Predictive Accuracy of Dynamic Risk Factors for Aboriginal and Non-Aboriginal Sex Offenders

Although Aboriginal offenders are overrepresented in Canadian prisons, there is limited research examining the extent to which commonly used risk factors and risk scales are applicable to Aboriginals. Aboriginal ( n = 88) and non-Aboriginal ( n = 509) sex offenders on community supervision were compared on the dynamic risk factors of STABLE-2007. Data on sexual, violent, any crime, and any recidivism (including breaches) were collected with an average follow-up of 3.4 years. Aboriginal offenders scored significantly higher than non-Aboriginal offenders on STABLE-2007 total scores and on several items measuring general criminality. STABLE-2007 did not significantly predict recidivism with Aboriginal offenders (although it did for non-Aboriginals). The general antisociality items were generally significantly less predictive for Aboriginals than non-Aboriginals, whereas items assessing sexual self-regulation and relationship stability predicted similarly for both groups. These exploratory results suggest that Aboriginal sex offenders are a higher-needs group but that some STABLE-2007 items are not predictive with this population.

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The Application of Network Analysis to Dynamic Risk Factors in Adult Male Sex Offenders

Clinical Psychological Science ◽

10.1177/2167702620901720 ◽

2020 ◽

Vol 8 (3) ◽

pp. 539-554 ◽

Cited By ~ 3

Author(s):

Jan Willem van den Berg ◽

Wineke Smid ◽

Jolanda J. Kossakowski ◽

Daan van Beek ◽

Denny Borsboom ◽

...

Keyword(s):

Risk Factors ◽

Network Analysis ◽

Sex Offenders ◽

Adult Male ◽

Sexual Contact ◽

Central Position ◽

Dynamic Risk Factors ◽

Dynamic Risk ◽

Male Sex ◽

Male Sex Offenders

Although dynamic risk factors are considered important in the assessment and treatment of adult male sex offenders, little is known about their interrelationships. We apply network analysis to assess their associations and to provide an analysis of their shortest pathways to sexual and violent (including sexual contact) recidivism. Analyses revealed a central position for general rejection/loneliness (in all networks), poor cognitive problem solving (in networks containing sexual or violent—including sexual contact—recidivism), and impulsive acts (only in the network including sexual recidivism). These variables represented links between clusters of dynamic risk factors composed of factors relating to sexual self-regulation, emotionally intimate relationships, antisocial traits, and self-management. Impulsive acts showed the strongest independent association with sexual and violent (including sexual contact) recidivism.

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A Dynamic Risk Factors–Based Typology of Sexual Offenders

International Journal of Offender Therapy and Comparative Criminology ◽

10.1177/0306624x16629399 ◽

2016 ◽

Vol 61 (14) ◽

pp. 1623-1647 ◽

Cited By ~ 4

Author(s):

Ana Martínez-Catena ◽

Santiago Redondo ◽

Nina Frerich ◽

Anthony R. Beech

Keyword(s):

Risk Factors ◽

Sex Offenders ◽

Sexual Offenders ◽

Child Molesters ◽

Criminal History ◽

Correctional Facilities ◽

Dynamic Risk Factors ◽

Dynamic Risk ◽

Criminogenic Needs ◽

The One

The purpose of this article was to develop an Spanish psychometric typology of sexual offenders taking into account dynamic risk factors. The sample comprised 94 sex offenders imprisoned in Spain (52 rapists and 42 child molesters). The analysis yielded two different offender categories based on the subjects’ criminogenic needs level (high and low). The results also showed that social desirability has a strong influence on the developed typologies, whereas the offence type, sociodemographic characteristics, and criminal history do not. A dynamic risk factors typology, such as the one proposed here, could help criminal and correctional facilities to fulfill their remit. It could also be useful for linking treatment intensity to offenders’ criminogenic needs, as well as providing a platform for recidivism risk assessments.

