Risk Factors For Prison Recidivism Research Paper

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One of the most frequently used measures to gauge the effectiveness and impact of criminal sentencing and correctional programs is the recidivism of those processed through the justice system and released from community corrections programs or prisons. Broadly defined, recidivism is the return to criminal behavior following some type of intervention by the criminal justice system; however, in practice and research, how recidivism is measured varies dramatically, and as a result, so too do rates of recidivism. Based on one definition that has been used for those released from prison – whether or not the former inmate was rearrested for a new crime within 3 years following release – the recidivism rate of a nationally representative sample of released inmates in the United States was 68 %; however, when defined as returned to prison as a result of a new conviction, the recidivism rate was 25 % (Langan and Levin 2002). In addition to recidivism rates varying depending what definition of recidivism is used, the likelihood of recidivism also varies depending on a variety of individual-level and community-level risk factors, as well as state and local criminal justice practices and policies. Over the past four decades, risk factors for prisoner recidivism have increasingly been used to guide criminal justice practice and policy, and the understanding within the field of criminal justice and criminology as to the factors associated with prisoner recidivism have increased in depth and sophistication. This knowledge has helped improve the targeting of limited criminal justice resources to those who pose the highest risk of recidivism and those who can benefit most from rehabilitative interventions that can reduce risk of recidivism. These advances in understanding of the risk factors associated with prisoner recidivism have also improved the designs of evaluations of program and policy interventions intended to reduce recidivism.

Definitions And Measures Of Recidivism

The broad definition of recidivism is the return to criminal behavior following some type of intervention by the criminal justice system, such as following an individual’s conviction and placement on probation or following their release from prison. Although there are a number of purposes or goals when it comes to sentencing those convicted of crimes, including individual and general deterrence, retribution/punishment, incapacitation, and rehabilitation, only two of these goals actually seek to reduce criminal behavior following the completion of a criminal sentence: individual deterrence and rehabilitation. Thus, the concept of recidivism within this context can be seen as a measure of the degree to which these interventions were effective. “High” recidivism rates can be used to draw the attention of public policy makers and practitioners to interventions that may need to change or are used to illustrate the difficulty of deterring or rehabilitating specific types of offenders. Varying levels of recidivism rates across programs or services, or among specific types of offenders, can also be used by practitioners and policy makers to invest more, or refer more offenders, to those interventions that seem to be “working” to reduce recidivism.

However, as important as recidivism is as a measure of the effectiveness of criminal justice interventions, the definition of what constitutes “recidivism” in the domains of both criminal justice researchers and practitioners varies considerably. While the conceptual definition of recidivism is the return to criminal behavior, how exactly have researchers and practitioners operationalized this concept so that it can be measured in the real world? The operational definitions and methods of measurement have ranged from researchers interviewing former prison inmates and asking them to self-disclose new criminal behavior, such as illegal drug use or theft, to state departments of corrections determining how many of the inmates they released from prison have been readmitted to prison. Because the specific measure used to gauge recidivism has such a significant impact on the level of recidivism that will be detected, it is important here to briefly describe the measures of recidivism that have been most frequently used in examining those released from prison and their relative strengths and weaknesses.

In addition, the amount of time following an inmate’s release from prison during which recidivism is measured also varies considerably from study to study, ranging from relatively short periods of time at risk to much longer postprison follow-up periods. Generally, recidivism research has found that if a prison release is going to recidivate, it tends to happen relatively soon after their release and as the longer they survive without recidivating, the lower the likelihood that it will occur.

As a result of these different methods of operationalizing and measuring recidivism, recidivism rates can vary considerably and also have varying levels of reliability and validity. For example, many practitioners and policy makers would question the truthfulness (i.e., reliability) of former inmates reporting new criminal behavior to a researcher, regardless of assurances of anonymity or confidentiality that may be used to improve the reliability of the responses. In addition to the concerns regarding the reliability of self-reported information about the participation of former inmates in new criminal activity, one of the biggest limitations to the use of self-reported information as a means of gauging postprison recidivism is the enormous amount of time and resources needed to collect this information from sufficiently large samples of former inmates.

