Juvenile Correctional Facilities: Impact on Recidivism (an evidence-based practice brief)

Do juvenile correctional facilities reduce recidivism among juvenile offenders? The goal of this brief is to answer this question. Gaining a deeper understanding of the juvenile delinquent youth population, by compiling current and relevant research, that is both strong in method and measurement, is valuable so professionals in the field can offer these adolescents the best possible outcome. As a social worker in training and volunteer at a juvenile boot camp, witnessing youth’s travel in and out of the residential, six-month program is quite common. Why is that so? What contributes to re-offense after placement in residential programs and furthermore, why are youths committing crimes in the first place? Many of the youths involved in the juvenile justice system come from low-income backgrounds with few to limited resources, have violent pasts, struggle with mental illness, or have had previous physical and sexual abuse. To refer to this population as underserved is an understatement, because these youths are ignored. It is the goal of this brief to address the most popular intervention treatment technique—residential juvenile placement, to assess whether it contributes to juvenile recidivism rates (rise in criminal behavior).

The period of adolescent development is difficult for any teenager, regardless of their upbringing. Authors Leverso, Bielby, and Hoelter conducted a study that examines juvenile recidivism and supports a general existing theory on juvenile crime. A trait found common across all juvenile delinquents is an inability to control their impulses (Leverso, Bielby, & Hoelter, 2015). Youths who engage in criminal behaviors generally do so when they believe the risk (of getting caught) to be minimal, and social validation among peers can be gained. Together, all these factors combined, contribute to a troubled adolescence often resulting in criminal activities that push this population into residential placement facilities across America.

Beginning the search with Census data for juveniles in residential placement highlights important population and demographic data, including age, sex, race and ethnicity for national statistics. According to the Office of Juvenile Justice and Delinquency Prevention (OJJDP), in 2013, just over fifty four thousand youths were either committed or detained in juvenile placement facilities in the nation (Puzzanchera, Sladky, Kang, & Sickmund, 2015). Race and ethnicity profiles in juvenile placement included a majority of African American’s representing just over twenty one thousand five hundred, Caucasians representing seventeen thousand five hundred, Hispanic/Latino’s representing twelve thousand, and the remainder was a mixture of Asian American and Native American (Puzzanchera, Sladky, Kang, & Sickmund, 2015). Ages ranged from under twelve (the lowest number of juveniles), to over eighteen (the highest number of juveniles) years old and gender was the most revealing statistic with roughly forty six thousand males and seven thousand females (Puzzanchera, Sladky, Kang, & Sickmund, 2015).

Juvenile offenders who enter the juvenile justice system are placed in different facilities. Having a basic understanding of the terminology is important when examining the data available. According to the OJJDP, a ‘Detention Center’ is a restrictive facility where youths are detained for a short period of time. Here juvenile offenders are either waiting to have a case heard and decided by a judge or awaiting transfer to another fmore permanent facility. A ‘Residential Treatment Center’ is considered a lock down facility similar to the Detention Center, only it is long-term, where offenders receive individualized treatment plans specific to substance abuse crimes, mental health issues, and sexual offenses. In the state of California, during the year of 2013 eleven thousand, seven hundred juveniles were sentenced to Residential Treatment (Puzzanchera, Sladky, Kang, & Sickmund, 2015). The ‘Long-Term Secure Facility’ is similar to adult prisons, with strict confinement protocol, commonly known as juvenile correctional facilities. In 2013, California placed over twelve thousand, nine hundred juvenile offenders in these types of facilities (Puzzanchera, Sladky, Kang, & Sickmund, 2015).

Part II: Evidence Search

Gaining some knowledge of this population through existing census data combined with a basic understanding of the terminology of juvenile placement provided a necessary foundation for a data search, which proceeded. To address a rise in crime, one must examine factors that cause recidivism, before concluding that placement facilities contribute to a rise in crime among youth offenders. Thus, the two databases that provided the most useful, current, and relevant data were ProQuest and Violence and Abuse Abstracts (hosted by EBSCO).

