Predictors Of Recidivism Research Articles

Time for a Change: Examining the Relationships between Recidivism-Free Time, Recidivism Risk, and Risk Assessment

As efforts to reverse mass incarceration increase, so does the need to supervise more individuals in the community. Faced with heightened demand, community corrections agencies increasingly use risk assessment to allocate resources efficiently and improve public safety. While both static, historical factors as well as dynamic, changeable factors have been incorporated into risk assessment instruments, one factor notably absent is the amount of time an individual remains in the community recidivism-free. Using parametric and discrete hazard models, we examine the relationship between recidivism-free time and observed recidivism among individuals on parole supervision in Pennsylvania where dynamic risk assessment is used. Specifically, we assess whether recidivism-free time predicts recidivism independent of these risk scores and the extent to which single and repeated risk scores accurately predict recidivism. Findings support the use of dynamic risk instruments but suggest that recidivism prediction may benefit from considering recidivism-free time. Implications for community corrections policy are discussed.

Gender Differences in Substance Abuse History and Offending Behavior: A Multicentre Study in Dutch Forensic Psychiatry

ABSTRACT Substance abuse is an important risk factor for offending, but is mostly studied in males. The aim of this multicentre study is to gain insight into possible gender differences in substance abuse history and offending behavior in forensic psychiatric patients. Files were analyzed of 275 women and 275 matched men who have been admitted between 1984 and 2014 to one of four Dutch gender-mixed forensic hospitals. Risk assessment ratings were related to registered violent incidents during treatment for both women and men and to official recidivism data after discharge for a subgroup of 78 women. Substance abuse history was coded as a risk factor for more than half of the women (56.7%), but significantly more often for men (68.4%). Men were more often diagnosed with substance dependence and more frequently committed the index-offense whilst intoxicated. Prediction of violent incidents during treatment was more accurate for men. A history of substance abuse was not a significant predictor for recidivism after discharge in the subgroup women. It is concluded that there are gender differences in substance abuse history and that the relationship with offending behavior seems stronger for men. These differences have implications for substance use treatment in forensic mental health services.

"Part Man, Part Machine, All Cop": Automation in Policing.

Digitisation, automation, and datafication permeate policing and justice more and more each year—from predictive policing methods through recidivism prediction to automated biometric identification at the border. The sociotechnical issues surrounding the use of such systems raise questions and reveal problems, both old and new. Our article reviews contemporary issues surrounding automation in policing and the legal system, finds common issues and themes in various different examples, introduces the distinction between human “retail bias” and algorithmic “wholesale bias”, and argues for shifting the viewpoint on the debate to focus on both workers' rights and organisational responsibility as well as fundamental rights and the right to an effective remedy.

The Contribution of Static and Dynamic Factors to Recidivism Prediction for Black and White Youth Offenders

Scholars have presented concerns about potential for racial bias in risk assessments as a result of the inclusion of static factors, such as criminal history in risk assessments. The purpose of this study was to examine the extent to which static factors add incremental validity to the dynamic factors in criminogenic risk assessments. This study examined the Youth Level of Service/Case Management Inventory (YLS/CMI) in a sample of 1,270 youth offenders from a medium-sized Midwestern county between June 2004 and November 2013. Logistic regression was used to determine the predictive validity of the YLS/CMI and the individual contribution of static and dynamic domains of the assessment. Results indicated that the static domain differentially predicted recidivism for Black and White youth. In particular, the static domain was a significant predictor of recidivism for White youth, but this was not the case for Black youth. The dynamic domain significantly predicted recidivism for both Black and White offenders, and static risk factors improved prediction of recidivism for White youth, but not for Black youth.

