Examining the Validity of Risk Assessments in Predicting General, Nonsexual Violence in Sexual Offenders

This study, published in Law and Human Behavior, provides implications with respect to the accurate assessment of institutional violence risk within a sex offender population. Below is a summary of the research and findings as well as a translation of this research into practice.

Featured Article | Law and Human Behavior | 2018, Vol. 42, No. 1, 13-25

Predictive Validity of HCR-20, START, and Static-99 Assessments in Predicting Institutional Aggression Among Sexual Offenders

Authors

Joel K. Cartwright, North Carolina State University and RTI International, Research Triangle Park, North Carolina
Sarah L. Desmarais, North Carolina State University
Justin Hazel and Travis Griffith, California Department of State Hospitals–Coalinga, Coalinga, California
Allen Azizian, California Department of State Hospitals–Coalinga, Coalinga, California, and California State University, Fresno

Abstract

Sexual offenders are at greater risk of nonsexual than sexual violence. Yet, only a handful of studies have examined the validity of risk assessments in predicting general, nonsexual violence in this population. This study examined the predictive validity of assessments completed using the Historical-Clinical-Risk Managment-20 Version 2 (HCR-20; Webster, Douglas, Eaves, & Hart, 1997), Short-Term Assessment of Risk and Treatability (START; Webster, Martin, Brink, Nicholls, & Desmarais, 2009), and Static-99R (Hanson & Thornton, 1999) in predicting institutional (nonsexual) aggression among 152 sexual offenders in a large secure forensic state hospital. Aggression data were gathered from institutional records over 90-day and 180-day follow-up periods. Results support the predictive validity of HCR-20 and START, and to a lesser extent, Static-99R assessments in predicting institutional aggression among patients detained or civilly committed pursuant to the sexually violent predator (SVP) law. In general,
HCR-20 and START assessments demonstrated greater predictive validity—specifically, the HCR-20 Clinical subscale scores and START Vulnerability total scores—than Static-99R assessments across types of aggression and follow-up periods.

Keywords

HCR-20, Static-99R, START, risk assessment, sexual offender

Summary of the Research

Background
“Structured risk assessment protocols have become integral components of the criminal justice system, as part of efforts to mitigate the potential risk to public safety, as well as strategies designed to rehabilitate offenders. One subgroup of offenders for which this is especially true is sexual offenders. Indeed, many jurisdictions mandate the use of risk assessment instruments with sexual offenders to assist in making decisions regarding placement, treatment, and other management concerns within the institutions. As a result, the use of instruments designed to inform assessments of institutional aggression among sexual offenders is common practice in correctional and forensic psychiatric settings” (p. 13).

“Accordingly, much empirical attention has been focused on testing the psychometric properties and establishing the validity of assessments completed using these instruments for predicting sexual violence in this population. Overall, findings of the extant research provide overwhelming support for the validity of risk assessment tools in predicting sexual recidivism . . . In contrast, less empirical attention has focused on the assessment of risk for general (nonsexual) aggression among sexual offenders, and institutional aggression specifically, which is the focus of the present study” (p. 14).

“While the importance of assessing risk for sexual recidivism is without question, sexual offenders demonstrate higher rates of nonsexual violent recidivism than rates of sexual recidivism . . . Many sexual offenders are hospitalized for very long periods, particularly under SVP laws. Thus, risk of aggression posed by sexual offenders against staff, peers, and property within the institution is a pressing safety and risk management concern. Consequently, the accurate assessment of institutional violence risk within sexual offenders would benefit case management and treatment, as well as assist in decisions regarding supervision and release. However, there has been limited evaluation of the validity of assessments completed using tools designed to forecast general (nonsexual) violence risk among sexual offenders” (p. 14).

“Meta-analytic research shows that many violence risk assessment instruments can have good validity in predicting violence. Research also shows that instruments developed for predicting violent offending perform better than those developed to predict sexual or general offending. When risk for general violence is assessed among sexual offenders, tools designed to evaluate risk for sexual recidivism, such as the Static-99R, are frequently used rather than tools designed to evaluate risk for general (nonsexual) violence. However, the HCR-20 and, most recently, the START are two risk assessment instruments now used to assess risk for general violence in this population” (p. 14).

Current Study
“This study examines the predictive validity of the HCR-20 and START assessments, as well as Static-99R assessment, in predicting institutional aggression in a sample of 152 male sexual offenders. Our specific aims were to: (a) examine the distribution of HCR-20, START, and Static-99R assessment scores and risk estimates; (b) evaluate concordance among the HCR-20, START, and Static-99R assessments; and (c) test the predictive validity of the HCR-20, START, and Static-99R assessments in predicting institutional aggression over 90 and 180 days” (p. 15).

Results
“Overall, almost a quarter of the sample engaged in some form of aggression during the 90-day follow-up period and over a third of the sample at 180-day follow-up . . . Across both START and HCR-20 assessments, very few patients were rated as high risk for violence (4.1% and 6.5%, respectively). Using the HCR-20, the majority were rated as low risk (67.4%); few were rated as moderate (26.1%) or high (6.5%). START final risk estimates showed a similar pattern of results: most participants were rated as low risk (83.7%), followed by moderate (12.2%) and high (4.1%). The Static-99R risk classifications demonstrated an inverse pattern of results, with more than half of participants classified as high risk (54.5%). Approximately one third (32.1%) were classified as moderate risk by the Static-99R, and relatively few (13.4%) as low” (p. 17-19).

“Associations were moderate to strong between START Strength total scores and Vulnerability total scores, and between HCR-20 subscale and total scores. Conversely, START Strength and Vulnerability total scores were weakly associated with Static-99R scores, if at all. The HCR-20 and START risk estimates showed moderate agreement. There were no instances in which a patient was identified as high risk on the HCR-20 or the START and low risk on the other instrument, and both HCR-20 and START assessments showed similar distributions of violence risk estimates” (p. 19).

“Over the 90-day follow-up period, HCR-20 total scores predicted all forms of aggression except physical aggression toward objects. The HCR-20 Clinical subscale score was the most predictive of the HCR-20 subscales, predicting all forms of aggression. All three HCR-20 subscale scores and total score predicted both any aggression and verbal aggression. START Strength total scores predicted all forms of aggression with the exception of physical aggression toward objects. START Vulnerability total scores predicted all forms of aggression. Static-99R total scores predicted any aggression and verbal aggression, but not physical aggression toward others or toward objects” (p. 19).

“We found significant discrimination among participants classified as low compared with moderate and high risk on the HCR-20 for any aggression, verbal aggression, and physical aggression toward others. For example, those rated high risk on the HCR-20 were almost 20 times more likely, and those rated as moderate risk were over 4 times more likely, to engage in any aggression compared with those rated as low risk. For physical aggression toward objects, there was only significant discrimination between those classified as low versus high risk, but not moderate versus high risk. For the START assessments, there was significant discrimination among participants classified as low compared with moderate and high risk for any aggression and verbal aggression. To demonstrate, those rated as high risk on the START were almost 15 times more likely, and those rated as moderate risk were over 7 times more likely, to engage in any aggression compared with those rated as low risk. For physical aggression toward objects, significant discrimination was only found for those identified as low versus moderate risk. START violence risk estimates did not discriminate among participants in the prediction of physical aggression toward others. Statistics for Static 99-R risk categories could not be calculated due to empty cells” (p. 19-20).