Because of the costs and concerns with the reliability of obtaining self-reported information to gauge recidivism, most researchers, agency administrators, and policy analysts examining prisoner recidivism utilize “official” records of recorded events, such as new arrests, convictions, or admissions to prison. However, while relatively easy to access and obtain, operationalizing and measuring recidivism using official records of arrests, convictions, or returns to prison also have their own limitations, and recidivism rates vary dramatically depending on which of these measures is selected. Illustrative of this is recidivism analyses performed on a nationally representative sample of prison releasees by the US Department of Justice’s Bureau of Justice Statistics which utilized four different measures of recidivism (Langan and Levin 2002). Specifically, the recidivism of a cohort of inmates released from state prisons in 1994 was examined using rates of rearrest, reconviction, return to prison for any reason (a new conviction or a technical parole violation), and return to prison as a result of a new conviction, all within 3 years of release. While somewhat dated, the results from that study are illustrative and useful for revealing the differences in recidivism rates across different definitions of recidivism. For example, when the operational definition of recidivism was rearrest for a new crime, 68 % of prison releasees recidivated, compared to a recidivism rate of 52 % when defined as being returned to prison for a new crime or a technical violation of their release conditions, 47 % when recidivism was defined as being reconvicted for a new crime, and, lastly, a recidivism rate of 25 % when defined as being resentenced to prison for a new crime (Langan and Levin 2002). Thus, depending on the operational definition of recidivism selected, the overall rates of recidivism will vary considerably, but, again, there are concerns regarding the validity of these measures. For example, some would not feel as though being convicted, or returned to prison as a result of a new conviction, is a sufficiently broad (i.e., valid) definition of recidivism, and it is likely that if it were possible to obtain reliable self-reported information regarding involvement in crime that the recidivism rate would be considerably higher. Similarly, many have pointed out that simply being arrested for a new crime does not necessarily provide a valid measure of recidivism, but merely that police had probable cause that the individual had committed a crime, and it is also obvious that not all criminal behaviors come to the attention of the police or result in arrests.

Fundamentals Of Risk Factors For Prison Recidivism

While the operational definition used to measure recidivism results in different recidivism rates, regardless of the specific measures of prison recidivism used, a number of risk factors have been identified as having a consistent relationship to recidivism and have played a significant role in criminal justice policy and practice. Indeed, one of the oldest and most fundamental decision-making processes in community corrections, including the supervision of those released from prison, is the assessment of offender risk (Holsinger et al. 2001). The problem of predicting offender risk is paramount to decision making at various stages of the criminal justice system and is integral to several decisions regarding the release of those from prison, including decisions as to whether or not they should be released and, if released, the level and conditions of parole supervision. Over the past 30 years, the tools and approaches to risk assessment of prison releasees and probationers have evolved dramatically, and experts in the field of community corrections have identified three generations of risk assessment: subjective or clinical judgments, actuarial or case classification approaches, and criminogenic/dynamic evaluations (Bonta 1996). From the development of these risk assessment instruments, and extensive research on recidivism of those released from prison, a number of general conclusions regarding risk of prisoner recidivism have now become widely accepted within the field of criminal justice and criminology, while other risk factors are either evolving in terms of better understanding prisoner recidivism, and still others are the subject of considerable debate among scholars, practitioners, and policy makers. These risk factors associated with prisoner recidivism can be grouped, generally, into three main categories: (1) individual-level risk factors, (2) community-level risk factors, and (3) criminal justice policies and practices that influence the likelihood of recidivism.

Individual-Level Risk Factors Of Prisoner Recidivism

The first category of risk factors for prisoner recidivism include the characteristics or traits of the individual prison releasee and have been characterized by Andrews and Bonta (1994) as falling into one of two subcategories of individual risk: individual static characteristics and individual dynamic characteristics. Static risk factors are those that cannot be changed as a result of correctional interventions and include traits such as age at first arrest, prior arrests, current age, current conviction offense, and gender. Dynamic risk factors, on the other hand, are characteristics of the offender that can be changed, either through clinical interventions or by changes in the former prison inmate’s circumstances, such as antisocial thinking patterns and cognition, drug use patterns, employment status, and having antisocial or criminal peer groups and associates.

As a result of numerous individual studies and meta-analyses examining prison inmate recidivism, a number of individual-level, static characteristics have been consistently found to be associated with postprison recidivism. For example, a metaanalysis conducted by Gendreau et al. (1996) found the offender’s criminal history, history of other antisocial behaviors, age, the environment within which the inmate was raised as a child (family criminality, family structure, and family-rearing practices), race, and gender were all related to the risk of recidivism. Two of the strongest individual-level, static predictors of recidivism in the Gendreau et al. (1996) study, as well across numerous individual studies examining offender populations (i.e., prison releasees and probationers), were the individual’s age and the extent of their criminal history.

