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.

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.

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 Forensic application of static and dynamic risk factors: Is it the right time?

2021 ◽  
Vol 16 ◽  
Author(s):  
Brian Abbott
Keyword(s):  
Risk Factors ◽  
Sexual Violence ◽  
Sexual Offender ◽  
Risk Assessments ◽  
Future Research ◽  
Offender Treatment ◽  
Violence Risk ◽  
Dynamic Risk Factors ◽  
Dynamic Risk ◽  
Forensic Practice

It is common, accepted clinical practice to conduct risk assessments of individuals who commit sexual offenses using the combination of sexual violence risk actuarial measures and dynamic risk factors. This assessment approach has utility when identifying treatment targets, assessing progress in sexual offender treatment, and forming risk management plans. Little research has examined this method in forensic contexts such as deciding whether individuals who suffer from mental disorders are likely to engage in sexually dangerous behavior as defined by sexually violent predator or persons (“SVP”) involuntary civil confinement laws in the USA. In particular, it is uncertain whether the combination of sexual violence risk actuarial measures and dynamic risk factors (DRF) produces sufficiently reliable, relevant, and probative evidence for the trier of fact to properly evaluate the SVP legally defined likelihood of sexual dangerousness. This article explores the efficacy of combining actuarial measures of sexual violence risk and dynamic risk factors as applied in SVP risk assessments based on some commonly observed forensic practices among evaluators. Based on the analysis, recommendations for forensic practice and future research are offered.

Predictive Validity of the DYRA and SAFVR: New Zealand Police’s Family Violence Risk Assessment Instruments

2021 ◽  
pp. 009385482199752
Author(s):  
Apriel D. Jolliffe Simpson ◽  
Chaitanya I. Joshi ◽  
Devon L. L. Polaschek
Keyword(s):  
Risk Assessment ◽  
New Zealand ◽  
Family Violence ◽  
Predictive Validity ◽  
Family Relationship ◽  
Poor Performance ◽  
Dynamic Risk Factors ◽  
Dynamic Risk ◽  
Police Responses

Rapid access to accurate risk assessment information is essential for effective police responses to family violence (FV) calls for service. This study describes the predictive validity of the Dynamic Risk Assessment (DYRA) for family violence and Static Assessment of Family Violence Recidivism (SAFVR), currently in use by the New Zealand Police. We used 1,817 police reports of FV episodes to predict recurrence (i.e., repeat call for police service) over three follow-up periods. Regardless of follow-up, the DYRA and SAFVR each displayed poor ability to discriminate between episodes with and without a recurrence. Both instruments substantially over-predicted recurrence and performed relatively consistently across subsamples (e.g., intimate partners vs. other family relationship; aggressor gender, ethnicity, age). The especially poor performance of the DYRA suggests further research on dynamic risk factors and their contribution to police responses for FV is needed to make these instruments more useful for agencies working with families.

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.

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