 participants were male (61.5%), with a mean age of 15.6 years.

A total of 10.2% of the participants were Caucasian, 66.6% were African American, and 23.2%

were classified as “other.” Several studies did not report the gender, age, and/or racial

background of the participants (see Table 5).

Predictor Variables

A review of the samples resulted in the identification of nine predictor variables for

sexual recidivism and one predictor variable (intervention) for violent recidivism. These

variables were divided into three domains: offense history, family/social factors, and treatment.

Offense History. Five predictors were included in this domain: age at first sexual

offense, type of initial sexual offense (i.e., contact vs. noncontact), age of youngest victim,

relationship to victim (i.e., acquaintance or stranger), and number of prior non-sexual arrests.

Family and Social Factors. Three predictors were included in this domain: social

problems, having been a victim of physical abuse, and having been a victim of sexual abuse.

Social problems was measured in a variety of ways. The first involved the identification of

functional deficits, which included inadequate knowledge about sexual behaviors and poor social

skills (Kahn & Chambers, 1991). The second encompassed social maladjustment, as determined

by levels of peer support and participation in group activities while placed in a community-based

sexual reoffending program (Smith & Monastersky, 1986). Finally, the Social Problems


subscale of the Achenbach Youth Self-Report was used to measure social competencies and

problem behaviors (Worling & Curwen, 2000).

Intervention. There were not enough studies investigating similar treatments to divide

this domain into separate variables according to the type of treatment provided (e.g.,

multisystemic, individual, group). Thus, a composite variable – intervention – was created to

represent any studies investigating any form of treatment geared at reducing sexual reoffending

or any reoffending among violent juvenile offenders.

Procedure

Two meta-analyses, with sexual recidivism and any recidivism as the outcome variables,

were conducted using the predictor variables just described. Raw statistics from each study were

converted to correlation coefficients using formulas provided by Rosenthal (1991). These

coefficients were normalized using Fisher’s transformation formula:

Zr = ½ loge [1 + r/1-r].

The effect sizes were then used to calculate an overall weighted effect size (wtd. Zr) for

each variable:

Weighted Zr = ( wjzr)/(wj).

The mean levels of significance were calculated by converting each p-value to a normal

deviate (Z) corresponding to each, and averaging the weighted Z’s:

Weighted Z = (wjzj)/(wj2)1/2.

RESULTS


Sexual Offenders

Three of the five variables in the offense history domain were significantly related to

recidivism in sexual offenders (see Table 6). The age of the offender (Zr = -.069, p <.05) was

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negatively associated with reoffending behavior, with younger adolescents at greater risk to

reoffend. The type of the initial sexual offense (Zr = .126, p <.01) was positively associated with

recidivism. Specifically, those juveniles who committed less serious sexual offenses (e.g.,

indecent liberties, non-contact offenses), were more likely to reoffend both sexually and non-

sexually than juveniles who committed more serious offenses, such as rape. The offenders’

relationship to their victim (Zr = .184, p <.001) was significantly related to reoffending, with

those juveniles committing offenses against acquaintances being more likely to recidivate than

those who victimized either relatives or strangers. The age of the victim (Zr =-.077, p = ns) and

the perpetrators’ offense history (Zr = .083, p = ns) were the only non-significant variables in this

domain.

None of the three variables in the family/social factors domain were significantly related

to recidivism: social problems (Zr = .024, p = ns), history of sexual abuse (Zr = .063, p = ns), and

history of physical abuse (Zr = .016, p = ns). Finally, the composite variable in the intervention

domain (Zr = -.158, p<.001) was significantly negatively related to recidivism in sexual

offenders, indicating that the interventions under investigation were negatively associated with

recidivism.


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Table 7 provides a rank-ordered list of all the predictor variables according to the

magnitude of the Z scores. The offender’s relationship to his or her victim was the strongest

predictor of recidivism; juveniles who were acquainted with their victims were more like to

recidivate than juveniles who offended against strangers. The composite intervention variable

was found to be the second strongest predictor of a decrease in recidivism rates, followed by type

of initial sex offense and criminal history.