“Over the 180-day follow-up period, HCR-20 Clinical and Risk Management subscale scores, as well as the HCR-20 total score, predicted all outcomes, with one exception: Historical subscale scores were not associated with physical aggression toward objects. START Vulnerability total scores showed strong predictive validity across outcomes. START Strength total scores predicted any aggression and verbal aggression, but not physical aggression toward others or toward objects. Static-99R total scores showed moderate associations with any, verbal, and physical aggression toward others, but not physical aggression toward objects” (p. 20-21).

“HCR-20 risk estimates predicted all forms of aggression during this time frame, with the greatest discrimination appropriately found between those estimated as low and high risk. To demonstrate, those estimated as high risk using the HCR-20 were over 20 times more likely to engage in any or verbal aggression, over 70 times more likely to engage in property damage, and almost 15 times more likely to engage in aggression toward others compared with those classified as low risk. In contrast, we did not find discrimination between those rated low versus high risk on the START. However, those estimated as moderate risk using the START were approximately 8 times more likely to engage in any or verbal aggression, over 12 times as likely to engage in physical aggression toward objects, and over 3 times more likely to engage in physical aggression toward others when compared with those classified as low risk. For the Static-99R, ORs were significant for only one comparison: those classified as high risk on the Static-99R were almost 5 times more likely to engage in verbal aggression than those classified as low risk” (p. 21).

Translating Research into Practice

“Although we may have anticipated ceiling effects on the HCR-20 subscale and total scores, and START Vulnerability total scores, as well as floor effects for the START Strength total scores, in our relatively homogenous sample of male sexual offenders, this was not the case. Instead, assessments made use of the full range of possible scores and violence risk estimates for both HCR-20 and START ratings. This finding suggests that HCR-20 and START assessments may be useful for distinguishing between patients more or less likely to engage in aggressive behaviors even within a somewhat homogenous, high-risk population. They also suggest that HCR-20 and START assessments may be useful for informing supervision decisions and risk management strategies (e.g., identifying which patients require higher security levels)” (p. 21).

“Further, we found high rates of concordance between the results of HCR-20 and START assessments, but low rates of concordance among HCR-20 and START total scores with Static-99R total scores and high rates of discordance among HCR-20 and START total scores with Static-99R. These patterns of results are not surprising, given that both instruments were developed to predict violence risk over the short-to-medium term. In contrast, the Static-99R is designed to predict sexual recidivism over much longer time frames. Nonetheless, these findings indicate that the HCR-20 and START are measuring constructs and risks that are distinct from those measured by the Static-99R. And, as such, they support the use of the HCR-20 and START in addition to the use of the Static-99R in clinical practice with sexual offenders. Indeed, results of the predictive validity analyses provided stronger support for the use of the HCR-20 and START, compared with the Static-99R, in assessing risk for different forms of institutional aggression among sexual offenders” (p. 21-22).

“Consistent with prior research examining the predictive validity of the HCR-20, HCR-20 assessments performed well across outcomes. Like prior studies, however, the HCR-20 Historical subscale demonstrated the lowest levels of predictive validity of the HCR-20 assessment components and failed to predict physical aggression toward objects or others. In contrast, the HCR-20 Clinical subscale performed the best of the HCR-20 scales and predicted all forms of aggression at good or excellent levels. Generally, performance of HCR-20 assessments was greater for the prediction of aggression over the 180-day than 90-day follow-up period, demonstrating good to excellent predictive validity. Taken together, these findings add to the empirical evidence supporting the use of the HCR-20 for identifying violence risk over the medium term (i.e., 6 months) among sexual offenders” (p. 22).

“START assessments, including the Vulnerability and Strength total scores, as well as violence risk estimates, showed good to excellent validity in predicting any aggression and verbal aggression over both 90-day and 180-day follow-up periods. In fact, of all the assessments, the START Vulnerability total score outperformed any other HCR-20, START, or Static-99R subscale or total score. The extant literature varies on whether the START Strength or Vulnerability total scores perform better than the other, but the current results suggest greater validity of the Vulnerability than Strength total scores in the prediction of institutional aggression among sexual offenders. Strength total scores nonetheless demonstrated good validity in predicting any aggression, verbal aggression, and physical aggression, particularly over the 90-day follow-up period. This finding is consistent with the START’s intended 3-month assessment and prediction time frame and is similar to, if not slightly better than, findings reported in prior studies of START assessments in forensic psychiatric patients. Overall, findings support the use of the START in the assessment and management of risk for short-term institutional aggression among sexual offenders” (p. 22).

“Finally, the Static-99R assessments showed fair to good validity in predicting any aggression and verbal aggression, as well as physical aggression toward objects, but not physical aggression toward others. Further, although the Static-99R assessments demonstrated validity in predicting these forms of aggression, performance was consistently poorer compared with the performance of both the HCR-20 and START assessments. Prior research has found good validity of Static-99R assessments in predicting general aggression; however the majority of these studies have focused on community-based rather than institutional aggression, have aggregated sexual offenses with general offenses, and have investigated much longer follow-up periods. For these reasons, findings of the current study suggest that the Static-99R is most appropriately used for estimating sexual recidivism risk and that general violence risk assessment instruments, such as the HCR-20 or START, should be used to assess general aggression within sexual offenders” (p. 22).

Other Interesting Tidbits for Researchers and Clinicians

“This study supports the validity of the HCR-20, START, and to a lesser extent, the Static-99R assessments in predicting institutional aggression among patients detained or civilly committed pursuant to the SVP law. Typically, risk assessment instruments have shown lower levels of predictive validity in field studies compared with development studies. However, this does not appear to be the case in this sample of SVPs” (p. 23).

“This study adds to the body of literature supporting the application of structured violence risk assessments across diverse populations in the criminal justice system, and sexual offenders specifically. Beyond the assessment of risk for sexual recidivism, our findings suggest that general violence risk assessment instruments, such as the HCR-20 or START, have a place in the assessment and management of sexual offenders. Indeed, results indicate that instruments designed to assess sexual recidivism risk, and the Static-99R in particular, are limited in their ability to assess risk for general (nonsexual) violence. This is in keeping with the recommendations of the Static-99R authors to administer the Brief Assessment for Recidivism Risk – 2002R (BARR-2002R) for predicting nonsexual violence among sexual offenders, though this is not always done in practice. Consistent with the risk-need-responsivity model, findings suggest that using the HCR-20 or START to identify general violence risk among sexual offenders would benefit case management and treatment, as well as assist in decisions regarding supervision and release. Yet, the contributions of such assessments to clinical practice and, ultimately, violence prevention among sexual offenders remain to be tested in future research” (p. 23).

Join the Discussion

As always, please join the discussion below if you have thoughts or comments to add! To read the full article, click here.

