Factors Influencing Recidivism Among Juvenile Offenders

Introduction

The American Civil Liberties Union reports that nearly 60,000 youth under the age of 18 are incarcerated in the United States every day. What is even more troubling, however, is the number of juveniles who re-offend and are re-incarcerated within five years of their release. It is estimated that approximately 44% of offenders are rearrested within the first year of their release, with juveniles making up 55% of these rearrests (Alper, Durose & Markman, 2018). The high recidivism rates of juvenile offenders highlight the need to bring greater awareness to this issue.

Studies have already shown that incarceration dramatically impacts juveniles' futures by interrupting their social systems — including friendships and church involvement — and disrupting their opportunities to receive an education (Chetty & Hendren, 2017; Mallett, 2013). At the macro-level, incarceration also burdens the economy. Mukku and colleagues (2012) found that averting incarceration could reduce government expenses by $17 billion annually, primarily for non-violent-related crimes. For these reasons, this study reinforces the need to educate the public about the factors that lead to incarceration and, by extension, recidivism among juvenile offenders.

Recidivism presents a unique challenge for administrators and policymakers in the criminal justice system. Very high recidivism rates signify the system's inability to adequately rehabilitate and reintegrate offenders into their communities. National recidivism rates in the United States remain significantly high. Bureau of Justice Statistics (BJS) data released in 2018 showed that 5 in 6 (representing 83%) of offenders released in 2005 across 30 states had been re-arrested at least once between then and 2014 (Alper et al., 2018). Approximately 44% of offenders are rearrested before the end of their first year after release (Alper et al., 2018).

According to the Office of Juvenile Justice and Delinquency Prevention (OJJDP), juveniles make up approximately 55% of offenders who are rearrested within their first year of release (OJJDP, 2017). National data on juvenile recidivism does not exist, as juvenile justice is handled at the state level. State data, however, points to a worrying trend. A 2018 report from the State of Indiana puts juvenile recidivism at a rate of 33.3% for offenders released in 2015 (Indiana Department of Correction [IDOC], 2018). Of the 688 juveniles released in 2015, 229 had been rearrested at least once by 2017 — 145 as juveniles and 84 as adults (IDOC, 2018). Similarly, 2015 data from California indicates a juvenile recidivism rate of 50.5% in 2014–15, up from 49.1% in 2013–14 (California Department of Corrections and Rehabilitation [CDCR], 2015). The highest juvenile recidivism rates have been reported in New Jersey, where 2010–11 data indicates that 81% of juvenile offenders had been rearrested at least once within three years of release, with 71% of these arrests resulting in a new conviction or adjudication (New Jersey Department of Corrections, 2016).

Incarceration dramatically impacts juveniles' futures by removing them from the safety and protection of their communities, interrupting their social systems, disrupting their educational opportunities, and potentially exposing them to additional violence (Gilman, Hill & Hawkins, 2015). Re-incarceration has an even more significant impact on the individual, as it minimizes the chances of ever successfully exiting the criminal justice system.

There is a rich body of literature analyzing the factors that exacerbate the risk of reoffending among previously incarcerated individuals. However, most existing studies adopt a general approach to recidivism without focusing specifically on juveniles. Findings obtained from adult offender populations may not be generalizable to juvenile offenders, as adults and juveniles respond differently to societal influences. Furthermore, most existing studies examine factors that influence recidivism outside the criminal justice system and overlook the elements within the system — specifically, experiences during incarceration — that increase the risk of recidivism.

The proposed study seeks to address these knowledge gaps by analyzing the factors that exacerbate the risk of recidivism among juveniles, including exacerbating factors present during the period of incarceration. It would also be prudent to determine whether the factors that influence juvenile recidivism risk are the same as those that affect older offenders.

Studies have made several recommendations on potential programs that could enhance the rehabilitation of incarcerated juveniles and minimize their risk of recidivism. Elrod and Ryder (2020), for instance, advance the idea of restorative government and community collaborations through churches, Boys and Girls Clubs, and other community organizations to address the justice component.