Violent Offenders

A comparison was conducted between the variables “family/cognitive therapy” and

“usual services” for violent offenders. The distribution of effect sizes was homogeneous (χ2 =

2.51, p = .47), indicating a good fit for the model (no significant differences across studies). The

average effect size for all four studies was small (r = .14, SD = .08). Group mean differences

were significant (t = 3.49, p <.05) regarding their association with recidivism. The Binomial

Effect Size Display (BESD) suggested that family/cognitive therapies (BESD = .57, or 57 %

success rate) tend to be more successful in reducing recidivism rates among juveniles than usual

services (BESD = .43, or 43 % success rate).

DISCUSSION

Violent offending among juveniles has received increasing attention from the public,

legal professionals, and social scientists over the past ten years. In particular, interest has been

on preventing violence, on predicting which juveniles are likely to reoffend, and on developing

intervention strategies that are effective in treating violent offenders. Given this concern, our


knowledge about the risk factors of reoffending and effective interventions for reducing violent

behaviors should have a strong empirical basis. One way of judging the availability and

sufficiency of relevant research is to determine whether a meta-analysis can be conducted. In

this article, we identify six important areas in which a meta-analysis would be useful for those

investigating juvenile recidivism and those working with juvenile offenders in clinical settings:

1) predictors of general recidivism, 2) predictors of sexual recidivism, 3) predictors of violent

recidivism, 4) effects of interventions on general recidivism, 5) effects of interventions on sexual

recidivism, and 6) effects of interventions on violent recidivism. Of these, only three (predictors

of general recidivism, and effects of intervention on general and violent recidivism) have been

the subject of meta-analytic review. Our original goal for this study was to conduct meta-

analyses in the remaining areas. However, because of the lack of available research – and the

limited scope of existing research – we were only able to perform a meta-analysis in one area:

predictors of sexual recidivism. Even with a slightly modified outcome variable (general

recidivism among violent offenders), our ability to identify risk factors of recidivism among

violent offenders was limited by the limited amount of research available that could be used in a

meta-analysis.

Broadly, there are at least three types of limitations that preclude conducting a meta-

analysis in the areas of juvenile sexual and violent offending. These are (a) failure to provide

basic descriptive data, (b) use of predictor variables that are limited in range and inconsistent

across studies, and (c) comparable inconsistency in defining and measuring outcome. To address

these problems and facilitate the use of meta-analysis in these areas in the future, several steps

should be taken. All studies investigating juvenile recidivism should provide certain basic data,

including rates of recidivism, a thorough and clear description of the sample (e.g., demographic


information), and descriptions of the variables investigated and the manner in which those

variables were measured. In addition, inclusion in a meta-analysis requires that studies report

some means of computing an effect size. The easiest available statistic for this purpose is the

bivariate correlation coefficient, although other statistics, such as z-scores, t-scores, F-values,

and specific p-values, can also be used. Studies that fail to provide such data for the bivariate

relationships between the predictor variable and the outcome variable cannot be included. For

example, studies that use regression analyses that only report the variance accounted for by the

combined variables or only report beta weights do not lend themselves to meta-analysis, as there

is no statistical way to determine the effect size of individual variables or to convert beta weights

into effect sizes that can be combined with those of other studies. Similarly, studies that fail to

provide statistics for (and, in some instances, even the names of) variables that were not

significantly related to the outcome variable inevitably skew the results of a meta-analysis.

Since meta-analytic studies have become more prevalent as one form of empirical literature

review, researchers should anticipate that their findings will be used in a meta-analysis and

therefore provide the necessary data for this purpose.

A second limitation in the area of juvenile recidivism in particular relates to the

impoverished range and inconsistency of the predictors that have been investigated. In our meta-

analysis investigating sexual recidivism, we identified nine variables that could be analyzed.

Only a few of these variables were used by four or more studies (see Table 8). Most surprising

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was the finding that certain variables that are very important in investigating recidivism among

juveniles (e.g., gender, school adjustment, substance abuse) had been used in so few studies that

we could not conduct a meaningful meta-analysis. Yet these variables are clearly important in

researching juvenile offending, and, from a methodological standpoint, are obtained easily.