Authored by Becca Cheiffetz

publicBecca Cheiffetz is a master’s student in the Forensic Psychology program at John Jay College of Criminal Justice. She graduated in 2015 from Sam Houston State University with a BS in Psychology and plans to continue her studies in a Clinical/Forensic Psychology PhD program in the near future. Her professional interests include providing clinical evaluations and treatment for individuals in prison as a prison psychologist and conducting forensic assessments for defendants in criminal court.

Sexually Abusive Clergy A Unique Subgroup of Sexual Offenders

Given the differences between sex offender subgroups, it may be important to consider offender types and their unique risk factors when developing sex offender management practices. This is the bottom line of a recently published article in the International Journal of Forensic Mental Health. Below is a summary of the research and findings as well as a translation of this research into practice.

Featured Article | International Journal of Forensic Mental Health | 2017, Vol. 16, No. 1, 58-68

Understanding Sexually Abusive Clergy as a Unique Offender Subgroup: Risk-based Comparisons Across the Course of Offending

Authors

Anthony D. Perillo, John Jay College and the Graduate Center, CUNY
Anniken L. W. Laake and Cynthia Calkins, John Jay College of Criminal Justice

Abstract

The current study compares offending trends of sexually abusive clergy (n = 1,428) to general sex offenders (n = 2,842) on risk measure items coded across the course of offending. Results suggest significant differences on most risk-relevant variables. Clergy were particularly more likely to have male victims, V = .62, 95% CI [.58, .65], and less likely to be married, V = .59, 95% CI [.56, .63], or use force, V = .76, 95% CI [.73, .79]. The magnitude of differences remained when matched on offense factors (e.g., male child acquaintance victims). Findings suggest sexually abusive clergy are a unique subgroup differing from general sex offenders on factors associated with recidivism.

Keywords

sexual abuse, clergy, sex offenders, offense trends

Summary of the Research

“Research examining sexually abusive clergy is relatively sparse, but some characteristics of sexually abusive clergy and their offenses have recently been identified. A study that examined a sample of 4,392 sexually abusive Catholic clergy found this group typically offended in their thirties, committed several types of sexual abuse, offended in private places such as the work place or home, conducted abusive behavior for more than a year, and had male victims aged 11-14. Likewise, in a study comparing clergy and non-clergy samples of individuals accused of child sexual abuse, the clergy group overall had a higher educational level, tended to be older, reported lower sexual drives, and reported fewer victims who again tended to be older and male” (p. 59).

“The distinct age range for victims of sexually abusive clergy initially added fuel to the discussion of additional clinical diagnoses of sexual attraction toward pubescent and post-pubescent minors. Some hypothesize that the late onset age of abusive behavior and the overrepresentation of male victims among sexually abusive clergy are greatly influenced by opportunity, namely the fact that children serving in church are typically male and that unsupervised contact with children often increase over the course of a clergy’s career. The extent to which these factors justify considering sexual abusive clergy as a distinct subgroup of offender is therefore in question” (p. 59).

“The unique religious and situational context of serving within the Church may also contribute to sexually abusive clergy as a unique subgroup. Being sworn to celibacy and having limited exposure to women as seminarians may negatively impact the psychosexual development of Catholic clergy. However, a study comparing cleric and non-cleric individuals accused of sex offenses, found that, when controlling for a number of demographic variables such as educational level, age, and marital status, offending patterns among clerics were similar to those of non-clerics in multiple ways. Overall, the early research on sexual abusive clergy leaves open the question of whether they are a unique subgroup of offenders” (p. 59).

Current Study

“The current study compared offender and offense characteristics of sexually abusive clergy to those of a group of general sex offenders to determine whether sexually abusive clergy appear to be a unique subgroup of offenders. Comparisons were further made between sexually abusive clergy and specific subsets of general sex offenders (those with only child victims, those with child acquaintance victims, and those with male child acquaintance victims) to examine whether differences between sexually abusive clergy and general sex offenders are better explained by considering these clergy as belonging to a specific (but already considered) subgroup of sex offenders” (p. 59-60).

“Data (N = 4,272) originated from two independent datasets, both based on archival data. The first dataset included records from active and former clergy with documented allegations of sexual abuse against children occurring from 1980-2002 (n = 1,428). The second dataset included records of male sex offenders incarcerated for a sexual offense and released from custody from 1996–2007 (n = 2,844). Group comparisons were based on items from the Static-99, Static-99R, and the Minnesota Sex Offender Screening Tool-Revised (MnSOST-R)” (p. 60-61).

Results

“Most likely impacted by the circumstances surrounding clergy life and working within the Catholic Church, the clergy sample exhibited little-to-no variance on several items. For example, no clergy victims were strangers. Other items with minimal variance for clergy include history of non-sexual violence, being younger than age 25 at time of offense, ever being married (or co-habitating with a partner for at least two years), and history of adolescent antisocial behavior. The minimal variance on these items can be attributed to both the circumstances of clergy life and a lack of available records on other items. For the general sample, variance of scores was observed on all risk items” (p. 62).

Overall group comparisons. “Compared to general sex offenders, sexually abusive clergy showed distinct patterns on most risk items measured, including all items on the Static-99/99R. Large effect sizes were revealed for three of the items from these measures: sex offenses, with clergy having significantly more offenses on record than general offenders; having a male victim, with a significantly larger portion of clergy having male victims; and ever being married, with significantly fewer clergy ever being married or living with a lover for at least two years. Another three items were observed to have medium effect sizes: clergy were significantly less likely to have history of non-sexual violence; significantly more likely to have an unrelated victim; and significantly less likely to have a stranger victim” (p. 62).

“For items from the MnSOST-R, clergy abusers presented with significantly different patterns on all but one item; there were no significant differences between clergy abusers and general offenders with regard to the number of different age groups offended against. Large effect sizes were observed for two MnSOST-R items: clergy were significantly less likely to have physically threatened or used physical force against victims, or to have committed multiple types of sexual acts against a single victim. Medium effect sizes were observed for four items: clergy were significantly less likely to have a history of adolescent antisocial behavior, substance abuse, or disciplinary action during an incarceration, and were significantly less likely to have offended against strangers, Finally, although there were only small effect sizes for offender age at first event, clergy were significantly older than general sex offenders at first documented offense, an average of approximately ten years” (p. 62).

“Although the clergy and general samples differed on the presence of most risk items, the overall trends did not appear to push heavily in one direction with regard to higher or lower risk for one group . . . More notable, however, was the split of risk items from different measures as a function of risk direction. Most of the items that differed in a direction of higher risk for clergy originated from the Static-99/99R. In contrast, most the items that differed in a direction of lower risk for clergy originated from the MnSOST-R” (p. 62-63).

Translating Research into Practice

“Results of the current study suggest sexually abusive clergy indeed differ from general sex offenders on offending patterns and personal characteristics included as actuarial sexual risk items . . . Several robust differences identified on the Static-99/99R (e.g., having male victims) appear to be influenced to some degree by contextual factors within the Church. One such difference is the increased number of victims for clergy, which may have been impacted by a lack of supervision for clergy, a lack of reporting of sexual abuse, and Church responses to abuse allegations that often granted continued unsupervised time with children. What remains unclear, however, is the extent that these findings would be different had these clergy abused outside the Church environment. For example, it is not surprising that the majority of victims for sexually abusive clergy are male (whereas most victims for general offenders were female), given that clergy are far more likely to have professional and unsupervised private time with males than females. It is unknown how significantly the rate of male victims would change were these clergy to have offended outside the Church” (p. 65).