Beginning with ProQuest, using the advanced search option with keywords “juvenile offenders,” across all one hundred and thirty two databases, with limiters that only included document types that comprised of statistical and data reports, case studies, government and official documents, and literature reviews. The source type selected was scholarly, peer-reviewed journals, the time period included documents published after 2010, and documents published in English. The search yielded twenty-eight results. A discovery of a meta-analysis examining the effect of youth diversion programs as a replacement for traditional juvenile correctional facilities provided useful. This highlighted a successful alternative to an aging model (traditional juvenile correctional “prison type” units) that may be contributing to the rise in arrests among youth. In the same search, a systematic review on the effects of juvenile boot camps added relevant background that is important to the researcher who chose this topic. Both studies are considered ‘experimental’ and therefore ranked in the higher levels of the research hierarchy.

The Violence and Abuse Abstracts database seemed to elicit more results with similar keywords. The first step was choosing Advanced Search and using similar keywords including, “juvenile,” “residential,” “violence,” to narrow the search further. Selecting ‘SmartText Search’ uses the most relevant terms to search the data available, usually when researchers have multiple keywords, or long sentences. Limiters are also known as source type and publication type, so in this database Academic and Scholarly (peer-reviewed) journals, and a separate box was checked for references available, to limit the results and narrow down the search. Further limiters included publications dated after 2010. Using the first set of keywords yielded six thousand, seven hundred fifteen results. In particular, one article examines gender differences on recidivism as well as other factors through a pre-experimental design using non-probability sampling. This would place the study on the lower levels of the research hierarchy, however it was beneficial to examine predictors of one single group because most of the relevant available data was a collection of reports (meta-analysis, systematic reviews).

Juvenile correctional facilities as an intervention is considered common practice in the juvenile justice system in the USA, therefore when searching for effectiveness of treatment or the intervention itself, ‘juvenile detention’ was never the search term to effectively describe the actual intervention. It was found after awhile that the correct terms to describe these types of facilities was “residential placement” or “juvenile placement.” When using the keywords chosen for the search, all kinds of interventions were littered in the results that contained various types of ways to reduce criminal behavior in delinquent youth, but many did not address the residential facility itself. It was difficult to narrow down facilities because they are broad and include a multitude of intervention options, especially for youths with mental illness, substance abuse and traumatic backgrounds. Juvenile facilities could be a residential, boot camp, prison type lock down, or a residential treatment and therefore it was difficult to narrow down the search and examine juvenile corrections as a whole because there are too many types of facilities.

In order to examine the rise in crime, one must begin the search by looking at contributing factors and each facility has different goals, addresses different crimes, and produces different results. Therefore, to answer the practice question one must go outside the juvenile facility and study the histories and case files of each juvenile offender. Each article presented in the search results addressed different aspects of this population. Some were sex offenders, others had substance abuse issues, and a majority struggled with mental illness. In addition, it is important to factor in normal biological and cognitive developments each adolescent passes through, before transitioning to early adulthood, because even though these youths are considered criminals, they are still children. The largest limitation of the search initially, was that the researcher only had a basic knowledge of the juvenile population and the problem of recidivism. The object of this brief is to provide enough background on this population, address the recidivism problem among juvenile youth, and provide reasoning for that cause.

Part III: Critical Appraisal of the Evidence

The first study entitled, “The Effect of Youth Diversion Programs on Recidivism,” examined the benefits of youth diversion programs to reduce criminal behaviors in youth offenders. Authors Wilson and Hoge argue that a rise in recidivism among juveniles in traditional correctional facilities can be explained by two theories, labeling theory and social learning theory. The “delinquent” label and stigma that comes from placement in traditional correctional facilities and can contribute to negative consequences both developmentally and legally for youths (Wilson & Hoge, 2013). Once a juvenile is processed through the juvenile court system and sentenced to a long-term care facility, the youth is labeled as a “juvenile delinquent.” In addition, once a youth is living around other, more violent peers, adopting similar behaviors is quite common, explaining social learning theory (Wilson & Hoge, 2013). Thus, a diversion program for less violent offenders is beneficial to reduce recidivism, and labels resulting in negative stigma. The authors also presented a key argument supported by empirical research from multiple authors, suggesting that recidivism is more common the longer a youth remains in traditional correctional facilities (Wilson & Hoge, 2013). Therefore, supporting the development of other treatment alternatives like diversion programs was analyzed to see if recidivism was reduced in youths in this meta-analysis study.