Other variables (e.g., family circumstances, peers, leisure time use, specific personality and

behavioral features; see Hoge & Andrews, 1996) have consistently been associated with juvenile

offending. However, few studies investigate these variables, which limits the degree to which

conclusions can be drawn about the strength of their predictive validity relative to other

variables. Ultimately, a meta-analysis should be conducted that not only summarizes the effect

sizes of individual variables but also provides information about the relative predictive power of

the variables, as well as the identification of variables that act as moderators in the prediction of

recidivism among juveniles. Such analyses cannot be performed until a wider and more relevant

range of predictor variables is used more consistently by researchers.

A related issue is the inconsistency of predictors that have been employed in the study of

violent recidivism among juvenile offenders. Some studies use idiosyncratic variables, such as

level of distress and restraint, that may be helpful in developing theories of recidivism but are not

conducive to meta-analytic review. Further, even when similar predictor variables are used,

there is often a lack of consistency in how they are defined. For example, in this meta-analysis,

we included one variable – “social problems” – that was investigated by three studies (Kahn &

Chambers, 1991; Smith & Monastersky, 1986; and Worling & Curwen, 2000). Each of these

studies operationalized “social problems” differently, however, with the various definitions

incorporating elements such as social skills, knowledge about sexual behaviors, level of peer

support, participation in group activities while placed in a community-based sexual reoffending


program, social competencies, and problem behaviors). Further compounding the confusion is

the lack of consistency and clarity in measuring the construct, as in the example of "social

problems," which, in this study, included such measures as clinician ratings and the youth’s self

report. The result of such inconsistency in choosing, defining, and measuring constructs is

limited generalizability between studies, and particular problems for meta-analysis.

A third limitation in the area of juvenile recidivism relates to inconsistency in outcome.

In juvenile recidivism research, this problem arises when “reoffending” is used as the outcome

variable. As Figure 1 suggests, there are at least three broad categories of offenders that can be

investigated. First is the general population of offenders, which includes the full range of

offenses. Within this category are sexual offending, which includes non-violent, sexual

offending (e.g., exhibitionism) and violent offending, which includes a wide range of offending

behaviors that could be considered violent (e.g., murder, assault). Overlapping the two are

offending behaviors that are both violent and sexual in nature, such as rape. Currently, there

appears to be little research investigating recidivism among the group of offenders whose initial

offense was violent. Indeed, a second meta-analysis investigating violent recidivism was not

possible because we did not find any studies that specifically focused on the predictors of violent

reoffending among juveniles whose initial offense was violent. Given the upsurge of recent

interest in violent juveniles, the absence of published research in this area is both surprising and

concerning.

Regardless of the outcome used, many current studies also fail to consistently identify the

sources (e.g., official data, self-report) that were used in determining the outcome. Such

reporting problems result in inaccurate estimates of recidivism and point to the need to broaden

the number of measures of a given outcome. Studies investigating juvenile recidivism should


aim to include official data, self-report, and the reports of collateral sources, when available, as

this practice is likely to provide a more sensitive indicator of recidivism among juveniles.

Related to this is the need for research investigating outcomes other than reoffending that are

related to violence, such as adjustment to juvenile placement, and functioning within the family,

in school, and with peers.

The results of the present meta-analysis should be interpreted in the context of these

limitations. First, in the meta-analysis investigating juvenile sexual recidivism, few studies

(k=9) were included in the analysis and there were rarely more than three studies available for

each variable. In the meta-analysis investigating recidivism among violent offenders, only four

studies were included in the analysis. As noted earlier, our search of the literature identified only

nine variables that could be subjected to meta-analytic review for sexual recidivism and only one

variable for recidivism among violent offenders. Overall, the degree of confidence we can place

in the breadth and reliability of our findings is limited by a small sample size, a limited range of

predictor variables, and the probability that we did not include some studies reporting null results

(the file drawer problem).

