Motivational Interviewing: Preparing People for Change

The history of risk assessment in criminal justice has been written on several occasions (Andrews & Bonta, 2003; Clements, 1996; Hollin, 2002). Here we assess progress since Andrews, Bonta, and Hoge’s (1990; Andrews, Zinger, et al., 1990) statement of the human service principles of risk-needresponsivity (RNR) and professional discretion. In those articles, the corrections-based terms of risk and need were transformed into principles addressing the major clinical issues of who receives treatment (higher risk cases), what intermediate targets are set (reduce criminogenic needs), and what treatment strategies are employed (match strategies to the learning styles and motivation of cases: the principles of general and specific responsivity). General responsivity asserts the general power of behavioral, social learning, and cognitive-behavioral strategies. Specific responsivity suggests matching of service with personality, motivation, and ability and with demographics such as age, gender, and ethnicity. Nonadherence is possible for stated reasons under the principle of professional discretion. Expanded sets of principles now include consideration of case strengths, setting of multiple criminogenic needs as targets, community-based, staff relationship and structuring skills, and a management focus on integrity through the selection, training, and clinical supervision of staff and organizational supports (Andrews, 2001). The review is conducted in the context of the advent of the fourth generation of offender assessment. Bonta (1996) earlier described three generations of risk assessment. The first generation (1G) consisted mainly of unstructured professional judgments of the probability of offending behavior. A

The Recent Past and Near Future of Risk and/or Need Assessment

The present meta-analysis integrates research from 1,435 studies on associations of parenting dimensions and styles with externalizing symptoms in children and adolescents. Parental warmth, behavioral control, autonomy granting, and an authoritative parenting style showed very small to small negative concurrent and longitudinal associations with externalizing problems. In contrast, harsh control, psychological control, authoritarian, permissive, and neglectful parenting were associated with higher levels of externalizing problems. The strongest associations were observed for harsh control and psychological control. Parental warmth, behavioral control, harsh control, psychological control, autonomy granting, authoritative, and permissive parenting predicted change in externalizing problems over time, with associations of externalizing problems with warmth, behavioral control, harsh control, psychological control, and authoritative parenting being bidirectional. Moderating effects of sampling, child's age, form of externalizing problems, rater of parenting and externalizing problems, quality of measures, and publication status were identified. Implications for future research and practice are discussed. (PsycINFO Database Record

Associations of parenting dimensions and styles with externalizing problems of children and adolescents: An updated meta-analysis.

The nascent field of fair machine learning aims to ensure that decisions guided by algorithms are equitable. Over the last several years, three formal definitions of fairness have gained prominence: (1) anti-classification, meaning that protected attributes---like race, gender, and their proxies---are not explicitly used to make decisions; (2) classification parity, meaning that common measures of predictive performance (e.g., false positive and false negative rates) are equal across groups defined by the protected attributes; and (3) calibration, meaning that conditional on risk estimates, outcomes are independent of protected attributes. Here we show that all three of these fairness definitions suffer from significant statistical limitations. Requiring anti-classification or classification parity can, perversely, harm the very groups they were designed to protect; and calibration, though generally desirable, provides little guarantee that decisions are equitable. In contrast to these formal fairness criteria, we argue that it is often preferable to treat similarly risky people similarly, based on the most statistically accurate estimates of risk that one can produce. Such a strategy, while not universally applicable, often aligns well with policy objectives; notably, this strategy will typically violate both anti-classification and classification parity. In practice, it requires significant effort to construct suitable risk estimates. One must carefully define and measure the targets of prediction to avoid retrenching biases in the data. But, importantly, one cannot generally address these difficulties by requiring that algorithms satisfy popular mathematical formalizations of fairness. By highlighting these challenges in the foundation of fair machine learning, we hope to help researchers and practitioners productively advance the area.

The Measure and Mismeasure of Fairness: A Critical Review of Fair Machine Learning.

The effects of correctional interventions on recidivism have important public safety implications when offenders are released from probation or prison. Hundreds of studies have been conducted on those effects, some investigating punitive approaches and some investigating rehabilitation treatments. Systematic reviews (meta-analyses) of those studies, while varying greatly in coverage and technique, display remarkable consistency in their overall findings. Supervision and sanctions, at best, show modest mean reductions in recidivism and, in some instances, have the opposite effect and increase reoffense rates. The mean recidivism effects found in studies of rehabilitation treatment, by comparison, are consistently positive and relatively large. There is, however, considerable variability in those effects associated with the type of treatment, how well it is implemented, and the nature of the offenders to whom it is applied. The specific sources of that variability have not been well explored, but some princ...