The Price of Mistrust: A Study into the Working Alliance as Predictor for Recidivism

The responsivity principle is a vital element in the risk-need-responsivity model. The working alliance is a good illustration of the intention of this responsivity principle. In this study, we examine the influence of the working alliance (WAMCI) between 199 offenders and probation officers on recidivism. Data for this longitudinal study originate from adult probation services in the Netherlands. The association between the working alliance factors and recidivism was analyzed using a Cox regression. Offenders who reported more Trust in the relationship with their Probation Officer after 9 months community supervision showed less recidivism in the subsequent 4-year follow-up period. This association remained significant when controlled for criminal history, age, gender, ethnicity, family status, employment and addiction problems. Offenders who reported more reactance showed significantly more recidivism in the follow-up period, but this association was accounted for criminal history variables. These results can be regarded as an extension of the responsivity principle; a trusting relationship may be needed to create a space in which the client becomes engaged in a changing process.

The Impact of Fair Relationships on Rule Compliance for Women under Community Supervision

Women face many potential difficulties when under community supervision, and more research that examines their experiences there is needed. This study investigates how women under supervision relate to their supervisors and how these relationships impact their tendencies toward supervisory compliance. Using secondary data, predictors of recidivism are evaluated in 16 Michigan counties using the Dual Role Relationship Inventory–Revised (DRI-R) and its shorter form (DRI-SF), which quantify relationship quality. We found that one of the most important predictors of rule compliance for women under supervision is their relationship with their probation or parole officer. Thus, probation and parole officers should prioritize their personal relationships with their female clients by considering their unique circumstances while striving to cultivate an environment of fairness and mutual respect. This article advances our understanding of how to administer effective community supervision for women.

Does Reassessment Enhance the Prediction of Imminent Criminal Recidivism? Replicating Lloyd et al. (2020) With High-Risk Parolees.

Lloyd et al. (2020) proposed and tested a novel three-step framework for examining the extent to which reassessment of dynamic risk and protective factors enhances the prediction of imminent criminal recidivism. We conducted a conceptual replication of Lloyd et al.'s study. We used the same dynamic risk assessment measure in the same jurisdiction but, unlike Lloyd et al., our sample comprised solely high-risk men on parole in New Zealand (N = 966), the individuals who are most frequently reassessed in the community and most likely to imminently reoffend. The results of the previous study were largely reproduced: reassessment consistently enhanced prediction, with the most pronounced effects observed for a scale derived from theoretically acute dynamic risk factors. These findings indicate reassessment effects are robust to sample selection based on a narrower range of risk levels and remain robust across years of practice in applied contexts, despite potential organizational drift from initial training and reassessment fatigue. The findings also provide further support for the practice of ongoing risk reassessment in community supervision and suggest that the method proposed by Lloyd et al. is a replicable approach for testing the essential criteria for defining dynamic risk and protective factors.

Exposure to Family Violence and Risk Factors for Recidivism in Juvenile Offenders

ABSTRACT A better understanding of the relationship between exposure to family violence and criminal recidivism is essential in order to develop interventions which target the specific needs of juvenile offenders. Using the Structured Assessment of Violence Risk in Youth (SAVRY), we explored the differences in historical, social/contextual, and individual risk and protective factors for delinquency among youth males exposed (n = 253) and not exposed to family violence (n = 497) in Spain. Chi-square test shows that most of the risk factors assessed were present in the group exposed to family violence, especially a history of child maltreatment. Logistic regression analysis show that peer delinquency was a common predictor of recidivism in youth both exposed and not exposed to family violence. Early initiation of violence predicted recidivism in young offenders without exposure to family violence, while the absence of strong social support predicted recidivism in young offenders with this exposure. Professionals in juvenile justice services need to work on peer relationships, but also to keep in mind and to address the specific needs of young offenders both with and without exposure to family violence if the aim is to avoid recidivism.

Success Stories of Males Convicted of a Violent Offense

The United States incarceration rate is the highest in the world. Most research involving individuals with criminal involvement history focuses on predictors of recidivism versus factors contributing to success post-release. Post-release successes are important considerations to inform strengths-based approaches to working with this population. In this qualitative study, perspectives of males convicted of a violent offense in the United States who did not recidivate at least three-years-post release from incarceration were explored. Utilizing narrative inquiry, six participants shared their stories of how they avoided returning to a correctional facility. Through narrative analysis, the researchers identified five themes across participant stories: (a) knowledge as power, (b) paychecks after prison, (c) using to belong, (d) connections, and (e) transformational thinking. This study provides a strengths-based perspective when working with formerly incarcerated persons (FIPs). Implications for counselors and counselor educators are provided.