The purpose of the present meta-analyses was to identify predictor variables that can be

associated with recidivism risk in juvenile sexual and violent, non-sexual offenders. In this

context, we use the term “predictor variables” in a methodological sense. It should not imply

that variables found to be significant can consistently predict which juvenile delinquents will

reoffend – only that they are empirically related to the likelihood of reoffense.

Results of the present meta-analysis with juvenile sexual offenders suggest that the

variable most strongly associated with recidivism risk is the offender’s relationship to the victim.


Juveniles whose victim was an acquaintance were more likely to reoffend than those whose

victim was a stranger. In addition, the composite intervention variable was also significantly

related to risk of reoffending; juveniles who undergo clinical interventions as part of their

sentences were at significantly lower risk for reoffending sexually when compared with juveniles

who are involved in standard services only (i.e., probation or incarceration). Taken together,

These findings underscore the importance of targeting juveniles’ interpersonal skills and

relationships for both prevention and intervention efforts. They may also provide modest

support for the use of specialized programs for juvenile sexual offenders, although firmer

evidence on this issue will await the conducting of a meta-analysis on intervention impact with

this population (Cell V in Table 1).

Additional variables associated with recidivism risk among juvenile sexual offenders

include those related to offense history. The type of initial offense was significantly related to

recidivism, with those charged with less serious (non-contact) sexual offenses being more likely

to reoffend sexually. In addition, age was inversely related to reoffense risk, with younger

juveniles at higher risk for reoffending. Other offense history variables were also significantly

associated with recidivism risk, while variables in the family/social factors domain did not

demonstrate a significant relationship with recidivism risk. It is likely, however, that this finding

is an artifact of the inconsistent and infrequent way in which family and social variables were

used in these studies. Indeed, the earlier-noted finding that juveniles who offended within the

family are at higher risk for reoffense strongly suggests that certain family variables (e.g.,

physical or sexual abuse histories, level of parental supervision) are relevant and likely to show

effects, if measured reliably (Henggeler et al., 1997; Henggeler, 1999).


In the second meta-analysis, the composite intervention variable was the only one that

could be examined for juvenile violent, non-sexual offenders. The studies included in the

analysis reviewed various non-clinical interventions (e.g., probation) with clinical interventions

that can be categorized as family treatments and/or cognitive therapies. Results reveal this

variable to be strongly associated with recidivism risk. Specifically, interventions incorporating

individual and family treatments were found to decrease reoffending behavior in violent

juveniles, compared to standard, non-clinical interventions. This offers some support for the use

of treatment in addition to standard tools such as probation and parole to reduce recidivism rates

among violent juvenile offenders. This is consistent with recent research efforts to determine the

effectiveness of specialized treatment programs (e.g., multisystemic therapy) among juvenile

offenders (see, e.g., Henggeler, 1999; Borduin, 1999; Tate, Reppucci, & Mulvey, 1995 for a

review of such treatment programs and how they might help to inform various policy questions

in the juvenile justice system).

Several steps are needed to help rectify the limitations of the research in the areas of

sexual and violent juvenile recidivism. First, this review highlights the need for additional

research in the areas of predicting juvenile sexual recidivism and violent recidivism, and in

investigating the effects of interventions on sexual recidivism. Second, it clearly underscores the

need for improvement in defining and measuring relevant variables. For risk factors, this can be

accomplished by having investigators carefully consider the selection and operationalization of

relevant variables, and explicitly articulating the rationale for such a selection. This would allow

other researchers to use a similar method and ultimately, would allow for a more meaningful

summary of the literature in the form of a meta-analysis. The use of structured risk/needs

assessment tools for adolescents, such as the Youth Level of Service/Case Management


Inventory (Hoge & Andrews, 1994), is useful in addressing these problems, as the application of

such a tool involves preselected relevant variables that have been operationalized in a standard

fashion.