Other studies, such as Gilman et al. (2015), have proposed the expansion of residential placement programs as an alternative to incarceration for juvenile offenders. Under residential placement programs, youth are placed in residential homes with families, or in facilities with specialized training. Residential placement programs are considered more effective than incarceration in minimizing the risk of future reoffending because they employ a community-oriented approach (Brown & Smith, 2018). However, opponents argue that residential programs may actually increase aggression and violence among youth, since such programs are not physically secure and often involve placing like-minded youth together under under-trained and poorly paid staff members (Brown & Smith, 2018). Critics also argue that residential programs may fail to uphold the strict disciplinary measures found in juvenile incarceration facilities, which could undermine their overall purpose.

Amidst the ongoing debate on what may or may not work in minimizing recidivism risk among delinquent juveniles, it is crucial to educate the public and policymakers on the factors that influence this risk. Understanding these factors is the first step toward developing effective rehabilitation programs.

The proposed study seeks to analyze the factors that influence recidivism among juvenile offenders. The findings will provide policymakers with crucial insights into the specific factors that drive juvenile recidivism and, by extension, the rehabilitation programs most appropriate for this population. The research questions guiding the study are:

RQ1: What factors exacerbate the risk of recidivism among juvenile offenders outside the criminal justice system?

RQ2: What factors exacerbate the risk of recidivism among juvenile offenders during their incarceration?

RQ3: What therapeutic influences could help reduce the risk of recidivism among juvenile offenders?

Literature Review: Variables Influencing Recidivism

The proposed study seeks to identify and analyze the structural factors that influence recidivism among juvenile offenders. In line with this objective, this chapter reviews literature on the factors exacerbating the risk of recidivism among former inmates. It is organized into three sections. The first reviews literature on the effect of quality-of-life variables on the risk of recidivism. The second reviews literature on the role of unemployment in fueling recidivism. The final section identifies the knowledge gaps evident in the reviewed literature and explains how the proposed study will address them.

Recidivism is defined as the act of returning to prison within three years of one's release (Chetty & Hendren, 2017). Multiple studies have been conducted to identify factors that exacerbate this risk among former inmates. There is general agreement in the literature that an individual's quality of life upon release influences their likelihood of repeat offending in young adulthood (Mallett, 2013). Pereira and Maia (2017) conducted a study analyzing the relationship between criminal history and reoffending rates among Portuguese prisoners, concluding that quality of life was a significant influencer of criminal thinking, with those surrounded by low quality-of-life indicators running higher risks of recidivism. These findings were replicated by Barett and Katsiyannis (2015), who analyzed the effect of demographic elements — particularly race — on recidivism rates among juveniles in South Carolina. Like Pereira and Maia (2017), they found a significant likelihood of recidivism in young adults with a history of juvenile delinquency, as well as among African Americans, with police presence, crime, and poverty identified as significant contributing factors. While both studies take similar approaches, Barett and Katsiyannis (2015) additionally analyze the effect of demographic variables in predicting recidivism risk, which Pereira and Maia (2017) do not address.

A study by Grunwald et al. (2010) also reported a strong association between quality-of-life indicators — specifically neighborhood characteristics — and the risk of recidivism. Like Barett and Katsiyannis (2015), Grunwald et al. (2010) found a positive correlation between neighborhood disorganization, childhood poverty, drug use, mental illness, socioeconomic status, and negative family dynamics and the risk of reoffending upon release. Unlike Barett and Katsiyannis (2015), however, Grunwald et al. (2010) found no significant relationship between police presence and recidivism risk.

Grunwald et al. (2010) introduced the role of environmental factors in shaping criminal behavior — a finding replicated by Mulder et al. (2010), who established that, based on social control theory, child neglect, family breakdown, and high neighborhood crime rates significantly impact the chances of a juvenile reoffending upon release from incarceration. Ryan et al. (2013) also analyzed the effect of parental attachment — specifically child neglect — on recidivism risk using statewide data from youth in the childcare system. Their findings showed a significant positive correlation between repeat offense and child neglect, particularly for youth in foster care. Based on this evidence, future research might focus on early interventions for children in foster care and supportive services for parents accused of neglect or abuse.

Ryan et al. (2013) also introduced the important dimension of time, finding that approximately 61% of convicted youth who recidivated did so within 18 months of their initial arrest. Studies focused on the time elapsed between release and re-arrest among juvenile offenders remain limited, making this an important avenue for future research. This finding is intriguing in that it establishes that the window to recidivism is relatively short — youth are released and almost immediately re-offend and are re-incarcerated. This may be linked to Mulder et al.'s (2010) finding that the environment in which a juvenile is placed immediately upon release has a significant impact on their risk of recidivism.

