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.

scholarly journals Beyond dynamic risk factors: Towards a comprehensive explanation of offending

2021 ◽  
Author(s):  
◽  
Roxanne Heffernan
Keyword(s):  
Risk Factors ◽  
Causal Explanation ◽  
Individual Characteristics ◽  
Theoretical Research ◽  
Future Research ◽  
Clear Understanding ◽  
Dynamic Risk Factors ◽  
Dynamic Risk ◽  
Frequent Use ◽  
Wide Range

<p>The current conceptualisation of dynamic risk factors (DRF) for criminal offending is problematic. There have been significant conceptual issues highlighted in this domain, however, until recently addressing these has not been a priority for researchers. Instead, research has predominantly focused on the success of DRF in predicting reoffending and the effectiveness of treatment programmes that target these factors. DRF are typically defined as aspects of individuals and their environments that are associated with an increased likelihood of reoffending, and they are widely considered ‘plausible causes’ of criminal behaviour. It is acknowledged that this definition encompasses a wide range of individual characteristics, social processes, behaviours, and environmental features, and that these vary in their ability to explain and predict offending. The more recent interest in features that reduce risk has prompted similar discussions about the concept of protective factors (PF). Given the frequent use of, and interest in, these foundational concepts it is timely to investigate them in depth, and to address two key issues. First, both DRF and PF are broad category labels that encompass a diverse (and largely unspecified) range of psychological and contextual features and processes. Second, without a clear understanding of what exactly these constructs are, it is difficult to effectively link them to correctional research and practice. I will begin this thesis by setting out the problems with the reliance on DRF to explain offending. I will do this by exploring recent empirical findings concerning their relationship with recidivism and outlining numerous conceptual problems which make DRF poor candidates for causal explanation. I will then suggest a shift in focus, from these crime correlates to human nature and agency, and argue that this perspective is essential in explaining any behaviour. I will present a preliminary model based on agency and demonstrate the utility of this perspective in reconceptualising DRF as aspects of goal-directed behaviour. Next, I will develop a framework for continuing this theoretical research and adding depth to theories of agency. Finally, I will discuss the implications of agency theories for forensic interventions, including their integration with widely used rehabilitation models. I will conclude with an evaluation of the approaches developed throughout this thesis and make some suggestions for future research. This research holds promise in directing the field away from the otherwise inevitable theoretical ‘dead end’.</p>

scholarly journals Understanding the Latent Structure of Dynamic Risk: Seeking Empirical Constraints on Theory Development Using the VRS-SO and the Theory of Dynamic Risk

Sexual Abuse ◽  
2021 ◽  
pp. 107906322110028
Author(s):  
Mark E. Olver ◽  
David Thornton ◽  
Sarah M. Beggs Christofferson
Keyword(s):  
Risk Factors ◽  
Factor Model ◽  
Theory Development ◽  
Latent Structure ◽  
Violence Risk ◽  
Dynamic Risk Factors ◽  
Sexual Offenses ◽  
Dynamic Risk ◽  
Item Level ◽  
Key Issues

The present study is part of a larger project aiming to more closely integrate theory with empirical research into dynamic risk. It seeks to generate empirical findings with the dynamic risk factors contained in the Violence Risk Scale—Sexual Offense version (VRS-SO) that might constrain and guide the further development of Thornton’s theoretical model of dynamic risk. Two key issues for theory development are (a) whether the structure of pretreatment dynamic risk factors is the same as the structure of the change in the dynamic risk factors that occurs during treatment, and (b) whether theoretical analysis should focus on individual dynamic items or on the broader factors that run through them. Factor analyses and item-level prediction analyses were conducted on VRS-SO pretreatment, posttreatment, and change ratings obtained from a large combined sample of men ( Ns = 1,289–1,431) convicted and treated for sexual offenses. Results indicated that the latent structure of pretreatment dynamic risk was best described by a three-factor model while the latent structure of change items was two dimensional. Prediction analyses examined the degree to which items were predictive beyond prediction obtained from the broader factor that they loaded on. Results showed that for some items, their prediction appeared to be largely carried by the three broad factors. In contrast, other items seem to operate as funnels through which the broader factors’ predictiveness flowed. Implications for theory development implied by these results are identified.