“Results of the follow-up analyses suggest that aside from general victim characteristics, sexually abusive clergy are no more similar to different subsets of sex offenders with similar victims than they are to other sex offenders in general. Overall, from the perspective of factors included in actuarial risk assessment, the findings suggest sexually abusive clergy represent a unique subset of sex offenders that have demonstrated different offense patterns over their course of offending. As such, unique or altered considerations may be warranted when understanding clergy sexual abuse” (p. 65).

Other Interesting Tidbits for Researchers and Clinicians

“Although conclusions and recommendations for actuarial risk assessment with sexually abusive clergy cannot be drawn from the current study, the fact that the current analyses included factors used in risk assessment with general sex offenders lends itself to preliminary theorizing on the prospects of extending current actuarial risk instruments with sexually abusive clergy. Relative to sex offenders in general, sexually abusive clergy present with different patterns on variables included on currently used risk measures. Because these offender and offense variables contribute to overall scores on risk measures, the combination of these differences may create different sum score distributions and, in turn, markedly different pictures of risk for sexually abusive clergy” (p. 65-66).

“For example, stark differences such as sexually abusive clergy having a higher rate of offending against unrelated victims, having more victims, and having never been married would seemingly increase risk for future offending. In contrast, differences such as sexually abusive clergy having lower rates of using force, lower rates of non-sexual violence, and lower rates of substance abuse would seemingly decrease risk for future offending. The lack of variance for sexually abusive clergy on these variables suggests that sexually abusive clergy would likely be assessed with poor discrimination, hindering efforts to distinguish higher-risk clergy from lower-risk clergy” (p. 66).

“Changes from the Static-99 to the Static-99R may greatly impact the instrument’s utility with sexually abusive clergy. The revised scoring of offender age on the Static-99R, which lowered risk scores for older offenders, would be expected to both lower mean risk scores and increase the variance across sexually abusive clergy. Such changes may increase the instrument’s utility with this group, though the Static-99R’s validity with clergy is currently unknown. In addition, differences in the factors assessed on the Static-99/99R and the MnSOST-R may impact their use with clergy. The MnSOST-R includes more items related to general antisociality than the Static-99/99R, which appears to focus primarily on sex-related items. Given the minimal presence of (non-sexual) antisocial behavior among clergy in the current study and research suggesting sexual and social development issues among sexually abusive clergy, sexual and social deviancy would likely be more relevant to assessing sexual risk among clergy than general antisociality. The Static-99/ 99R, therefore, may ultimately be preferred over the MnSOST-R when assessing sexually abusive clergy” (p. 66).

Join the Discussion

As always, please join the discussion below if you have thoughts or comments to add!

Authored by Becca Cheiffetz

Becca Cheiffetz is a master’s student in the Forensic Psychology program at John Jay College of Criminal Justice. She graduated in 2015 from Sam Houston State University with a BS in Psychology and plans to continue her studies in a Clinical/Forensic Psychology PhD program in the near future. Her professional interests include providing clinical evaluations and treatment for individuals in prison as a prison psychologist and conducting forensic assessments for defendants in criminal court.

Precondition Model May Be Beneficial for Understanding Female Sex Offenders

Forensic Training AcademyThe Precondition Model, typically used with male sex offenders, is useful for understanding progression and motivation for female contact and noncontact sex offenders. This is the bottom line of a recently published article in International Journal of Forensic Mental Health. Below is a summary of the research and findings as well as a translation of this research into practice.

International Journal of Forensic Mental HealthFeatured Article | International Journal of Forensic Mental Health | 2016, Vol. 15, No. 1, 111-124

The Precondition Model as a Method for Developing Understanding of Female Contact and Non-Contact Sex Offending: A Single Case Study

 

Authors

Sophia Collins, School of Life and Medical Sciences, Department of Psychology and Sport Sciences, University of Hertfordshire, Hatfield, UK
Simon Duff, Mersey Forensic Psychology Service, Merseycare NHS, Liverpool, UK; The Centre for Forensic and Family Psychology, University of Nottingham, Nottingham, UK

Abstract

This research evaluates the use of an established model, typically used for understanding male sex offenders, to understand the behavior of a female sex offender. The Finkelhor (1984) Precondition Model of offending is used to provide a rare opportunity to explore the process of offending for a female contact and non-contact offender, whose offenses were against children. It reviews the efficacy of utilizing this model in the rehabilitation and collaborative risk management of a female sex offender. The results suggest that this approach can be applied to Internet and contact sex offenses to develop understanding of the progression of offending, including issues such as sexual arousal and the impact of a male co-perpetrator. In this case, the results indicate a post-intervention improvement in areas such as affect control, ability to maintain positive relationships, self-support, and reduced dissociation and dysfunctional sexual behavior. This project provides support for the development of a treatment approach that explores the individual nuances of female sex offending.

Keywords

Female, sex offender, treatment, precondition, model

Summary of the Research

“While research has begun to identify themes and trajectories within female sex offender characteristics, the reporting of these cases is still relatively rare in comparison to the male sex offender literature” (p.111). “Female offenders tend to be younger than their male counterparts, often experience financial issues, have experienced frequent and severe abuse themselves, and show high levels of emotional dependency, amongst other traits. They also tend to use less physical violence and more persuasion and coercion than males. It is not yet clear how these factors may be related to offending behavior nor what are the core issues to be addressed to reduce recidivism. However, there are many features that are shared between male and female offenders, but a recent review concludes that we are yet to reach an agreement on how to accurately conceptualize female offenders” (p. 112).

“The Finkelhor (1984) Precondition Model is described as one of the most promising etiological theories for use in the rehabilitation of sexual offenders, it has had an important role in both research and practice, and has been used as a framework for understanding aspects of male offending” (p. 112). “The model is based on research suggesting that in order for sexual offenses to occur the offender must pass through four planning stages: motivation to offend, overcoming internal inhibitions, overcoming external barriers, and overcoming victim resistance. These stages highlight both the intrapersonal (within perpetrator) and external factors relevant to the offending behavior” (p. 112). “A significant strength of the model is the way it relates a broad range of causal factors to the offense process, providing a useful framework for therapists. Indeed, it was selected for the present study based on this merit, as the model explores specific details of the offending behavior that can inform risk management strategies for the individual” (p. 113).

“The study aims were to increase awareness of a female perpetrator’s perspective of child sex offending and provide evidence regarding the relevance and efficacy of using the Precondition Model in the understanding, rehabilitation, and risk management of female sex offenders. There have been no previously published single case studies of female sex offenders using the Precondition Model.

The aims were to answer the following questions: Q1. Is the Finkelhor Precondition Model appropriate for the exploration of female noncontact (Internet) sex offenses? Q2: Can the Finkelhor Precondition Model be used to develop further understanding of the nature of female contact sex-offending behavior? Q3: Is the Finkelhor Precondition Model efficacious in the rehabilitation/risk management of a female contact and noncontact child sex offender?” (p.113).