For outcome variables as well, researchers should aim to use a comparable index of

offenses, similar to provided by the FBI (see Appendix A). The enhanced standardization and

cross-investigational consistency that could be achieved by greater attention to both predictive

and outcome variables could provide a valuable basis for applying meta-analysis to studies

across various jurisdictions and juvenile populations. Unfortunately, however, as the present

study demonstrates, the current state of the research literature provides only limited opportunity

to apply the tool of meta-analysis to considering broad trends in empirical findings on the

prediction of juvenile offending.


Footnote

1. The age in most jurisdictions at which an individual is eligible for the juvenile system is 11 or

12. Some of the studies we reviewed, and eventually used, considered children as young as 7

years old. While most of the participants in these studies were within the conventional juvenile

age range of 11-21, we had no way of removing the data on younger juveniles without

significantly reducing the number of studies included, and thus variables analyzed, in the meta-

analysis.


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Table 1

Meta-Analytic Research on Juvenile Recidivism: Prediction versus Intervention Impact,

and Different Outcomes

I

Predictors of General Recidivism

(Cottle et al., 2001)

II

Predictors of Sexual Recidivism

(Present study)

III

Predictors of Violent Recidivism

(Present study)

IV

Effects of Interventions on General Recidivism

(Lipsey, 1992)

V

Effects of Interventions on Sexual Recidivism

(Not yet possible*)

VI

Effects of Interventions on Violent Recidivism

(Lipsey & Wilson, 1998)

* A review of the literature yielded an insufficient number of empirical treatment outcome studies to conduct a meta-analysis. Only three such studies were located: Borduin et al., 1990; Kahn & Chambers, 1991; Worling & Curwen, 2000)


Table 2

Characteristics of Studies (N = 9) Included in Meta-Analysis of Juvenile Sexual Offenders_____________________________________________________________________________Variable M SD Range k_____________________________________________________________________________

Sample size 128.9 59.9 16 - 221 9

Follow-up (months) 54.2 23.1 24 - 228 9

Recidivisma base rates (%)

Sexual Offending 14.3 13.1 0.6 - 44.0 9

Nonsexual Offending 41.0 9.4 35.0 - 54.0 6b

Any Offending 48.7 19.7 19.0 – 78.6 6c

_____________________________________________________________________________Note. k= number of unique samplesa This variable incorporates three definitions of recidivism: Rearrest, reconviction, reincarceration. To the extent that rearrest is the most sensitive indicator of reoffending, this merged “recidivism” variable is likely to underestimate participants’ reoffending. However, to the extent that reincarceration is the most specific indicator of participants’ reoffending, the merged variable may overestimate the number of participants who are overcharged or inaccurately charged with future offenses.b N=663; Three studies failed to report nonsexual recidivism rates: Dolan et al. (1996), Kahn & Chambers (1991), and Lab et al. (1993).c N=866; Three studies failed to report recidivism rates for any crime: Borduin et al. (1990); Dolan et al. (1996); and Smith & Monastersky (1986).


Table 3

Age, Race, and Gender of Participants Included in Meta-Analysis (Sexual Juvenile Offenders,

N=1,160)_____________________________________________________________________________Variable M SD Range k_____________________________________________________________________________

Age (years) 14.6 0.6 7-20 8a,b

Race (%) 5c

Caucasian 73.4

African American 12.3

Otherd 14.3

Gender (%) 9

Male 96.9

Female 3.0_____________________________________________________________________________Note. k = number of unique samplesa N=1060; One study failed to report a mean age: Hagan & Cho (1996).b Two studies failed to report an age range: Borduin, et al. (1990) and Lab et al. (1993).c N=683; Four studies failed to report racial breakdown of the samples: Hagan & Cho (1996); Langstrom (in press); Smith & Monastersky (1986); and Worling & Curwen (2000).d Includes Hispanic, Native American, Asian American, and minority participants not further specified.

Table 4


Characteristics of Studies (N = 4) Included in Meta-Analysis of Juvenile Violent Offenders_____________________________________________________________________________Variable M SD Range k_____________________________________________________________________________

Sample size 95.0 41.4 60 – 155 4

Follow-up (months) 17.6 5.6 14 – 24 4

Recidivism base rates (%)

Violent Offending 23.0 1a

Any Offending 34.9 13.59 26.00 – 51.19 4

_____________________________________________________________________________Note. k= number of unique samplesa Three studies failed to report recidivism rates for violent reoffending: Henggeler, et al. (1997); Henggeler, et al. (1992); and Myers, et al. (2000).