Testing the Role of Emotion Dysregulation as a Predictor of Juvenile Recidivism.

The current study proposed to determine whether adolescent emotion regulation is predictive of the amount and type of crime committed by adolescent juvenile offenders. Despite evidence in the literature linking emotion regulation to behaviour problems and aggression across the lifespan, there is no prior longitudinal research examining the predictive role of emotion regulation on adolescent recidivism, nor data regarding how emotion regulation relates to the occurrence of specific types of crimes. Our primary hypothesis was that poor emotion regulation would positively and significantly predict re-offending among adolescents. We tested our hypothesis within a binary logistic framework utilizing the Pathways to Desistance longitudinal data. Exploratory bivariate analyses were conducted regarding emotion regulation and type of crime in the service of future hypothesis generation. Though the findings did not indicate a statistically significant relation between emotion regulation and reoffending, exploratory findings suggest that some types of crime may be more linked to emotion regulation than others. In sum, the present study aimed to examine a hypothesized relation between emotion regulation and juvenile delinquency by identifying how the individual factor of dysregulated emotion regulation may have played a role. This study’s findings did not provide evidence that emotion regulation was a significant predictor of recidivism over time but did suggest that emotion regulation is related to participation in certain types of crime one year later. Directions for future research that build upon the current study were described. Indeed, identifying emotion regulation as a predictor of adolescent crime has the potential to enhance current crime prevention efforts and clinical treatments for juvenile offenders; this is based on the large amount of treatment literature, which documents that emotion regulation is malleable through treatment and prevention programming.

Fairness in machine learning with tractable models

Machine Learning techniques have become pervasive across a range of different applications, and are now widely used in areas as disparate as recidivism prediction, consumer credit–risk analysis and insurance pricing. The prevalence of machine learning techniques has raised concerns about the potential for learned algorithms to become biased against certain groups. Many definitions have been proposed in the literature, but the fundamental task of reasoning about probabilistic events is a challenging one, owing to the intractability of inference.The focus of this paper is taking steps towards the application of tractable probabilistic models to fairness in machine learning. Tractable probabilistic models have recently emerged that guarantee that conditional marginal can be computed in time linear in the size of the model.In particular, we show that sum product networks (SPNs) enable an effective technique for determining the statistical relationships between protected attributes and other training variables. We will also motivate the concept of “fairness through percentile equivalence”, a new definition predicated on the notion that individuals at the same percentile of their respective distributions should be treated equivalently, and this prevents unfair penalisation of those individuals who lie at the extremities of their respective distributions.We compare the efficacy of this pre-processing technique with an alternative approach that assumes an additive contribution. It was found that when these two approaches were compared on a data set containing the results of law school applicants, the percentile equivalence method reduced the average underestimation in the exam score of ethnic minority applicants black applicants at the bottom end of their conditional distribution by about a fifth. We conclude by outlining potential improvements to our existing methodology and suggest opportunities for further work in this field.

Survivorship Bias Mitigation in a Recidivism Prediction Tool

Survivorship bias is the fallacy of focusing on entities that survived a certain selection process and overlooking the entities that did not. This common form of bias can lead to wrong conclusions. AI Fairness 360 is an open-source toolkit that can detect and handle bias using several mitigation techniques. However, what if the bias in the dataset is not bias, but rather a justified unbalance? Bias mitigation while the “bias” is justified is undesirable, since it can have a serious negative impact on the performance of a prediction tool based on machine learning. In order to make well-informed product design decisions, it would be appealing to be able to run simulations of bias mitigation in several situations to explore its impact. This paper describes the first results in creating such a tool for a recidivism prediction tool. The main contribution is an indication of the challenges that come with the creation of such a simulation tool, specifically a realistic dataset.