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The conceptualization of dynamic risk factors in child sex offenders: An agency model

Aggression and Violent Behavior ◽

10.1016/j.avb.2015.07.001 ◽

2015 ◽

Vol 24 ◽

pp. 250-260 ◽

Cited By ~ 28

Author(s):

Roxanne Heffernan ◽

Tony Ward

Keyword(s):

Risk Factors ◽

Sex Offenders ◽

Agency Model ◽

Dynamic Risk Factors ◽

Dynamic Risk

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Predictive Power of Dynamic Risk Factors in the Finnish Risk and Needs Assessment Form Compared to Static Predictors

10.31234/osf.io/v5uq3 ◽

2018 ◽

Author(s):

Benny Salo ◽

Toni Laaksonen ◽

pekka santtila

Keyword(s):

Machine Learning ◽

Risk Factors ◽

Needs Assessment ◽

Predictive Power ◽

Risk Assessments ◽

Dynamic Risk Factors ◽

Machine Learning Methods ◽

Dynamic Risk ◽

Violent Recidivism

We estimated the predictive power of the dynamic items in the Finnish Risk and Needs Assessment Form (RITA), assessed by case-workers, for predicting recidivism. These 52 items were compared to static predictors including crime committed, prison history, and age. We used two machine learning methods (elastic net and random forest) for this purpose and compared them with logistic regression. Participants were 746 men that had, and 746 that had not, reoffended during matched follow-up periods from 0.5 to 5.8 years. Both RITA-items and static predictors predicted general and violent recidivism well (AUC = .73 – .79), but combining them increased discrimination only slightly (ΔAUC = 0.01 – 0.02) over static predictors alone. Calibration was good for all models. We argue that the results show strong potential for the RITA-items but that development is best focused on improving usability for identifying treatment targets and for updating risk assessments.

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@myTabu—A Placebo Controlled Randomized Trial of a Guided Web-Based Intervention for Individuals Who Sexually Abused Children and Individuals Who Consumed Child Sexual Exploitation Material: A Clinical Study Protocol

Frontiers in Psychiatry ◽

10.3389/fpsyt.2020.575464 ◽

2021 ◽

Vol 11 ◽

Author(s):

Peter Fromberger ◽

Sonja Schröder ◽

Louisa Bauer ◽

Bruno Siegel ◽

Safiye Tozdan ◽

...

Keyword(s):

Risk Factors ◽

Clinical Trial ◽

Sexually Abused ◽

Sexual Exploitation ◽

Community Supervision ◽

Placebo Condition ◽

Web Based ◽

Dynamic Risk Factors ◽

Dynamic Risk ◽

Sexually Abused Children

Background: There is a high demand for evidence-based and cost-effective treatment concepts for convicted individuals who sexually abused children (ISAC) and individuals who consumed child sexual exploitation material (ICCSEM) under community supervision (CS). The @myTabu-consortium developed a guided web-based intervention for convicted ISAC and ICCSEM under CS consisting of six online modules targeting psychological meaningful risk factors. The study aims to evaluate the effectiveness of this guided web-based intervention in reducing dynamic risk factors and the risk to re-offend compared to a placebo condition. Furthermore, these dynamic risk factors are measured before and after every module to evaluate their individual effectiveness to reduce the respective risk factor as well as risk to re-offend. This clinical trial protocol describes the planned methods as well as the intervention concept.Methods: The methodological design is a placebo controlled randomized add-on trial (N = 582) with follow-ups at 8 points in time. The placebo condition controls for attention and expectation effects and comprises the same amount of modules with a comparable temporal effort as the experimental intervention. The trial is conducted as an add-on to community supervision as usually done. Primary outcomes are dynamic risk factors assessed by self-report risk assessment tools and officially recorded re-offenses.Discussion: To the best of our knowledge, the study is the first to compare the (cost-) effectiveness of a guided web-based intervention for convicted ISAC and ICCSEM under community supervision against a placebo condition. Methodological limitations (e.g., potential ceiling- or volunteers-effects) are discussed.Clinical Trial Registration: German Clinical Trial Register (DRKS 00021256). Prospectively registered: 24.04.2020.