To be included in this meta-analysis, authors only used studies that examined recidivism rates when compared to interventions that used diversion programs or the traditional juvenile correctional residential model. Authors examined seventy three diversion programs in total, which diverted over fourteen thousand youths, along with studies that processed over eighteen thousand youths through the traditional juvenile justice correctional system. Recidivism was measured after youths completed programs in either diversion or correctional facilities, and the most valid and reliable studies reflected posttests after twelve months or longer. Each study contained a comparison group, but not all of them were considered to be strong in terms of sampling selection and timing of posttests. The authors primarily coded two groups in the research design to represent the target sample, which included medium and low risk offenders who would benefit most from diversion programs, while more serious offenders were excluded.

Diversion programs are defined as any program that provided an alternative to incarceration, or diverted youths from any official screening toward processing an official charge. Studies were coded by the quality strength of each study on a scale represented by three choices, successful, somewhat successful and not successful (Wilson & Hoge, 2013). The most successful studies had the highest reliability (tested by Interrater reliability) and strength of design (timing of posttest—after twelve months). The most successful studies used random sampling, multiple groups, a comparison group, and had the strongest internal validity. Authors used a separate coding system to organize all studies in the meta-analysis on three principles including, risk, need and responsivity, as well as fifty-two additional variables (i.e. gender, location, offense). However, not all studies met all three principle qualities and coding was necessary to organize each variable accordingly (Wilson, & Hoge, 2013).

The main difference between diversion and traditional correctional placement is the focus on individualized treatment plans and additional services the diversion programs provide to youth offenders. After youths received the diversion intervention, and there was additional follow up of posttests (after twelve months) the average rate of recidivism was calculated at 31.5% (Wilson, & Hoge, 2013). Compared to youths receiving the traditional juvenile correctional treatment without additional crime prevention services and individualized treatment plans, the rate was slightly higher. Recidivism rates for juveniles processed through the traditional route, given the correctional placement intervention, followed up with same number of posttests (after twelve months), resulted in an average of 41.3% (Wilson, & Hoge, 2013).

To measure reliability of this meta-analysis, researchers used Interrater reliability to measure the effectiveness of diversion treatment across forty-three studies, measuring seventy-three different diversion programs. According to authors Wilson and Hoge, the kappa scores ranged from .87 to 1.0, with a median of .98, indicating high reliability. The lowest score was .54, which was coded as a separate type of treatment entirely, similar to counseling therapy (Wilson, & Hoge, 2013). The odds ratio was used to measure each programs effectiveness with values from 0-.999 reflecting the diversion intervention as effective, and values 1.00 to infinity reflected the juvenile correctional path (comparison group) as effective in reducing recidivism (Wilson, & Hoge, 2013). Different studies had diverse sample sizes, and this was also factored in when calculating the odds ratio. Authors also included ‘random effects,’ which is a generalization of results explained through weighted averages and calculated by variability within studies (Wilson & Hoge, 2013). Because of the multiple studies used in this analysis and the various sample sizes, the study results of the meta-analysis are not generalizable and do not represent the population of juvenile offenders who reoffend. However, the study is beneficial in providing relevant support for the argument that recidivism can be reduced if juvenile offenders are sent to diversion programs instead of traditional correctional facilities.

The second study was a systematic review that examined the effects of juvenile boot camps, which are an option for placement. Authors Meade and Steiner address the popularity, cost of such facilities and discuss attitudes of juveniles inside placement, and the effects on recidivism (Meade & Steiner, 2010). This study was a collection of all available evidence on various studies performed in forty-five different boot camps. To organize the data, researchers classified each study into three groups, which included juvenile attitudes and behaviors developed as a result of the intervention (boot camp), effects of recidivism (what happened after release), and availability of bed space (Meade & Steiner, 2010). Each study was rated on a scale of one to five depending on its strength of measurement. For example, if researchers found the study to be a five, it was the most rigorous study using random sampling and a comparison group, also known as an experimental design. A score of one would represent no comparison between two groups receiving treatment, a pre-experimental form of research design. A majority of the studies were classified as three, which meant that researchers controlled elements that affected how the comparison group differed from the treatment group. Even though this systematic review provided relevant support to the practice question, it did not however go into detail about reliability measurement techniques.