Predicting youth reoffending after incarceration: added value of protective factors and heart rate variability

ABSTRACT This study examined a biopsychosocial approach on risk assessment in a clinical sample of youth offenders. In search of enhancing the validity of prediction of recidivism through risk factors alone, the added value of protective and neurobiological factors was measured. In 209 male youth offenders (age 15-24), risk and protective factors were assessed with the Structured Assessment of Violence in Youth (SAVRY) and the Structured Assessment of Protective Factors for violence risk-Youth Version (SAPROF-YV). Autonomic nervous system (re)activity was assessed, and cortisol and testosterone levels were measured in saliva. Recidivism data were obtained from official criminal records. As expected, risk factors alone provided moderate predictive validity for general and violent recidivism. Incorporating protective factors and Heart Rate Variability (HRV) reactivity significantly improved prediction models. Risk assessment may gain by adopting a broader, biopsychosocial perspective. Including neurobiology and protective factors in risk assessment could improve release decision-making, offer guidance for better tailored interventions, and enhance chances of successful community reintegration.

Testing the utility of the psychopathy construct for predicting criminal recidivism among detained girls

Few studies have scrutinized the prospective relation between psychopathy and criminality in detained girls. Consequently, it is not well known if the psychopathy construct adds to the prediction of recidivism over other risk factors, such as conduct disorder and past criminality. To address this research gap, the current study examined data from 302 detained girls (M age = 16.2). Psychopathy total and component (i.e., narcissism, callous-unemotional, and impulsivity) scores were derived from the self-report version of the Antisocial Process Screening Device (APSD). Latent profile analysis was used to identify girls with high scores on the three components (tentatively labeled ‘putative psychopathic personality’). Five youth recidivism outcomes were measured (i.e., violent, serious non-violent, drug, total, and versatile), based on arrest charges that occurred before girls were 18 years of age. With a few exceptions, neither the ASPD total nor the APSD component scores contributed to the prediction of the recidivism outcomes. Girls with a putative psychopathic personality also were not at increased risk for recidivism. Findings overall suggest that the psychopathy construct should not be used for risk assessment purposes among detained girls, at least not when assessed via the self-report version of the APSD.

Dynamic Appraisal of Intimate Partner Violence Risk and Need: Results From an Outpatient Treatment Program

This study examined the psychometric, predictive, and dynamic properties of intimate partner violence (IPV) risk. The sample consisted of 88 men attending an outpatient IPV correctional program. The Ontario Domestic Assault Risk Assessment (ODARA) was rated at pretreatment using participant files. The Spousal Assault Risk Assessment–Version 3 (SARA-V3) was rated at pre- and posttreatment using collateral information (e.g., facilitator ratings, files) and participant questionnaires. Recidivism data were obtained from a court database with an average follow-up of 15 months. The SARA-V3 and ODARA demonstrated strong convergent validity and predicted violent and general recidivism with moderate to high accuracy; SARA-V3 posttreatment ratings incremented the ODARA in the prediction of recidivism, yet not vice versa. Noncompleters were higher risk and had higher recidivism rates. Changes on the SARA-V3’s Perpetrator Risk Factors domain were significantly associated with decreased recidivism in bivariate analyses and some change associations remained significant with stringent controls for risk. Implications for risk assessment/management, service planning, and future research are discussed.

Does Reassessment Improve Prediction? A Prospective Study of the Sexual Offender Treatment Intervention and Progress Scale (SOTIPS)

This prospective study examined the predictive validity of the Sex Offender Treatment Intervention and Progress Scale (SOTIPS; McGrath et al., 2012), a sexual recidivism risk/need tool designed to identify dynamic (changeable) risk factors relevant to supervision and treatment. The SOTIPS risk tool was scored by probation officers at two sites (n = 565) for three time points: near the start of community supervision, at 6 months, and then at 12 months. Given that conventions for analyzing dynamic prediction studies have yet to be established, one of the goals of the current paper was to demonstrate promising statistical approaches for the analysis of longitudinal studies in corrections. In most analyses, static SOTIPS scores predicted all types of recidivism (sexual, violent, and general [any]). Dynamic SOTIPS scores, however, only improved the prediction of general recidivism, and only when the analyses with the greatest statistical power were used (Cox regression with time dependent covariates).