Generally, the older the individual when discharged from their correctional programming (i.e., prison or probation), the lower the risk of recidivism, regardless of how recidivism has been operationalized and regardless of what other risk factors are statistically controlled. While the general criminology literature has found a strong association between age and involvement in crime, or desistence from crime, even among those who are known offenders (i.e., those released from prison), this pattern also holds. Similarly, those released from prison with more extensive criminal histories, whether operationalized as prior arrests, prior convictions, prior prison sentences, or other measures of previous antisocial behavior, have a higher risk of continued involvement in crime (i.e., recidivism) independent of other risk factors or characteristics. Males released from prison also tend to have higher rates of recidivism than females, even after the influence of other characteristics have been accounted for or statistically controlled. The current conviction offense has also been found to be associated with recidivism of those released from prison, with those released from prison after having served a sentence for a property crime or a drug-law violation having a higher risk of recidivism than those who had served a sentence for a violent crime. However, the magnitude of effect for this risk factor tends to lessen after other risk factors are controlled for, such as age at release from prison, prior criminal and substance abuse history, and education level. In fact, the static, individual-level risk factors of age, criminal history, gender, and current conviction offense are even consistent predictors of prisoner recidivism in the few studies of inmate recidivism that have been performed in nonindustrialized Western nations, such as in Malta, a small republic in the Mediterranean Sea (Baumer 1997).

The Gendreau et al. (1996) meta-analysis also found the race of the offender to be related to recidivism in the small number of studies that included this as a variable, with minorities having a higher likelihood of recidivism, and some more recent studies have also found that minorities have significantly higher odds of recidivating than white offenders (DeComo 1998; Strom 2000). However, some studies suggest that in fact there is no statistically significant difference in the recidivism rates of minority and white juveniles (Mbuba 2005), particularly after other risk factors are taken into consideration. Thus, while some studies have found race to be predictive of recidivism for those released from prison, others have found the magnitude of the race effect on recidivism to vary or be neutral depending on what other variables are statistically accounted for in the analyses. There are also a large number of recidivism studies that have not included race as an individual-level risk factor in the analyses.

However, from the standpoint of criminal justice policy and practice, one of the biggest limitations of these static risk factors is that, by definition, they cannot be changed. Thus, while they can be used to aid in predicting the risk of recidivism, and as a result subject the individual to a higher level of supervision, they cannot always be effectively used to reduce the risk of recidivism. Therefore, it is critical to point out that there are also numerous individual-level risk factors that are considered dynamic or malleable and, if changed, can be viewed as assets or protective factors. For example, while an individual’s history of drug use is predictive of their likelihood of recidivism, their current drug use patterns, their cognitive views on the appropriateness of drug use, and their completion of substance abuse treatment while in prison can reduce the likelihood of recidivism. Although the efficacy of prison-based treatment as a means of reducing the risk of recidivism was challenged in the 1970s, leading to a number of policy shifts that reduced the availability and emphasis on rehabilitation for prison inmates, there is currently agreement among most criminologists that treatment addressing dynamic criminogenic needs and utilizing evidence-based practices can reduce the risk of recidivism, which has led to a revival of rehabilitative efforts both within prisons and following release from prison.

Again, a number of meta-analyses have identified the individual-level, dynamic risk factors associated with recidivism among those released from prison, including antisocial personalities; socialization with other offenders; antisocial attitudes related to behavior, employment, and education; conflict with family; personal distress, such as anxiety and low self-esteem; social achievement, such as employment, marital status, and education; and drug use patterns (Gendreau et al. 1996). Thus, interventions that seek to alter a prison inmate’s or a parolee’s antisocial attitudes, teach them to more effectively handle anxiety or interpersonal conflict in noncriminal ways (i.e., without the use of drugs or violence), or improve their educational achievement or employability can change these dynamic risk factors and, as a result, reduce the risk of recidivism. Evidence regarding the impact these types of interventions can have on recidivism is also quite plentiful. For example, Wilson et al. (2000) found in a meta-analysis of corrections-based education, vocational and work programs that participants generally had lower rates of recidivism, although the existing literature is still limited in terms of fully understanding the causal relationship of these programs versus issues of selection bias regarding who participates in these types of programs. Another intervention used within prisons to addresses individual-level, dynamic risk is cognitive-behavioral therapy (CBT), which views an offender’s cognitive processes related to crime as something that can be changed. “Cognitive-behavior therapy is based on the assumption that cognitive deficits and distortions characteristic of offenders are learned rather than inherent. Programs for offenders, therefore, emphasize individual accountability and attempt to teach offenders to understand the thinking processes and choices that immediately preceded their criminal behavior” (Lispy et al. 2007). In their meta-analysis of CBT programs, Lipsy et al. (2007) found that, overall, CBT interventions were effective at reducing recidivism and that some specific characteristics of programs generated greater recidivism reductions, including how well the programs were implemented (i.e., fidelity to program design), targeting of higher risk offenders, and the incorporation of specific CBT elements related to anger management and interpersonal problem solving.