For the purpose of this brief, the most important part of this research was the effects on recidivism and if the boot camps had any effects on that for juvenile youths. To assess this, youths who were receiving the intervention were compared to a similar group of juvenile offenders not receiving the treatment. According to authors Meade and Steiner, when evaluating recidivism in boot camps the results showed that these facilities have little affect on recidivism among juvenile delinquents (Meade & Steiner, 2010). The study seemed to focus more on benefits of boot camps to alleviate high costs from over populating long-term facilities. Boot camps also had a positive effect on the attitudes of juvenile offenders, compared to attitudes of those in alternative correctional units, which translated into positive behaviors. However, when examining recidivism it had no effect. That is why the researchers evaluated each qualifier (attitudes and behaviors, bed space/cost, and recidivism) separately.

Given the knowledge that is available in this systematic review, addressing recidivism among juvenile youth was hardly addressed in this study. This is beneficial because the intervention had little or no effect. Concluding that juveniles can be placed here and the possibility of committing crimes, after release, is low. Further studies should be done on this because the intervention did not contribute to the rise or reduction of recidivism.

The final study reviewed was a pre-experimental design that used a form of non-probability sampling. Its research design used one group with a pre-test and posttest design. Its goal was to examine recidivism factors among youth placed in out-of-home treatment programs, which ranged from group homes (low security) to long-term correctional units (high security) in Kentucky. In this study, authors Minor, Wells, and Angel reviewed one sample, which consisted of a sample frame of two thousand youth’s released from out-of-home placements over a two-year period, during 2000-2001, across multiple treatment programs (Minor, Wells, & Angel, 2008).

Case files from the state of Kentucky were provided to select participants and every fourth male was randomly selected, and females were randomly selected, so enough could be representative of the population (Minor, Wells, & Angel, 2008). In total, five hundred and eighty participants were randomly chosen, ranging in ages from twelve to eighteen, 70.3% of the sample youths were White, and 80.5% were male (Minor, Wells, & Angel, 2008). Much of the history on each individual’s case relied on personal integrity of self-reports given by participants and administered by clinicians. Recidivism was measured within eighteen months of release from placement, if the juvenile was charged with a Class A misdemeanor or felony (Minor, Wells, & Angel, 2008).

This study assessed thirty-three different predictors of recidivism, and authors concluded that four in particular played a significant role in reconvictions. These included age (twelve to eighteen years in study), gender, mental health needs (special education), and victimization history of neglect or abandonment (Minor, Wells, & Angel, 2008). Each of these four factors predicted future crime and was also in line with current available research, when compared to other juveniles reoffending outside of this studies’ sample.

Results showed that 52% of the studies sample reoffended post release in the eighteen-month period (Minor, Wells, & Angel, 2008). In addition, it was found that males were two times more likely to reoffend than females post release and males were 1.3 times more likely to reoffend each year they progressed in age, from twelve to eighteen (Minor, Wells, & Angel, 2008). Females were more likely to reoffend if they were first time offenders, than those with previous placement and a criminal history (Minor, Wells, & Angel, 2008). Looking deeper into the self-reporting interview data, a majority of juveniles had histories of sexual trauma, and authors believed those who presented such a background were less likely to reoffend. In contrast, maltreatment, neglect, and abandonment, were all considered to be predictors that males shared and contributed to recidivism post release.

It was not clear whether or not each type of placement facility contributed to recidivism rates. Instead, other factors present in each youth’s history seemed to point to prediction of future crime. This study examined contributing factors for recidivism in males, but does not address the female gender in as much detail. The female sample size selected is a contributing factor to the limited results. It does not examine programs within the juvenile units themselves, which may affect criminal behaviors among youths after release. Instead, the study focuses on self-reporting data to determine its results. There are many threats to internal validity here, which make the data unreliable, however it is still beneficial to gain an understanding of predictors, which are present among this age group. The data is not generalizable for the population group concerned in this research brief due to the multiple threats present and the pre-experimental design of the study. Thus, the strength of the evidence is low, but it does provide an insight into causes that can predict recidivism. Further research is required to address whether these four predictors contribute to re-offense.