Table 5


Age, Race, and Gender of Participants Included in Meta-Analysis (Violent Juvenile Offenders,

N=380)_____________________________________________________________________________Variable M SD Range k_____________________________________________________________________________

Age (years) 15.6 1.0 14.9 – 17.0 4

Race (%)

Caucasian 10.2 4

African American 66.6 3a

Other 23.2 3b

Gender (%) 4

Male 61.5

Female 38.5_____________________________________________________________________________Note. k = number of unique samplesa One study failed to report a percentage for African American participants: Guerra & Slaby (1990).b One study failed to report a percentage for participants of other racial backgrounds: Guerra & Slaby (1990).


Table 6

Predictors of Juvenile Sexual Recidivism (N=1,160)_____________________________________________________________________________Variable Zr N k Studies_____________________________________________________________________________

Offense History

Age of Offender -.069* 572 5 Kahn & Chambers (1991); Langstrom (in press); Rasmussen (1999); Smith & Monastersky (1986); Worling & Curwen (2000)

Type of Initial .126** 398 4 Dolan et al. (1996); Hagan & Cho (1996);Sex Offense Langstrom (in press); Smith & Monastersky

(1986)

Relationship to .184*** 391 4 Langstrom (in press) Rasmussen (1999); Victim Smith & Monastersky (1986); Worling &

Curwen (2000)

Age of Victim -.077 272 3 Rasmussen (1999); Smith & Monastersky (1986); Worling & Curwen (2000)

Criminal History .083 389 4 Rasmussen (1999); Langstrom (in press) Smith & Monastersky (1986); Worling & Curwen (2000)

Family/Social Factors

Social Problems .024 455 3 Kahn & Chambers (1991); Smith & Monastersky (1986); Worling & Curwen(2000)

History of Sexual .063 514 5 Dolan et al. (1996); Kahn & Chambers Abuse (1991); Rasmussen (1999); Smith &

Monastersky (1986); Worling & Curwen (2000)

History of Physical .016 385 4 Dolan et al. (1996); Kahn & ChambersAbuse (1991); Rasmussen (1999);

Worling & Curwen (2000)

Intervention

Intervention -.158*** 535 5 Borduin et al. (1990); Kahn & Chambers (1991); Lab et al. (1993); Rasmussen

(1999); Worling & Curwen (2000)_____________________________________________________________________________Note. Zr = weighted mean effect size; k = number of unique samples.


*p<.05 **p<.01 ***p<.001


Table 7

Predictors of Juvenile Sexual Recidivism (N=1,160) by Predictive Strength_____________________________________________________________________________Variable Zr N k Studies_____________________________________________________________________________

Relationship to .184*** 391 4 Langstrom (in press); Rasmussen (1999); Victim Smith & Monastersky (1986); Worling &

Curwen (2000)

Intervention -.158*** 535 5 Borduin et al. (1990); Kahn & Chambers (1991); Lab et al. (1993); Rasmussen (1999); Worling & Curwen (2000)

Type of Initial .126** 398 4 Dolan et al. (1996); Hagan & Cho (1996);Sex Offense Langstrom (in press); Smith & Monastersky

(1986)

Criminal History .083 389 4 Langstrom (in press); Rasmussen (1999); Smith & Monastersky (1986);


Age of Victim -.077 272 3 Rasmussen (1999); Smith & Monastersky(1986); Worling & Curwen (2000)

Age of Offender -.069* 572 5 Kahn & Chambers (1991); Langstrom (in press); Rasmussen (1999); Smith & Monastersky (1986); Worling &

Curwen (2000)

History of Sexual .063 514 5 Dolan et al. (1996); Kahn & ChambersAbuse (1991); Rasmussen (1999); Smith &