“A single case design was utilized. The qualitative data gathered via the therapeutic intervention outlined in this report were analyzed retrospectively, along with quantitative outcome measures that had been administered pre- and post-intervention” (p.113). “The service-user was a female, aged 40–50 of White ethnicity. She had completed a custodial sentence imposed for offenses of sexual assault against a child under 13 years old, making indecent photographs of a child, and possessing indecent photographs of children” (p.113).

“Following an assessment interview, in which the service user’s motivation to engage with a further psychological intervention was established, the service-user engaged with 22 individual 50-minute sessions. Sessions took place at a community Forensic Psychology Service with expertise in the psychological treatment of male and female sex offenders and in the therapeutic use of the

Precondition Model. Sessions occurred weekly over an 8-month period, with allowance made for planned leave from therapy” (p. 114).

“The results demonstrate that the Precondition Model can be applied with a female contact and noncontact sex offender, providing a beneficial framework for the exploration of the offending behavior. The service-user in this case example was able to engage with the model and it provided a platform for empowering the service-user to identify risk factors and develop risk management strategies” (p.118).

“The results suggest that the Finkelhor (1984) Precondition Model can be utilized to explore the process of offending for noncontact (Internet) offending behavior” (p. 118). “In this case, the use of the Precondition Model illuminated several key themes in the development of this offending behavior. The service-user identified her sense of curiosity regarding the sexual abuse of children, which she linked to her own experience of early sexualization and the abuse of her own children by a male partner” (p. 119). “The service-user acknowledged how her curiosity and initial shock had developed into sexual arousal when viewing or thinking about abusive images” (p.119). “The use of the Precondition Model highlighted practical aspects of the Internet offending behavior, such as the use of passwords, secrecy, and taking advantage of other’s lack of knowledge. This created the opportunity to develop collaborative risk management strategies and encourage engagement with Probation-enforced rules around computer and Internet use” (p.119).

“The quantitative outcome measures used did highlight some significant and reliable change for the individual post-intervention. In terms of risk management, the improvement in areas such as affect control, ability to maintain positive relationships, the reduction of externalizing behaviors in reaction to painful internal states, reduced dissociation, improved self-identity and self-support and reduced dysfunctional sexual behavior is highly relevant” (p. 120). “Quantitative content analysis also illuminated the role of cognitive distortion in the selection, grooming, and abuse of the victim. For example, the abdication of responsibility, minimization and justification at the time of offending. Also highlighted was the impaired emotional regulation and interpersonal problems that motivated the offending. This created opportunity to explore and challenge these risk factors, while focusing on the service-user’s strengths and her innate capabilities to overcome these difficulties. This approach is recommended by [researchers] who advocate focus on positive states of mind, personal characteristics, and experiences that provide a viable alternative to the offending behavior” (p. 120).

 

Translating Research into Practice

“Although female sex offender treatment needs appear similar to those of male sex offenders it is crucial that treatment providers recognize gender-specific nuances in relation to those treatment needs. For example, in contrast to their male counterparts, female sex offenders tend to demonstrate an absence of beliefs associated with an entitlement to sexually abuse children and are often impacted by the negative environment created by a male co-perpetrator” (p. 112).

“Due to increasing recognition of the perpetration of sexual abuse by females, there is a need for services to provide suitable psychological interventions for the rehabilitation and risk management of sex offenders, both male and female. The Finkelhor (1984) Precondition Model is a well-established framework for exploring the process of offending and developing factors such as responsibility and empathy that reduce the risk of future offending behavior in males” (p. 121).

“It is widely recognized that group interventions add a beneficial dynamic in the rehabilitation of male offenders… However, the number of female sex offenders referred for psychological intervention in relation to their offenses is much reduced in comparison to males. Therefore, it will not always be possible, as in this case, for the group approach to be facilitated. It is therefore essential for services to consider the individual needs of female sex offenders, many of whom are likely to have experienced sexual abuse themselves. In this case the gender of the psychologist facilitating the intervention was carefully considered and collaboratively agreed with the service-user” (p. 121).

The following considerations are recommended for the “provision of gender informed services for this population: gender should be central to guiding women out of sexual offending; female-perpetrated sex offenses are more likely to occur in the context of a caregiving situation, and with a male co-perpetrator; these females generally present with an interrelated set of needs, for example victimization, traumatic history, and mental health needs; interventions should target deficits in interpersonal, self-regulation, and distress-tolerance skills and should assist females to establish and maintain pro-social, supportive, and equitable relationships” (p. 121).

“This case study provides a unique insight into the perspective of a female contact and noncontact sex offender in relation to her offending behavior. It also highlights the benefits of using the Precondition Model with a female to address both types of offending, including elaboration on underresearched issues such as progression from noncontact to contact offending and motivation” (p.122). “This study illuminates a number of limitations of the model itself, in particular the absence of focus on factors such as shame and identity. Therefore, a priority for future research must be the development of a framework for exploring the individual nuances of sexual offending that addresses both the cognitive and emotional factors of the offending. Furthermore, the development of suitable outcome measures that have been validated for female sex offenders will greatly support understanding in this field” (p. 122).

 

Other Interesting Tidbits for Researchers and Clinicians

“In addition, of interest in this case was the element of progression identified by the service-user. This included how the use of abusive images during sexual contact with her adult partner generated further interest in seeking and using abusive images. Also, how it encouraged discussion about how they could commit contact abuse themselves. This is in contrast to research into the progression from noncontact to contact offending of males, which largely suggests that the risk of progression is low“ (p.119).

“It would be of substantial benefit for the study to be replicated with additional female sex offenders. This would provide further insight into this underresearched group and allow for meaningful comparisons of the cognitive aspect of male and female sex offending. Future applications of this model would do well to be supported by collateral reports from other professionals in close contact with the service-user. In addition, replications of this study would reduce bias further by having coding schemes checked by completely independent reviewers” (p.122).

 

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Authored by Megan Bandford

Megan Banford is a master’s student in the Forensic Psychology program at John Jay College. She graduated in 2013 from Simon Fraser University with a B.A. (Honors) and hopes complete a PhD in clinical forensic psychology. Her main research interests include violence risk assessment and management, juvenile offenders and public policy.

Site Differences Impact Clinician Applications and Predictive Accuracy of the J-SOAP-II

Forensic-Training-AcademyThe J-SOAP-II should be used as part of a battery of risk assessment tools rather than in a strict actuarial manner for assessing future risk. This is the bottom line of a recently published article in International Journal of Forensic Mental Health. Below is a summary of the research and findings as well as a translation of this research into practice.

 

Featured Article | International Journal of Forensic Mental Health | 2015, Vol. 14, 56-65ijfmh

 

Predictive Validity of the J-SOAP-II: Does Accuracy Differ Across Settings?