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Antisocial Behavior and Victimization Over 2-Year Follow-Up in Subgroups of Childhood Arrestees

Journal of Interpersonal Violence ◽

10.1177/0886260516672052 ◽

2016 ◽

Vol 34 (18) ◽

pp. 3780-3806 ◽

Cited By ~ 2

Author(s):

Lieke van Domburgh ◽

Charlotte Geluk ◽

Lucres Jansen ◽

Robert Vermeiren ◽

Theo Doreleijers

Keyword(s):

Risk Factors ◽

High Risk ◽

Antisocial Behavior ◽

Self Report ◽

Childhood Onset ◽

High Group ◽

Dynamic Risk Factors ◽

Dynamic Risk ◽

First Time

Not only are childhood onset offenders at high risk of becoming serious persistent offenders, they are also at high risk of becoming victimized themselves. Furthermore, studies in the general population suggest that a combined perpetrator–victim group can be distinguished from a perpetrator-only and a victim-only group on individual and family risk factors. The current study investigated the co-occurrence of offending and victimization among first-time arrestees and the 2-year predictive value of previously found clusters of dynamic risk factors of offending. Childhood first-time arrestees ( N = 308; Mage = 10.3, SD = 1.45) were clustered into three groups based on dynamic risk factors of offending in the individual, peer, school, and family domains: a pervasive high, an externalizing intermediate, and a low problem group. Police records and self-report data on re-offending and victimization of these children were collected over a 2-year follow-up period. Compared with the low problem group, the prevalence of re-offending was higher in both the externalizing intermediate group and the pervasive high group. The pervasive high group was most likely to display co-occurring future antisocial behavior and victimization. These findings emphasize that attention should be paid to victimization in addition to future antisocial behavior, especially if additional internalizing and family problems are present. Furthermore, the differences in re-offending and victimization between subgroups of childhood onset offenders stress the need for specific interventions tailored to the risk profile of a child.

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Improving risk management for violence in mental health services: a multimethods approach

Programme Grants for Applied Research ◽

10.3310/pgfar04160 ◽

2016 ◽

Vol 4 (16) ◽

pp. 1-408 ◽

Cited By ~ 3

Author(s):

Jeremy W Coid ◽

Simone Ullrich ◽

Constantinos Kallis ◽

Mark Freestone ◽

Rafael Gonzalez ◽

...

Keyword(s):

Mental Health ◽

Risk Factors ◽

Risk Assessment ◽

Risk Management ◽

Research Programme ◽

Population Level ◽

Risk Assessments ◽

Dynamic Risk Factors ◽

Dynamic Risk

BackgroundMental health professionals increasingly carry out risk assessments to prevent future violence by their patients. However, there are problems with accuracy and these assessments do not always translate into successful risk management.ObjectivesOur aim was to improve the accuracy of assessment and identify risk factors that are causal to be targeted by clinicians to ensure good risk management. Our objectives were to investigate key risks at the population level, construct new static and dynamic instruments, test validity and construct new models of risk management using Bayesian networks.Methods and resultsWe utilised existing data sets from two national and commissioned a survey to identify risk factors at the population level. We confirmed that certain mental health factors previously thought to convey risk were important in future assessments and excluded others from subsequent parts of the study. Using a first-episode psychosis cohort, we constructed a risk assessment instrument for men and women and showed important sex differences in pathways to violence. We included a 1-year follow-up of patients discharged from medium secure services and validated a previously developed risk assessment guide, the Medium Security Recidivism Assessment Guide (MSRAG). We found that it is essential to combine ratings from static instruments such as the MSRAG with dynamic risk factors. Static levels of risk have important modifying effects on dynamic risk factors for their effects on violence and we further demonstrated this using a sample of released prisoners to construct risk assessment instruments for violence, robbery, drugs and acquisitive convictions. We constructed a preliminary instrument including dynamic risk measures and validated this in a second large data set of released prisoners. Finally, we incorporated findings from the follow-up of psychiatric patients discharged from medium secure services and two samples of released prisoners to construct Bayesian models to guide clinicians in risk management.ConclusionsRisk factors for violence identified at the population level, including paranoid delusions and anxiety disorder, should be integrated in risk assessments together with established high-risk psychiatric morbidity such as substance misuse and antisocial personality disorder. The incorporation of dynamic factors resulted in improved accuracy, especially when combined in assessments using actuarial measures to obtain levels of risk using static factors. It is important to continue developing dynamic risk and protective measures with the aim of identifying factors that are causally related to violence. Only causal factors should be targeted in violence prevention interventions. Bayesian networks show considerable promise in developing software for clinicians to identify targets for intervention in the field. The Bayesian models developed in this programme are at the prototypical stage and require further programmer development into applications for use on tablets. These should be further tested in the field and then compared with structured professional judgement in a randomised controlled trial in terms of their effectiveness in preventing future violence.FundingThe National Institute for Health Research Programme Grants for Applied Research programme.

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