Monastersky (1986); Worling & Curwen (2000)

Social Problems .024 455 3 Kahn & Chambers (1991); Smith & Monastersky (1986); Worling & Curwen(2000)

History of Physical .016 385 4 Dolan et al. (1996); Kahn & ChambersAbuse (1991); Rasmussen (1999);


______________________________________________________________________________Note. Zr = weighted mean effect size; k = number of unique samples.*p<.05 **p<.01 ***p<.001


Table 8

Variables Identified Among Studies Investigating Sexual Recidivism in Juvenile Offenders________________________________________________________________________________________

Variables Identified k Variables Identified k________________________________________________________________________________________

Demographic Variables Behavioral and Substance Abuse Problems

Gender 1 Psychopathy 2Socioeconomic Status 1 Delinquent Behavior 1Race 1 Aggressive Behavior 2

Substance Abuse History 2

Family Factors Offense History

Poor Family Atmosphere 1 Age at first arrest 5Parental Rejection 1 Criminal History 4Number of Siblings 1 Age of Victim 3Divorce of Parent 1 Relationship to Victim 4Loss of Parent 1 Same Sex Victim 1History of Abuse of Sibling 1 Sex of Victim 2

Number of Victims 2Social Factors Type of Sex Offense 4

Use of Verbal Threats 1History of Sexual Abuse 5 Offender-Age Difference 1History of Physical Abuse 4Social Problems 3 Variables Specific to Sexual Offending

Academic and School History Attitudes About Sex 2Deviant Arousal 1

School Behavior Problems 1 Level of Insight 2History of Truancy 1 Ability to Identify Strengths 1

Psychological Factors Intervention

Thought Disorder 1 Treatment 5Depression 2 Location of Treatment 1Self-Criticism 1 Empathy for Victim 2Self-Esteem 1 Motivation for Change 2History of Self-harm behaviors 1 Blames Victim 1History of Soiling 1 Denial 2

Therapist Assessment of Risk 2Length of Treatment 1

_____________________________________________________________________________________Note. k = Number of studies.


Appendix A

Criminal Offenses, as Defined by the Federal Bureau of Investigation ___________________________________________________________________________________________

Offense Definition___________________________________________________________________________________________

Criminal Homicide The willful killing of one human being by another.

Forcible Rape The carnal knowledge of a female forcibly and against her will.

Robbery The taking or attempting to take anything of value from the care, custody, or control of a person by force or threat of force or violence and/or by putting the victim in fear.

Aggravated Assault An unlawful attack by one person upon another for the purpose of inflicting severe or aggravated bodily injury.

Burglary The unlawful entry of a structure to commit a felony or a theft.

Larceny-theft The unlawful taking, carrying, leading, or riding away of property from the possession or constructive possession of another.

Motor vehicle theft The theft or attempted theft of a motor vehicle.

Arson Any willful or malicious burning or attempt to burn.

Simple Assault Assaults and attempted assaults where no weapons are used and which do not result in serious or aggravated injury to the victim.

Forgery Making, altering, uttering, or possessing, with intent to defraud, anything false in the semblance of that which is true.

Possessing Stolen Property Buying, receiving, and possessing stolen property.

Vandalism Willful or malicious destruction, injury, disfigurement, or defacement of any public or private property, without consent of the owner.

Weapons All violations of regulations controlling the carrying, using, possessing, furnishing, and manufacturing of deadly weapons or silencers.

Sex offenses Statutory rape and offenses against common decency and morals.

Drug abuse violations Unlawful possession, sale, use, growing, and manufacturing of narcotics.

Runaways Limited to juveniles (under 18) taken into protective custody under provisions of local statutes.

______________________________________________________________________________


Note. Obtained from FBI, http://www.fbi.gov/ucr/ucr.htm, April 21, 2001.

http://www.fbi.gov/ucr/ucr.htm


Figure 1

Meta-Analytic Research on Juvenile Recidivism: Population Defined by Offense Type

Documents

The Prediction of Criminal Recidivism in Juveniles: A Meta-Analysis