Prison-based programs that seek to address issues related to an inmate’s substance abuse patterns, also an individual-level dynamic risk factor, are another means by which the risk of recidivism can be reduced upon an inmate’s release back to the community. One of the most effective modalities of providing prison-based substance abuse treatment to inmates is through the use of Therapeutic Communities (TCs). TCs are “residential [programs] that use a hierarchical model with treatment strategies that reflect increased levels of personal and social responsibility. Peer influence, mediated through a variety of group processes, is used to help individuals learn and assimilate social norms and develop more effective social skills” (National Institute on Drug Abuse 2002). Also, because TCs are one of the most common and widely studied drug treatment modalities for prison inmates (Lurigio 2000), their efficacy in reducing the risk of recidivism among prison releasees has been well documented and established. Mitchell et al. (2006) is one of the most recent, comprehensive, and rigorous meta-analyses published on the effectiveness of incarceration-based drug treatment. In general, most of the research on prison-based TCs, including Mitchell et al. (2006), has documented recidivism reductions for those inmates who participated, although the magnitude of the reduction varied, depending on the length of stay, the population served, the inclusion of educational and vocational programming, and the provision of access to aftercare following release from prison.

Although not generally considered among the individual-level, dynamic risk factors for recidivism, the amount of time spent in prison is certainly a factor that can be modified and altered by criminal justice practitioners and policy makers if it were found to influence recidivism. Yet despite the fact that longer prison sentences have consistently been argued as an effective crime control policy based on the belief that longer sentences would generate individual deterrence and thus reduce subsequent recidivism, much of the research that has sought to examine this question is dated, suffers from methodological limitations, and has produced inconsistent and, at times, contradictory findings. For example, a meta-analysis by Gendreau, Goggin, and Cullen (1999) found that longer prison sentences were associated with an increased likelihood of recidivism, contrary to what would be expected through the lens of individual deterrence; however, Snodgrass et al. (2011) points out that this meta-analysis was based primarily on research conducted in the 1970s, when sentence lengths among prison inmates were dramatically different than they are today. In their recent examination of the question as to whether or not length of time in prison reduces recidivism among prison releasees in the Netherlands, Snodgrass et al. (2011) found there to be no effect of time served on subsequent recidivism. More generally than just length of time served, a meta-analysis examining the relationship of harsh penalties and recidivism found that harsher punishments were related to a slight increase in recidivism, but when it came to sentence lengths, sentences under six months showed no impact on recidivism while sentences were found to increase the risk of recidivism (Smith et al. 2002). Thus, while the research literature regarding the impact of length of stay in prison on subsequent recidivism appears to suggest that it either has no effect or increases the risk of recidivism, many would also argue that the reduction of recidivism is only one goal in the sentencing of convicted offenders to prison, and thus longer sentences would be justified on the basis of retribution and incapacitation.

The Universal Nature Of Individual-Level Risk Factors

It is important to note that many of the individual-level risk factors for recidivism, including both static and dynamic risks, may not be consistent or have the same magnitude of effect to all subpopulations of prison releasees. For example, since the majority of prison releasees are accounted for by males, and therefore much of what is known about risk factors for prison recidivism has been based on research predominantly of male offenders, concern regarding the generalizability of risk factors specifically to female prison releasees has been raised. Similarly, the degree to which risk factors are consistently predictive of “general” recidivism versus recidivism for specific types of crimes, such as violent offenses, also varies. For example, while under supervision or during reentry from prison, unemployment or job dissatisfaction – an individual-level dynamic risk factor – is related more to men’s recidivism than to women’s (Benda 2005). On the other hand, greater educational achievement significantly lowers women’s risk of recidivism, but has less effect on men’s recidivism (Uggen and Kruttschnitt 1998). Similarly, research has produced inconsistent findings on whether having friends who engage in criminal lifestyle – which has been identified in meta-analyses of increasing the risk of recidivism – increases the risk of recidivism for both men and women (Uggen and Kruttschnitt 1998; Benda 2005).

