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

2016 ◽  
Vol 34 (18) ◽  
pp. 3780-3806 ◽  
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.

Using behavioural manifestations of dynamic risk factors to assess change in incarcerated sexual offenders

2021 ◽  
Vol 2 (1) ◽  
pp. 1-20
Author(s):  
Tamara Sweller ◽  
◽  
Stuart Thomas ◽  
Michael Daffern ◽  
◽  
...  
Keyword(s):  
Risk Factors ◽  
Psychological Adjustment ◽  
Sexual Offenders ◽  
Social Adjustment ◽  
Self Report ◽  
Change Over Time ◽  
Dynamic Risk Factors ◽  
Dynamic Risk ◽  
Measure Change ◽  
Over Time

This study investigated change in behavioural manifestations of dynamic risk factors, in a sample of adult male sexual offenders who completed a custody-based treatment program. A checklist was developed to monitor and determine change in the frequency of behavioural manifestations of dynamic risk factors and prosocial equivalent behaviours. Offenders and custodial staff completed the checklist once each week for the duration of the offender’s period of treatment (range = 26-69 weeks, M = 45). Checklist scores were aggregated into domains based on the organisation of the Risk for Sexual Violence Protocol (Psychological Adjustment; Social Adjustment; Mental Disorder; Manageability). Change over time for individuals and the group was evaluated. Results showed an increase in positive behaviour in all domains, but there was only a decrease in risk-related manifestations in Psychological Adjustment, and this was only according to offenders. Offender self-report and staff observations were compared, revealing different perceptions of change. Using a behavioural checklist that incorporates self-report and observer data to measure change may provide a comprehensive measure of change over time.

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

2011 ◽  
Vol 56 (6) ◽  
pp. 856-876 ◽  
Author(s):  
Leslie Helmus ◽  
Kelly M. Babchishin ◽  
Julie Blais
Keyword(s):  
Risk Factors ◽  
Sex Offenders ◽  
Predictive Accuracy ◽  
Self Regulation ◽  
Community Supervision ◽  
Relationship Stability ◽  
Dynamic Risk Factors ◽  
Dynamic Risk ◽  
Aboriginal 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.

scholarly journals High-Risk Violent Prisoners’ Patterns of Change on Parole on the DRAOR’s Dynamic Risk and Protective Factors

2017 ◽  
Vol 45 (3) ◽  
pp. 340-363 ◽  
Author(s):  
Devon L. L. Polaschek ◽  
Julia A. Yesberg
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Protective Factors ◽  
Psychological Treatment ◽  
Similar Rate ◽  
Dynamic Risk Factors ◽  
Dynamic Risk ◽  
Two Samples ◽  
Dynamic Risk Assessment ◽  
Rehabilitative Intervention

Few studies have examined change after treatment completion; such investigations can enhance our understanding of how a rehabilitative intervention leads to reduced recidivism. The current study uses growth curve modeling to investigate change in dynamic risk factors in the community, following two samples of high-risk violent men for up to 12 months on parole. While in prison, one sample had completed intensive psychological treatment, whereas the other completed no programs or briefer programs. As expected, based on Dynamic Risk Assessment for Offender Re-Entry (DRAOR) scores, intensive program completers entered the community with higher protective and lower stable and acute dynamic factors, and showed less variability on acute risk factors, as did all of those with better initial scores. But the two samples improved at a similar rate over the course of parole. Those with initially poorer scores changed less on parole except for protective factors; those with stronger initial protective scores showed less change.

scholarly journals Applying the Criminal Narrative Experience Framework to Young Offenders

2018 ◽  
Vol 62 (13) ◽  
pp. 4091-4107 ◽  
Author(s):  
Maria Ioannou ◽  
John Synnott ◽  
Emma Lowe ◽  
Calli Tzani-Pepelasi
Keyword(s):  
Risk Factors ◽  
Young People ◽  
Living Arrangements ◽  
Personal Relationships ◽  
Young Offenders ◽  
Dynamic Risk Factors ◽  
Space Analysis ◽  
Smallest Space Analysis ◽  
Dynamic Risk ◽  
First Time

The present study applied the Criminal Narrative Experience for the first time with young offenders ( N = 23). The analysis was based on young people serving a community sentence and attending a Youth Offending Team. Participants completed questionnaires relating to their roles and emotions during a typical offence and data were examined with Smallest Space Analysis (SSA) to identify if the themes were replicated. Three themes were identified: Calm Professional, Elated Hero, and a combined theme of Distressed Revenger and Depressed Victim. Correlation indicated links between Narrative Experience and static and dynamic risk factors. Findings suggest that the Calm Professional theme correlates with Neighbourhood risk factors, the Elated Hero with Attitudes to Offending, and the Distressed Revenger/Depressed Victim theme with Living Arrangements and Family and Personal Relationships. Potential reasons for identifying three rather than four themes with this sample are discussed. Implications of findings in preventing reoffending are highlighted.

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

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.

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

2016 ◽  
Vol 4 (16) ◽  
pp. 1-408 ◽  
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.

Psychological Resilience Provides No Independent Protection From Suicidal Risk

Crisis ◽  
2016 ◽  
Vol 37 (2) ◽  
pp. 130-139 ◽  
Author(s):  
Danica W. Y. Liu ◽  
A. Kate Fairweather-Schmidt ◽  
Richard Burns ◽  
Rachel M. Roberts ◽  
Kaarin J. Anstey
Keyword(s):  
Risk Factors ◽  
Well Being ◽  
Current Status ◽  
Psychological Resilience ◽  
Cross Sectional ◽  
Life Project ◽  
Resilience Factors ◽  
First Time

Abstract. Background: Little is known about the role of resilience in the likelihood of suicidal ideation (SI) over time. Aims: We examined the association between resilience and SI in a young-adult cohort over 4 years. Our objectives were to determine whether resilience was associated with SI at follow-up or, conversely, whether SI was associated with lowered resilience at follow-up. Method: Participants were selected from the Personality and Total Health (PATH) Through Life Project from Canberra and Queanbeyan, Australia, aged 28–32 years at the first time point and 32–36 at the second. Multinomial, linear, and binary regression analyses explored the association between resilience and SI over two time points. Models were adjusted for suicidality risk factors. Results: While unadjusted analyses identified associations between resilience and SI, these effects were fully explained by the inclusion of other suicidality risk factors. Conclusion: Despite strong cross-sectional associations, resilience and SI appear to be unrelated in a longitudinal context, once risk/resilience factors are controlled for. As independent indicators of psychological well-being, suicidality and resilience are essential if current status is to be captured. However, the addition of other factors (e.g., support, mastery) makes this association tenuous. Consequently, resilience per se may not be protective of SI.

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