Part IV: Translating the Evidence Into Practice

Overall, after analyzing all of the literature collected for this research brief, it was discovered that more data was available on the predictors and causes of recidivism, instead of whether or not juvenile institutions reduce crime among youth. It is important for the agency to look at this population (juvenile offenders) as a group of young children who are easily swayed by their peers, but also learn behaviors just as naturally as any normal developing adolescent. However, one key trait all juvenile offenders share is an inability to control their impulses (Leverso, Bielby, & Hoelter, 2015). Social learning theory explains that juveniles will learn to handle situations with negative behaviors through watching some of their more violent peers in long-term (high security) facilities. Each study looked at different aspects of juvenile justice placement, in an effort to provide professionals of the agency with the most relevant data available on this recidivism problem.

Recidivism is not an easy topic to dissect. As an agency looking to understand recidivism among this population and to provide equal opportunity both in terms of quality and continuum of care, the next course of action is further research. The evidence selected for this brief had some limitations. Even though the evidence did answer the practice question, it was not clear how recidivism was reduced, or which diversion programs were more successful than others. Boot camps had no effect on recidivism, but provided no further details on which factors contributed to that. It is shown through the studies selected that recidivism is reduced or unaffected, depending on placement and it can be reduced when personal case files of juvenile offenders were reviewed in the pre-experimental design. Further action is required to gain a deeper understanding as to how a reduction of recidivism is possible if the agency is to improve the quality of care for this population.

To overcome these limitations the agency will need to further research the topic into more detail. First, it would be beneficial to use an established scoring system to evaluate additional services provided by juvenile residential placement facilities, to understand which services provide the strongest results in reducing recidivism. For example, in the meta-analysis study recidivism was reduced when juveniles were placed in diversion programs. Why is that so? Which services contributed to a reduction in recidivism, post release? The meta-analysis study did not address particular services offered, so it is suggested for the agency to evaluate those services with an established scoring scale to determine if that affected recidivism. Furthermore, which treatment therapies (if any), classes provided, disciplinary tools, or extracurricular options were youths given? Questions like these need to be answered if the agency and professionals in the field are to attain any additional information on how recidivism was reduced within each juvenile facility.

Since, the evidence in this brief suggests that recidivism can be affected by the placement of juvenile offenders in alternative facilities, different from traditional long-term correctional units, one barrier to further research is additional limitations and further confusion. Initially, as the researcher began this search it was apparent that this topic and population is both technical and delicate; terms, programs, and facilities can often become confusing. It is important to be focused and clear with the goal for the research. Assuming the agency agrees to proceed with analyzing successful placement programs, similar to diversion programs or boot camps, it will be beneficial to start the search with the first meta-analysis presented in this brief. Authors Wilson and Hoge reviewed seventy-three current diversion programs and the score used to measure each program (rating from one to five), was decided and used based on each independent studies’ rigorous methodological practices. Each program will provide the name of institution and study authors. This will be a successful starting point for the agency and overcome any initial confusion or limitations.

References

Leverso, J., Bielby, W., & Hoelter, L. (2015). Back on the streets: Maturation and risk factors for recidivism among serious juvenile offenders. Journal Of Adolescence, 41, 74-76. http://dx.doi.org/10.1016/j.adolescence.2015.02.008

Meade, B., & Steiner, B. (2010). The total effects of boot camps that house juveniles: A systematic review of the evidence. Journal Of Criminal Justice, 38(5), 841-853. http://dx.doi.org/10.1016/j.jcrimjus.2010.06.007

Minor, K., Wells, J., & Angel, E. (2008). Recidivism Among Juvenile Offenders Following Release from Residential Placements: Multivariate Predictors and Gender Differences. Journal Of Offender Rehabilitation, 46(3-4), 171-188. http://dx.doi.org/10.1080/10509670802143474

Puzzanchera, C., Sladky, T., Kang, W., & Sickmund, M. (2015). Easy Access to Juvenile Populations in Residential Placement. Ojjdp.gov. Retrieved 10 April 2017, from https://www.ojjdp.gov/ojstatbb/ezacjrp/asp/Age_Sex_Race.asp

Wilson, H., & Hoge, R. (2013). The Effect of Youth Diversion Programs on Recidivism. Criminal Justice And Behavior, 40(5), 497-518. http://dx.doi.org/10.1177/0093854812451089

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