In addition to factors that increase or decrease the overall likelihood of recidivism, practitioners and policy makers are often concerned with recidivism for very specific types of crimes. For example, it is of greater concern from the standpoint of public safety when the recidivism involves crimes of violence against a victim than when the recidivism involves minor property crimes or drug-law violations. Similarly, for offenders sentenced to prison for sexual assault, upon their release from prison one of the biggest concerns among practitioners and policy makers is their likelihood of committing another sexual assault. However, because violent recidivism, and even more specifically sexually violent recidivism, is much less prevalent than more general recidivism, it tends to be more difficult to accurately predict. Still, a review of research on the accuracy of standardized risk assessment scales of predicting violent recidivism indicates that scales containing individual-level dynamic risk factors have higher predictive accuracy than scales that contain only individual-level static risk factors (Campbell et al. 2009).

Community-Level Risk Factors

While there is a fairly extensive body of literature and significant agreement on the individual-level risk factors that contribute to recidivism among those released from prison, as a result of the growing interest among researchers and policy makers in the area of prisoner reentry, it has increasingly been recognized that the characteristics of the community the offender is released back into may also influence the likelihood of recidivism. Moreover, these environmental conditions may modify the predictive accuracy of certain individual-level risk factors. For example, offenders who have a history of substance abuse are more likely to relapse and use illicit drugs (i.e., recidivate) in high-poverty areas than in neighborhoods with low poverty rates (Galea et al. 2003). Thus, the risk assessment field has recently recognized the importance of incorporating risk factors that relate also to the criminogenic aspects of an offender’s surrounding environment in assessing offenders’ risk of recidivism. The recognition of this issue by policy makers and practitioners, coupled with the application of more sophisticated statistical techniques to examine recidivism (i.e., hierarchical linear modeling), has produced a small but growing body of scientific literature that has examined the influence of community-level characteristics on prisoner recidivism.

In the limited number of studies that have been published, there appears to be some confirmation that community or neighborhood characteristics related to poverty, crime and disorder, economic opportunity, and the availability of social services does influence, independent of individual-level risk factors, the risk of recidivism among prison releasees. For example, Kubrin and Stewart (2006) incorporated Massey’s (2001) Index of Concentration at the Extremes (ICE), a community-level measure of the degree of concentrated affluence relative to the concentration of poverty, in their analyses of recidivism among individuals released from prison and found that inmates released into neighborhoods with higher concentrations of affluence had a lower risk of recidivism independent of their individual-level risk factors. Similarly, Hipp et al. (2010) found that inmates released to communities with high levels of concentrated disadvantage and disorder had a higher risk of recidivism, independent of their individual-level risk factors, but communities where social service providers were not in close proximity to the released inmate also increased the risk of recidivism after controlling for the influence of other factors. A similar pattern was found by Olson et al. (2009), which suggested that inmates released back to communities where aftercare services for inmates are more readily available, and more varied, had higher rates of aftercare participation and completion, which reduced the likelihood of both parole violations and recidivism. Thus, while the Urban Institute’s research on reentry across a number of states has documented that the communities many inmates are released to have high levels of social and economic disadvantage (LaVigne et al. 2004), the increased risk that this poses regarding recidivism may be mitigated if there are higher levels of social service programs available. As the research regarding the independent influence of community-level risk factors for prison recidivism increases and evolves, it will be possible to better isolate the relative influences that individual-level versus community-level risk factors play in prisoner recidivism.

The Influence Of Criminal Justice Practice And Policy On Prison Recidivism

The last of the three general areas that can change the risk of recidivism has to do with changes and differences in criminal justice practice and policy. Among all of the risk factors presented, the degree to which criminal justice practice and policy impacts recidivism had more to do with how recidivism is operationalized and interpreted. For example, if return to prison within three years is the definition of recidivism, and one of the ways that a former inmate can be returned to prison is the result of violating the conditions of their release, then it is obvious that policies related to the extent and nature of postrelease conditions of supervision, staffing levels, and practices of parole agents, and the policies regarding how violations of release conditions are handled, will all influence the rate at which individuals released from prison are returned to prison (i.e., “recidivism”). Generally, those released from prison that are subject to a higher frequency of supervision contacts and more intensive monitoring have higher rates of violations of release conditions being detected and, as a result, higher rates of being returned to prison. The level and intensity of postprison supervision can change over time within a specific state and also varies considerably across states.