Unemployment and Recidivism

Studies contend that most offenders have difficulty obtaining employment upon release from incarceration, which increases their risk of reoffending (Ramakers et al., 2017; Nally et al., 2014). However, researchers differ on the question of whether post-incarceration employment actually reduces recidivism risk. A study by Tripodi, Kim, and Bender (2009) exploring the relationship between employment and recidivism for parolees found that post-incarceration employment did not significantly decrease the likelihood of recidivism, but only increased the time before re-incarceration. In other words, parolees who secured employment spent more time crime-free in the community before ultimately returning to prison (Tripodi et al., 2009).

In sharp contrast, more recent studies have found a positive association between unemployment and recidivism risk. In a five-year follow-up study, Nally et al. (2014) found a negative association between post-release employment and recidivism, though employment rates varied with the nature of the crime for which one was incarcerated. Their findings place drug and sex offenders at the highest risk of post-incarceration unemployment and non-violent offenders at the lowest risk (Nally et al., 2014). These findings conflict, however, with those of Bhuller et al. (2016), who found a significant association between post-incarceration employment and recidivism but no significant association between the nature of crime and employment rate. Both studies, however, found evidence of a negative association between incarceration and employment.

Regarding the possible reasons why former inmates face difficulty obtaining employment, researchers contend that unemployment among ex-convicts is largely due to a lack of skills, selection issues, and social barriers. According to Bhuller et al. (2016), selection has the greatest influence on unemployment, with most employers unwilling to hire former inmates for fear of reputational damage.

Other studies have shown that the risk of recidivism not only depends on the likelihood of securing a job, but also on the nature of the job. In their longitudinal study examining recidivism rates among Dutch prisoners, Ramakers et al. (2017) found that former inmates were less likely to be employed in jobs with higher occupational levels (stable jobs). The researchers agree with Bhuller et al. (2016) that, owing to their time in prison, most ex-prisoners lack the skills required for stable jobs and must opt for less stable positions. The two studies differ, however, on the primacy of skills: Bhuller et al. (2016) found that selection — not lack of skills — was the primary reason ex-prisoners struggle to find jobs.

Both Bhuller et al. (2016) and Ramakers et al. (2017) contend that post-incarceration unemployment increases recidivism risk. According to Ramakers et al. (2017), however, the risk is shaped not only by unemployment itself but also by the nature of the employment obtained. Jobs with higher occupational levels are associated with lower recidivism risk than less stable jobs (Ramakers et al., 2017). This finding was replicated by Schnepel (2018), who found that jobs in manufacturing and construction helped reduce recidivism, while other types of jobs characterized by low wages had no effect. More research is needed to accurately analyze the role of job stability in influencing recidivism. These findings nonetheless point to the importance of enhancing opportunities for offenders to obtain stable employment upon release as a strategy for minimizing recidivism risk.

While there is consensus across studies that post-incarceration unemployment increases recidivism risk, studies offer conflicting results on why ex-prisoners find it difficult to secure jobs and how the nature of the crime influences post-incarceration unemployment. There is agreement in the literature, however, that the nature of post-incarceration employment also influences the risk of recidivism.

Theoretical Framework: Social Learning Theory

Albert Bandura's social learning theory will serve as the guiding framework for the proposed study. The theory suggests that individuals learn by observing the actions of others and the positive or negative consequences associated with those actions (Hunter-Reel, 2013). It rests on two fundamental assumptions. First, humans are naturally social and learn through interactions such as reciprocal teaching, apprenticeships, and collaborations (Hunter-Reel, 2013). Second, human beings have significant control over their actions and environments and can therefore adequately shape their own learning (Hunter-Reel, 2013). The proposed study will use these assumptions to determine how juvenile intervention programs should be structured to enhance learning, reduce criminal inclinations, and minimize reoffending risk. The study will compare recidivism rates across selected states to determine whether significant differences exist between states whose offender interventions emphasize interaction and learning and those that limit such interactions.