Stalking Recidivism: A Comparison of Operational Definitions.

The criminal offense of stalking is somewhat different to other offenses due to the repetitive, innocuous, and often multifaceted nature of the crime. Given that stalking constitutes a number of different behaviors, such as violence and threats, research on stalking recidivism becomes difficult as recidivism can be defined in a number of ways. This study utilized a dataset of Western Australia Police Force incident reports, comprising a sample of 404 stalking offenders. Survival curves and a binomial logistic regression were used to determine time to recidivism and predictors of recidivism, using four different definitions of recidivism. Predictor variables included age of the offender, prior history of criminal charges, and offender ethnicity. The four definitions ranged from narrow (a new stalking charge) to broad (any new criminal charge). The results of the study show that stalkers reoffend quickly, however our understanding of how fast and which offender characteristics predict recidivism, is dependent on how we define recidivism. This highlights the importance of considering how stalking recidivism is defined in future works and may explain current differences in stalking recidivism findings.

Neighborhood Risk Factors for Recidivism: For Whom Do They Matter?

Justice-involved people vary substantially in their risk of re-offending. To date, recidivism prediction and prevention efforts have largely focused on individual-level factors like antisocial traits. Although a growing body of research has examined the role of residential contexts in predicting re-offending, results have been equivocal. One reason for mixed results may be that an individual’s susceptibility to contextual influence depends upon his or her accumulated risk of re-offending. Based on a sample of 2,218 people on probation in San Francisco, California, this study draws on observational and secondary data to test the hypothesis that individual risk moderates the effect of neighborhood factors on recidivism. Results from survival analyses indicate that individual risk interacts with neighborhood concentrated disadvantage and disorder — these factors increase recidivism among people relatively low in individual risk, but not those at higher risk. This is consistent with the disadvantage saturation perspective, raising the possibility that some people classified as low risk might not recidivate but for placement in disadvantaged and disorderly neighborhoods. Ultimately, residential contexts “matter” for lower risk people and may be useful to consider in efforts to prevent recidivism.

Monitoring changes in risk of reoffending: A prospective study of 632 men on community supervision.

Few studies have examined how much individuals change on intermediate targets of risk to reoffend. Even fewer studies have examined the extent to which change on such measures predict reoffending. Establishing the validity of intermediate measures requires a multistep approach that (a) assesses the reliability of the change, (b) assesses change using statistical analyses that can account for measurement error, and (c) examines the extent to which change on these intermediate measures predict reoffending. The current study examined the validity of an intermediate measure of risk to reoffend scored by community supervision officers (i.e., ACUTE-2007) in a large sample of men convicted of sexually motivated offenses (N = 632). We found that risk to reoffend changes across time, the pattern of change varies across individuals, risk levels can predict different patterns of change, and that the best predictors of recidivism are the latest score or a rolling average of scores. Community supervision can use recent information concerning the community adjustment of their clients to predict recidivism. Best practice includes updating assessments and adjusting supervision practices based on their clients' most recent assessment, or the average of previous assessments. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Neighborhood Risk Factors for Recidivism: For Whom do they Matter?

Justice-involved people vary substantially in their risk of reoffending. To date, recidivism prediction and prevention efforts have largely focused on individual-level factors like antisocial traits. Although a growing body of research has examined the role of residential contexts in predicting reoffending, results have been equivocal. One reason for mixed results may be that an individual's susceptibility to contextual influence depends upon his or her accumulated risk of reoffending. Based on a sample of 2218 people on probation in San Francisco, California, this study draws on observational and secondary data to test the hypothesis that individual risk moderates the effect of neighborhood factors on recidivism. Results from survival analyses indicate that individual risk interacts with neighborhood concentrated disadvantage and disorder-and these factors increase recidivism among people relatively low in individual risk, but not those at higher risk. This is consistent with the disadvantage saturation perspective, raising the possibility that some people classified as low risk might not recidivate but for placement in disadvantaged and disorderly neighborhoods. Ultimately, residential contexts "matter" for lower risk people and may be useful to consider in efforts to prevent recidivism.