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 Beyond dynamic risk factors: Towards a comprehensive explanation of offending

2021 ◽  
Author(s):  
◽  
Roxanne Heffernan
Keyword(s):  
Risk Factors ◽  
Causal Explanation ◽  
Individual Characteristics ◽  
Theoretical Research ◽  
Future Research ◽  
Clear Understanding ◽  
Dynamic Risk Factors ◽  
Dynamic Risk ◽  
Frequent Use ◽  
Wide Range

<p>The current conceptualisation of dynamic risk factors (DRF) for criminal offending is problematic. There have been significant conceptual issues highlighted in this domain, however, until recently addressing these has not been a priority for researchers. Instead, research has predominantly focused on the success of DRF in predicting reoffending and the effectiveness of treatment programmes that target these factors. DRF are typically defined as aspects of individuals and their environments that are associated with an increased likelihood of reoffending, and they are widely considered ‘plausible causes’ of criminal behaviour. It is acknowledged that this definition encompasses a wide range of individual characteristics, social processes, behaviours, and environmental features, and that these vary in their ability to explain and predict offending. The more recent interest in features that reduce risk has prompted similar discussions about the concept of protective factors (PF). Given the frequent use of, and interest in, these foundational concepts it is timely to investigate them in depth, and to address two key issues. First, both DRF and PF are broad category labels that encompass a diverse (and largely unspecified) range of psychological and contextual features and processes. Second, without a clear understanding of what exactly these constructs are, it is difficult to effectively link them to correctional research and practice. I will begin this thesis by setting out the problems with the reliance on DRF to explain offending. I will do this by exploring recent empirical findings concerning their relationship with recidivism and outlining numerous conceptual problems which make DRF poor candidates for causal explanation. I will then suggest a shift in focus, from these crime correlates to human nature and agency, and argue that this perspective is essential in explaining any behaviour. I will present a preliminary model based on agency and demonstrate the utility of this perspective in reconceptualising DRF as aspects of goal-directed behaviour. Next, I will develop a framework for continuing this theoretical research and adding depth to theories of agency. Finally, I will discuss the implications of agency theories for forensic interventions, including their integration with widely used rehabilitation models. I will conclude with an evaluation of the approaches developed throughout this thesis and make some suggestions for future research. This research holds promise in directing the field away from the otherwise inevitable theoretical ‘dead end’.</p>

Prison Climate and Its Role in Reducing Dynamic Risk Factors During Offender Treatment

2018 ◽  
Vol 62 (14) ◽  
pp. 4609-4621 ◽  
Author(s):  
Joanna Stasch ◽  
Dahlnym Yoon ◽  
Julia Sauter ◽  
Joscha Hausam ◽  
Klaus-Peter Dahle
Keyword(s):  
Risk Factors ◽  
Empirical Finding ◽  
Offender Treatment ◽  
Offender Rehabilitation ◽  
Treatment Motivation ◽  
Dynamic Risk Factors ◽  
Dynamic Risk ◽  
Positive Treatment ◽  
Relationship Factors ◽  
Positive Climate

Although several offender treatment experts have suggested that therapeutic relationships play an important role in offender treatment, empirical finding supporting those arguments are scarce. The present study has therefore examined the relationship between prison climate, treatment motivation, and their influence on changes in risk factors in N = 215 inmates and detainees in four correctional facilities in Berlin, Germany. The inmates’ perception of prison climate significantly correlated with their attitudes towards treatment. More positive climate in terms of therapeutic hold and more positive treatment attitude in terms of trust in therapy were also the best predictors of stronger decreases in dynamic risk factors measured by the Level of Service Inventory–Revised (LSI-R). Our results support the importance of treatment relationship factors within the course of offender rehabilitation.

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.

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