Authors

Ricardo Martinez, Fordham University
Barry Rosenfeld, Fordham University
Keith Cruise, Fordham University
Jacqueline Martin, Hoboken University Medical Center

Abstract

Court and mental health workers are frequently asked to determine which juvenile sex offenders (JSOs) are most likely to reoffend. One instrument commonly used to guide decision making with JSOs is the Juvenile Sex Offender Assessment Protocol-II (J-SOAPII). However, research utilizing this instrument has often generated contradictory results, perhaps related to the types of samples studied. The current study sought to compare the predictive accuracy of the J-SOAP-II across two samples of JSOs (a medium-security correctional setting versus an unlocked residential sex offender treatment program). Although the overall predictive accuracy for identifying post-release arrests for sexual offenses (i.e., sexual recidivism) was modest (AUC = .64) and not statistically significant, differences emerged with regard to the accuracy of some individual scales and subscales. Similarly, while no significant differences in predictive accuracy were observed between the two study sites, a number of interesting findings were observed. These findings highlight the need to consider risk assessment measures in light of the setting in which they are used in order to maximize predictive accuracy and optimize treatment and dispositional decision making.

Keywords

sex offenders, juveniles, risk assessment, J-SOAP-II, recidivism

Summary of the Research

There have been mixed findings regarding the predictive validity of the Juvenile Sex Offender Assessment Protocol (J-SOAP-II). “This research is no doubt hindered by the small sample sizes used in most studies, and the low rates of sexual reoffending that are typically found. Nevertheless, it appears that the scale’s predictive utility is somewhat stronger with JSOs in less restrictive settings, whereas its use with institutionalized offenders being considered for release into the community may be questionable. However, none of the published studies to date have directly compared samples drawn from different types of correctional/treatment settings” (p.57).

“The current study sought to address this gap in the existing literature by comparing the predictive accuracy of the J-SOAP-II across two samples of JSOs, a medium-security correctional setting versus an unlocked residential sex offender treatment program. In addition, unlike much of the existing literature that has examined risk assessments conducted at the time of intake, this study examined risk of reoffense at the time of release from the facility” (p.57).

Overall, results were moderate but insignificant when examining predictive accuracy using J-SOAP-II total scores. “Stronger, but still moderate predictive accuracy was observed for the Dynamic summary scale and its components (Scales III and IV)…However, neither the Static summary scale nor its components (Scales I and II) significantly predicted sexual reoffending in the total sample…Predictive accuracy was generally weaker for non-sexual recidivism though these small effects were often significant. In fact, only Scale II (Impulsive/Antisocial Behavior) generated a medium effect size” (p.62)

“Despite some small differences in AUC estimates across the two study sites for the individual J-SOAP-II subscales, there were also no significant differences in predictive accuracy. Similarly, no site differences were observed with regard to general reoffending, as only Scale II was significantly associated with general reoffending and this association was roughly comparable for both study sites” (p.61).

Translating Research into Practice

Clinicians may be most successful using the J-SOAP-II as a tool to generally and systematically review relevant risk factors for treatment and intervention purposes. The modest findings of the predictive accuracy of the tool suggest that the J-SOAP-II may not be appropriate as a pure actuarial measure in terms of anchoring risk estimates on total, summary, or subscale scores. “Thus, the scale may have ample utility for its recommended uses, despite the limited utility in predicting reoffense among institutionalized JSOs when used as a set of “scores”” (p.64).

“Interestingly, although the J-SOAP-II manual suggests that Scale IV (Community Stability/Adjustment) be omitted for youth who are incarcerated or housed in a secure treatment facility at the time of the evaluation, ratings based on treatment records demonstrated some utility for Scale IV. Reliability for the scale (internal consistency and interrater) was adequate and internal consistency was stronger when total scores included the Scale IV items. In addition, JSOAP-II total scores that included Scale IV were somewhat stronger (though not significantly so) than those without Scale IV, and the Dynamic summary scale (which combines Scales III and IV) was superior (though again, not significantly) to Scale III alone. Thus, while the J-SOAP-II authors recommend omission of this scale for detained youth, these findings suggest that the scale may have utility even for these individuals” (p. 63).

Other Interesting Tidbits for Researchers and Clinicians

“Although far from definitive, these findings may reflect the greater intensity of sex offender treatment at PRTC, as this setting focused much more intensively on sex offender programming than did JTSB. The significantly lower scores on JSOAP-II Scale III (Intervention), reflecting fewer intervention-based risk factors, supports this hypothesis but is clearly insufficient to “test” the differences in treatment programming across the two sites” (p.63).

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Authored by Andrea Patrick5

Andrea Patrick is completing her M.A. in Forensic Psychology at John Jay College of Criminal Justice. In the future, she hopes to be directly working with forensic populations providing risk assessments, clinical evaluations as well as conducting research within the field.

SSPI Bolsters Validity for STABLE-2007’s Deviant Sexual Interest Items

DarkBlue-Forensic-Training-AcademyThe SSPI significantly added to the predictive accuracy of the STABLE-2007 in terms of deviant sexual interest in children while it did not bolster the Static-99R or Static-2002R. This is the bottom line of a recently published article in Law and Human Behavior. Below is a summary of the research and findings as well as a translation of this research into practice.

Featured Article | Law and Human Behavior | 2015, Vol. 39, No. 1, 35-43

lhbThe Screening Scale for Pedophilic Interests (SSPI): Construct, Predictive, and Incremental Validity

Authors

Leslie Helmus, Forensic Assessment Group, Ottawa, Ontario, Canada
Caoilte Ó Ciardha, University of Kent
Michael C. Seto, Royal Ottawa Health Care Group, Brockville, Ontario, Canada

Abstract

This study of 410 adult male sex offenders against children, using data from the Dynamic Supervision Project (Hanson, Harris, Scott, & Helmus, 2007), examined the construct, predictive, and incremental validity of the Screening Scale for Pedophilic Interests (SSPI; Seto & Lalumière, 2001), a brief proxy measure of phallometrically assessed sexual response to children that is based on sexual victim characteristics. As predicted, the SSPI was significantly related to the Deviant Sexual Interests item on the STABLE-2007 (Hanson et al., 2007), a dynamic risk measure encompassing multiple domains, and with the Deviant Sexual Interests item from its predecessor, the STABLE-2000 (Hanson et al., 2007). The SSPI was unrelated (or more weakly related) to items measuring general antisociality. In addition, the SSPI significantly predicted sexual recidivism, defined as new charges or convictions for sexual offenses, and a broader sexual recidivism outcome that included breaches of community supervision conditions that might involve sexually motivated behavior (e.g., being in the presence of children unsupervised). The SSPI did not add to the predictive accuracy of 2 actuarial risk measures, the Static-99R and Static-200R (Helmus, Thornton, Hanson, & Babchishin, 2012), but it did add to the predictive accuracy of the STABLE-2007. Additional analyses suggest the SSPI can serve as a substitute for the STABLE-2007 Deviant Sexual Interests item, if necessary (e.g., in archival research), when assessing sexual offenders against children.

Keywords

deviant sexual interests, sexual offenders, prediction, recidivism, risk assessment

Summary of the Research

The Screening Scale for Pedophilic Interests (SSPI) is a risk assessment measure of deviant sexual interest in children. The measure provides timely and direct assessment based on criminal history information without requiring detailed file reviews, interviews with the offender, or specialized testing. Total SSPI scores range between 0 and 5, with higher scores indicating a greater likelihood of sexual interest in children. It aims to be a valid counterpart to the Static-99R, Static-2002R, and STABLE-2007.