The Effectiveness of Correctional Rehabilitation: A Review of Systematic Reviews

Over the recent past there have been several meta-analyses and primary studies that support the importance of the risk principle. Oftentimes these studies, particularly the meta-analyses, are limited in their ability to assess how the actual implementation of the risk principle by correctional agencies affects effectiveness in reducing recidivism. Furthermore, primary studies are typically limited to the assessment of one or two programs, which again limits the types of analyses conducted. This study, using data from two independent studies of 97 correctional programs, investigates how adherence to the risk principle by targeting offenders who are higher risk and varying length of stay and services by level of risk affects program effectiveness in reducing recidivism. Overall, this research indicates that for residential and nonresidential programs, adhering to the risk principle has a strong relationship with a program’s ability to reduce recidivism.

https://mow.fd.org/sites/mow.fd.org/files/training/2015_CLE_Detention_and_Release/The%20Risk%20Principle%20in%20Action%20What%20Have%20We%20Learned%20article.pdf

The Risk Principle in Action: What Have We Learned From 13,676 Offenders and 97 Correctional Programs?

Over the last several decades, the use of risk/need assessments has had a great impact on correctional classification and treatment decisions. One instrument that is now being used by many correctional agencies in the United States is the Level of Service Inventory-Revised (LSI-R). Criticisms of the LSI-R include failure to consider physical and sexual abuse as risk factors and failure to modify the instrument for the assessment of female offenders. Using a sample of 442 offenders (317 male and 125 female), this research investigates (a) the validity of the LSI-R for both females and males and (b) the relationship between childhood abuse, the LSI-R, and recidivism rates. Analyses indicated that the LSI-R is a valid (predictive) instrument for this sample of female offenders and that a history of prior abuse fails to add to the prediction of reincarceration, once risk is controlled for using the LSI-R. Implications for further research are discussed.

Risk/Need Assessment, Offender Classification, and the Role of Childhood Abuse

The impetus of the drug court movement can be traced to a number of factors, such as the social and organizational costs of imprisonment and the literature surrounding the effectiveness of community-based treatment. Regardless of its origins, however, drug courts have altered the way in which court systems process drug cases and respond to drug-dependent offenders. Evaluations of U.S. drug courts are beginning to emerge, and although the outcome results are encouraging, not all courts are showing a reduction in rearrest rates. Despite the rapid expansion of drug courts, their growing prevalence, and popularity, little is known about the drug court model's ability to achieve its objectives in a variety of circumstances. This research adds to the literature on drug courts by examining the effect of drug court programming on multiple indicators of recidivism. Results of the study are mixed; however, the drug court treatment group did perform better when examining arrest for a drug-related offense.

https://www.uc.edu/content/dam/uc/ccjr/docs/articles/Effect_of_Drug_Court_Cincinnati.pdf

The Effect of Drug Court Programming on Recidivism: the Cincinnati Experience

https://www.uc.edu/content/dam/uc/ccjr/docs/articles/native_american_lsi.pdf

Exploring the validity of the Level of Service Inventory-Revised with Native American offenders.

Since the early 1990s, research, largely from a feminist perspective, has been devoted to identifying the “gender-specific needs” of delinquent girls. This article explores racial differences between girls and how these differences may affect the commission of violent behavior and self-injurious behavior. Self-report data were collected from 163 girls incarcerated in Ohio in 1998. Data were collected on a wide range of variables, including potentially criminogenic areas such as abuse, antisocial attitudes, drug use, type of parenting received, self-esteem, family experiences, and mental health. The findings indicate that some of these variables differ significantly by race. Furthermore, these criminogenic areas are investigated in order to test their relationship to self-reports of violence, self-injurious behavior, suicide attempts, and overall delinquency. These models are then examined by race with findings that demonstrate the fallacy of representing girls as a homogeneous group. Of particular interes...

Alexander M. Holsinger

Papers

The Risk Principle in Action: What Have We Learned From 13,676 Offenders and 97 Correctional Programs?

Risk/Need Assessment, Offender Classification, and the Role of Childhood Abuse

The Effect of Drug Court Programming on Recidivism: the Cincinnati Experience

Exploring the validity of the Level of Service Inventory-Revised with Native American offenders.

Differential Pathways to Violence and Self-Injurious Behavior: African American and White Girls in the Juvenile Justice System