Several studies have employed social learning theory within the context of offender rehabilitation in correctional facilities. Sundt et al. (2014) sought to determine the extent to which prison-chaplain rehabilitation programs employed precepts of social learning theory. The study built on findings by Andrews and Kiessling, which showed that correctional counseling interventions rooted in social learning theory are associated with lower rates of offender recidivism (Sundt et al., 2014). Sampled prison chaplains were interviewed about their use of education, value-changing through religion, vocational skill instruction, and emotional support. The researchers also sought to identify how frequently chaplains offered support in the form of reality therapy, group counseling, client-centered counseling, and behavioral methods. The study concluded that most prison chaplains who employ rehabilitation interventions rooted in social learning theory face lower rates of reoffending among those they serve (Sundt et al., 2014).

Phipps et al. (2001) adopted a different approach, using offenders as participants to determine the effect of selected rehabilitation interventions on crime outcomes. The study was based on the assumption that programs rooted in social learning theory are likely to have a more significant effect on offenders' outcomes (Phipps et al., 2001). The study found that programs promoting effective interaction among offenders are more effective than those that limit interaction. With respect to drug-involved offenders, drug treatment programs in the community were found to be more effective than adult drug courts, in-prison therapeutic communities with or without aftercare, and cognitive-behavioral therapy in reducing criminal outcomes upon release (Phipps et al., 2001). Therapeutic community programs were also found to be more effective than jail diversion programs in reducing criminal outcomes among offenders with mental illness (Phipps et al., 2001). For sex offenders, programs encouraging circles of accountability and support — including faith-based supervision — had the greatest impact in reducing criminal outcomes compared with other interventions such as psychotherapy, cognitive-behavioral treatment, and behavioral therapy (Phipps et al., 2001). Finally, a comparison of intermediate sanctions found treatment-oriented approaches more effective than surveillance-based approaches, regular supervision, boot camps, and electronic monitoring (Phipps et al., 2001). Though the study does not directly cite social learning theory, its findings indicate greater efficacy for interventions that promote learning and enhance social interactions.

Davis et al. (2013) sought to determine whether correctional education had a significant effect on recidivism risk upon release. Their study found that correctional education programs reduced the risk of re-arrest within three years of release by 12.9 percentage points (Davis et al., 2013). Furthermore, the impact of these programs depended on the type of instruction method employed, with a significant effect found for instructional techniques that promote learning through interaction with instructors and with college instructors external to the correctional facility (Davis et al., 2013). The researchers explain these findings through the lens of social learning theory: since learning occurs through observing and learning from the experiences of others, offenders develop an admiration for the freedom and knowledge that people outside the facility possess. This admiration reduces their inclination to recidivate (Davis et al., 2013).

The researchers acknowledge the relevance of other theories, such as social bonds theory and social disorganization theory. Social bonds theory was set aside because of its core assumption that human beings are naturally self-interested and do not require external motivation to commit crime. Since the proposed study seeks to examine the impact of intervention programs — which are external stimuli — the assumption that external stimuli do not influence criminal behavior is not compatible with the study's objectives. Social disorganization theory was similarly set aside because it emphasizes changes in ecological structures such as racial composition, which fall outside the scope of the proposed study. Social learning theory, by contrast, directly supports the examination of how structured interactions and rehabilitation programs shape offender behavior and outcomes.

Conclusion

The proposed study seeks to analyze the factors that influence recidivism among juvenile offenders and to develop a practical intervention manual to guide stakeholders in rehabilitation efforts. High recidivism rates among juveniles represent both a human cost — in terms of disrupted lives and lost futures — and a systemic failure of the criminal justice system to rehabilitate and reintegrate young people. By examining quality-of-life indicators, the role of post-incarceration employment, and the influence of therapeutic programs grounded in social learning theory, the study aims to produce actionable findings for policymakers and practitioners in the field of juvenile justice.

The study is subject to several limitations. The reliance on interview data from stakeholders in a single metropolitan area (Durham, North Carolina) may limit the generalizability of findings. Additionally, the absence of comprehensive national juvenile recidivism data — due to the state-level administration of juvenile justice — presents a challenge for cross-state comparisons. Future research should consider longitudinal designs and larger, more geographically diverse samples.

The implications for social work practice are significant. Social workers play a central role in supporting juvenile offenders both during and after incarceration. Understanding the structural and individual-level factors that drive recidivism enables social workers to design more targeted, evidence-based interventions. Programs that promote learning, positive social interaction, family support, and stable post-release employment are most likely to reduce reoffending rates and improve long-term outcomes for justice-involved youth.