This study examined the construct and predictive validity of the SSPI in a sample of 410 adult male sexual offenders against children.

Construct Validity

The SSPI was compared to similar sexual violence risk assessment tools for its construct validity: (1) Static-99R, (2) Static-2002R, (3) STABLE-2007, and (4) STABLE-2000 Deviant Sexual Interest Item. The SSPI differs mostly from its counterparts with its emphasis on sexual offenses against children fourteen years or younger. Supervising officers provided their assessments from the four measures as part of the study as well as descriptive data regarding the offenders’ victim history.

“Total scores on the SSPI were moderately related to the STABLE-2000 Deviant Sexual Interests item and strongly related to the STABLE-2007 Deviant Sexual Interests item. Static-2002R was very strongly related to both complete SSPI scores and the approximated SSPI score” (p. 39).

Discriminant Validity

The SSPI was examined for discriminant validity in terms of antisocial behavior and general criminality. “Both the complete and approximated SSPI scores were unrelated to nonsexual violence (either as part of their current sex offense or a prior conviction), prior sentencing dates (on Static-99R), cooperation with supervision, impulsive acts, and any conviction for break and enter” (p. 39). Conversely, both SSPI scores were significantly related to prior sentencing occasions for any type of offense, poor cognitive problem-solving, and negative emotionality/hostility. “Although some of these correlations were significant, the highest correlation was still lower than the relationship between SSPI and the STABLE-2007 Deviant Sexual Interests item, and substantially lower than the other potential measures of deviant sexual interest” (p. 39)

The total scores for the SSPI were not statistically significant for nonsexually violence and nonviolent recidivism. Overall, the results show that the SSPI is more related to measurements of deviant sexual interests than to broadly defined criminality.

Predictive Validity

“SSPI was examined for predictive validity in terms of sexual recidivism and sexual recidivism with breaches. The complete SSPI total score was significantly correlated to both sexual recidivism and sexual recidivism with breaches” (p. 39).

Individual SSPI items did not show a strong relationship with sexual recidivism; the strongest individual item was having two or more child victims. “Similarly, the other indicators of deviant sexual interests showed small relationships with the outcomes. Both outcomes were significantly predicted by the unrelated victim item of Static-99R, the Deviant Sexual Interests subscale of the Static-2002R, and the Deviant Sexual Interests item of the STABLE-2007 (but not the STABLE- 2000). The Deviant Sexual Interest subscale of Static-2002R had fairly comparable predictive accuracy to the SSPI, whereas the Deviant Sexual Interests item of STABLE-2007 had slightly lower accuracy than the SSPI and Static-2002R subscale” (p. 40).

Translating Research into Practice

In terms of incremental validity, the SSPI did add to the STABLE-2007 for prediction of sexual recidivism. A greater emphasis on factors for deviant sexual interest towards children could positively affect the STABLE-2007 scale. For practical applications, this research suggests that by using both measures, predictive accuracy could be improved for sexual recidivism. Conversely, the SSPI did not significantly add to the Static-99R or the Static-2002R. In this study, the latter two assessment tools were found to adequately account for deviant sexual interest in children.

The Static-99R and Static-2002R have better predictive accuracy when it comes to recidivism most likely due to having a wider breadth of contributing variables. The SSPI is less suitable to predict recidivism rates for this population because recidivism is impacted by more factors than just sexual interest in children.

Based on these research results, “the SSPI could be a reasonable substitute for the STABLE-2007 Deviant Sexual Interests item if insufficient information was available to score the STABLE-2007 item as intended” (p. 42). This is not meant to formally substitute risk assessments in applied settings but to encourage more research for the SSPI.

Overall, the SSPI should be used as a brief assessment tool to quickly acquire information for sexual risk assessment towards young children. The research has expressed benefits for using the SSPI with other tools like the STABLE-2007 but it is not the only risk assessment tool that captures individual characteristics of sexual deviance towards children.

Other Interesting Tidbits for Researchers and Clinicians

In terms of sexual recidivism, “antisociality indicators play an important role as well, as reflected in variables such as younger offender age and prior criminal history. Although future refinement of the SSPI may improve its predictive ability somewhat, this will always be bounded by the absolute contribution of deviant interests to future reoffending” (p. 42).

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Authored By: Andrea PatrickForensic-Training-AcademyPatrickAndrea

Andrea Patrick is a first year masters student studying Forensic Psychology at John Jay College of Criminal Justice. In the future, she hopes to be directly working with forensic populations providing risk assessments and clinical evaluations.

 

Mental Illness not a Reliable Predictor of Sex Offender Recidivism

Forensic-Training-AcademyPresence of mental illness is less related to risk and needs but is an important factor for treatment responsivity among sexual offenders. This is the bottom line of a recently published article in the International Journal of Forensic Mental Health. Below is a summary of the research and findings as well as a translation of this research into practice.

 

Featured Article | International Journal of Forensic Mental Heath | 2015, Vol. 14, No. 1, 10-22. ijfmh

The Relationship between Mental Disorder and Recidivism in Sexual Offenders

Authors

Drew A. Kingston, Integrated Forensic Program, Royal Ottawa Health Care Group, Brockville, Ontario, Canada, Institute of Mental Health Research, University of Ottawa, Ottawa, Canada
Mark E. Olver, Department of Psychology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Melissa Harris, Integrated Forensic Program, Royal Ottawa Health Care Group, Brockville, Ontario, Canada
Stephen C.P. Wong, School of Medicine, University of Nottingham, Nottingham, United Kingdom, Department of Psychology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
John M. Bradford, Integrated Forensic Program, Royal Ottawa Health Care Group, Brockville, Ontario, Canada, Institute of Mental Health Research, University of Ottawa, Ottawa, Canada

Abstract

The importance of mental illness as a risk factor for violence has been debated with significant implications for mental health policy and clinical practice. In offender samples, mental health diagnoses tend to be unrelated to recidivism, although this effect has been questioned recently in sexual offenders. In the present, prospective investigation, the relevance of several mental health diagnoses and relevant co-morbidity is examined as predictors of various types of recidivism in two distinct samples of sexual offenders who were followed up to 27 years in the community. Results indicated that mental health diagnoses were not predictive of recidivism on their own or in multivariate categories, although comorbid substance-use disorders and some personality disorders showed some predictive validity. Results are discussed in the context of a social learning model of crime and in terms of the treatment of sexual offenders.