For example, in some states, such as California, those returned to prison for parole violations accounted for 65 % of all prison admissions in 2010, while at the other end of the spectrum were the states of Florida, Virginia, North Carolina, Idaho, Ohio, and Nebraska, where parole violators accounted for less than 10 % of all prison admissions (Guerino et al. 2011). Generally, the larger the proportion of prison releasees who are subject to supervision and other conditions of release, the larger the proportion of admissions accounted for by parole violators and the higher the “recidivism” rate if measured by rates of return to prison. If only a small proportion of prison releasees are supervised and have conditions, it follows that only a small number of prison releasees can be returned to parole violations. Also, some of these changes in practice and policy can be gradual, whereas other changes can be implemented quickly and dramatically. Thus, it is important to note that policies related to whether or not those released from prison are subject to supervision, what other conditions of release are required and monitored, and how long that supervision lasts vary from state to state and, as a result, can produce different rates of “recidivism” when measured as return to prison. Further, before one can conclude that recidivism rates based on return to prison in a state have changed or are higher or lower than another state, changes or differences in postprison supervision policies and practices need to be considered and accounted for in analyses.

However, it is not only correctional or parole policy and practice that can influence and impact recidivism rates of those released from prison but those of police departments and the courts as well. For example, if individuals are released from prison during a period when police departments are cracking down or focusing on specific types of crimes or offenders, such as drug delivery offenses or parolees in specific neighborhoods, then inmates released from prison during that period of time may be more likely to be arrested than those released from prison when police officers were being deployed for other purposes or periods when police presence was lower. Thus, if the definition of recidivism is rearrest for a new crime, then obviously changes or differences in police policy and practice over time and across place can have an influence on this measure of recidivism. The same can be said for measures or recidivism that rely on reconviction as the operationalized definition of recidivism: changes in the practices and policies of prosecutor’s offices regarding what types of offenses they will file charges for, take to trial, or plea bargain can potentially influence the likelihood of a prison releasee being reconvicted of a crime or a felony offense following their release. Importantly, all of these changes in policy and practice – parole supervision intensity, police department activities, and prosecutorial decision making – can impact each other and have differential impacts on the different measures of “recidivism” (i.e., rearrest, reconviction, return to prison for any reason or specifically as a result of a new conviction).

Conclusions And Directions For Future Research

The body of research and knowledge on the risk factors of prison recidivism has increased and improved dramatically over the past 40 years and is increasingly being used by criminal justice practitioners and policy makers. This knowledge of risk factors for prison recidivism is increasingly being used by clinicians working with prison inmates to better identify and target the individual-level dynamic risk factors that need to be addressed, by parole boards in deciding which inmates can be released from prison due to their lower risk of recidivism, and by policy makers as they seek to allocate resources to programs, interventions, and community-based services that can reduce recidivism among those released from prison. Still, it must be recognized that while the use of more sophisticated approaches to identifying and classifying the risk of prison recidivism has improved predictive accuracy and guided case management strategies and practices, the science is not perfect and is continually evolving and improving. When tasked with the challenge of predicting human behavior (i.e., recidivism), even when we can take into consideration individual-level static and dynamic risk factors, coupled with community-level risk factors, there are bound to be false positives and false negatives: there will be individuals who are low risk based on all of these factors that will reoffend, as well as individuals who are high risk based on their risk factors who end up not reoffending. The latter is unlikely to be a concern for criminal justice practitioners or policy makers, but the former will be of considerable concern and oftentimes results in the questioning of using actuarial risk to determine if an inmate should be released from prison and how they should be supervised. However, generally speaking, the criminal justice system can identify and utilize risk factors for recidivism much more effectively than in the past to address individual-level risks, reduce recidivism, and ultimately, improve public safety. Future research that improves the understanding in the field of the interactions of individual-and community-level risk factors, and can effectively articulate how this knowledge and information can be used within the applied setting of criminal justice practice and policy, will go a long way towards continuing to improve public safety and reduced risk of recidivism for prison releasees.

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