Keywords: sex offender, mental health, diagnoses, recidivism

Summary of the Research

“The vast majority of studies using offender samples have shown psychiatric diagnoses to be unrelated to recidivism and that the predictors of recidivism are largely shared between mentally disordered offenders and non-disordered offenders. According to the General Personality and Cognitive Social Learning Model (GPCSL), there are eight robust predictors of criminal behavior that reside within the individual or their immediate social learning environment: criminal history, procriminal companions, procriminal attitudes, antisocial personality pattern, education/employment, family/marital, substance abuse, and leisure/recreation. Mental health variables were not considered significant predictors of criminal behavior. Consistent with the research on general offenders, a meta-analysis reported that severe psychological dysfunction (psychosis) was not significantly related to sexual recidivism. Since this meta-analysis, there have been relatively few studies published examining the relationship between serious mental illness and recidivism in sexual offenders” (p. 11)

“In the present study, we examined the relationship between mental disorder and recidivism in a sample of treated Canadian correctional sample of sexual offenders, and replicated our findings in a sample of sexual offenders in an outpatient mental health hospital. We hypothesized that recidivism would be best predicted by factors identified by the GPCSL and previous meta-analyses. Additionally, we predicted that mental health diagnoses would not be associated with recidivism and would fail to show any incremental validity after controlling for needs that are consistent with the GPCSL” (p. 12).

“The vast majority of the sample (95% in study 1, 97% in study 2) had a mental disorder and a significant proportion of offenders had a [substance use disorder] and a [personality disorder], particularly [Antisocial Personality Disorder (ASPD)]. Importantly, these base rates are not representative of general offender populations, but rather reflect a select, broadly high risk sample of sex offenders attending treatment at a corrections-based mental health facility” (p. 15).

“Consistent with extant findings, non-substance related mental disorders were not predictive of recidivism outcomes either on their own or in multivariate categories. The Violence Risk Scale-Sexual Offender version dynamic score significantly predicted sexual, violent, and general recidivism. The only diagnostic categories that were associated with risk and recidivism were personality disorders (including ASPD), substance use disorders (SUD), and dual diagnoses involving substance use disorder comorbidity. Even in these instances, most diagnostic categories were marginal predictors of sexual violence, although they tended to be more robust predictors of general violence and any criminal recidivism.” (p. 15)

Translating Research into Practice

“A number of studies have shown that severe mental illness, particularly schizophrenia and other psychotic disorders are associated with crime. Such studies have been used to support specific policy recommendations and the initiation of diversion programs (e.g., mental health courts) that are intended to treat mental illness so that the likelihood of recidivism is reduced. Although diversion programs have been successful in reducing the rates of incarceration and increasing general access to mental health services, the ability of these programs to reduce recidivism has been mixed, at best. The evidence for mental health courts is particularly weak for those programs weighted more heavily toward mental health models, as opposed to criminal justice–based models” (p. 19)

“Addressing these dynamic risk factors or criminogenic needs is an important component of treatment programs that adhere to the principles of effective correctional intervention (i.e., risk, need, responsivity). A number of programs based on the principles of risk, need, and responsivity have been developed and applied to general offenders and sexual offenders with some degree of empirical support. It is our sense that some diagnoses contain or embody dynamic risk factors, which may be why they contribute to the prediction of recidivism outcomes. Given comprehensive measure of sexual violence risk that assesses static and dynamic domains, diagnostic information may be immaterial from a risk and need standpoint, although may be an important responsivity consideration” (p. 19)

“Despite the fact that mental illness is not a reliable predictor of recidivism, such diagnoses may be best conceptualized as a responsivity factor as noted above, such that some individuals with active mental illness may find it difficult to engage in treatment or attend to the treatment content. Therefore, targeting such symptoms may be an important first step in treatment process. In turn, addressing mental health symptoms may help to promote improvement on an individual’s identified criminogenic needs. For example, managing mental health symptoms may allow one to make more adequate use of leisure time, resisting urges to turn to substance use to manage symptoms, and to obtain employment, all of which have been shown to reduce the likelihood of recidivism” (p. 20).

Other Interesting Tidbits for Researchers and Clinicians

In study 2, SUDs, “demonstrated a unique association with outcome, particularly for general violence and any kind of reoffending upon release. It is worth noting that the sample had a fairly low base rate of NSMD, but a high base rate of personality disorder and SUD. Interestingly, SUD did not covary with VRS:SO posttreatment dynamic score. That is, individuals with or without an SUD bore little relation to their actuarial level of sexual violence risk; however, there was a clear differentiation between the two groups in terms of nonsexual outcomes, and this was additive beyond the VRS:SO. In this context, SUD may have served as a proxy for a general risk variable, given that the VRS:SO contains diverse item content, of which one domain includes general criminality” (p.15).

“After controlling for Static-99 score, few of these diagnoses (SUDs, PDs) predicted any outcome, save for a few interesting exceptions. This reflects the high degree of shared variance between some of these categories with a risk assessment tool such as the Static-99, explaining the higher scores observed in most groups that were positive for a given diagnosis (except for SGIDs and NSMDs). Thus, although some of these diagnostic entities have risk variance, there is little beyond that already captured by the Static-99 and they tend to offer little incrementally, at least from a pure prediction perspective. One interesting exception was Sexual Sadism, which provided additional predictive information beyond the Static-99, which likely captures in part the prominent risk-need domain of sexual deviance from the broader extant literature as a salient marker of risk for sexual violence” (p. 19).

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BanfordMegan-pic

Authored By: Megan Banford

Megan is a graduate student in the Forensic Psychology program at John Jay College. She graduated in 2013 from Simon Fraser University with a B.A. (Honors) and hopes to attain her PhD in clinical forensic psychology. Her main research interests include violence risk assessment and management, juvenile offenders and public policy.

 

Juror Ratings of Risk Appear Dependent Upon Communication Format in Static-99R Reports

Forensic-Training-AcademyProspective jurors draw different conclusions about reported Static-99R scores depending on whether risk is communicated in terms of category, relative risk, or normative samples. This is the bottom line of a recently published article in Law and Human Behavior. Below is a summary of the research and findings as well as a translation of this research into practice.

Featured Article | Law and Human Behavior | 2014, Vol. 38, No. 5, 418-427 

lhb

Same Score, Different Message: Perceptions of Offender Risk Depend on Static-99R Risk Communication Format 

 

Author

Jorge G. Varela, Marcus T. Boccaccini, Sam Houston State University
Veronica A. Cuervo, Sam Houston State University
Daniel C. Murrie, University of Virgina
John W. Clark, University of Texas at Tyler

Abstract

The popular Static-99R allows evaluators to convey results in terms of risk category (e.g., low, moderate, high), relative risk (compared with other sexual offenders), or normative sample recidivism rate formats (e.g., 30% reoffended in 5 years). But we do not know whether judges and jurors draw similar conclusions about the same Static-99R score when findings are communicated using different formats. Community members reporting for jury duty (N 211) read a tutorial on the Static-99R and a description of a sexual offender and his crimes. We varied his Static-99R score (1 or 6) and risk communication format (categorical, relative risk, or recidivism rate). Participants rated the high-scoring offender as higher risk than the low-scoring offender in the categorical communication condition, but not in the relative risk or recidivism rate conditions. Moreover, risk ratings of the high-scoring offender were notably higher in the categorical communication condition than the relative risk and recidivism rate conditions. Participants who read about a low Static-99R score tended to report that Static-99R results were unimportant and difficult to understand, especially when risk was communicated using categorical or relative risk formats. Overall, results suggest that laypersons are more receptive to risk results indicating high risk than low risk and more receptive to risk communication messages that provide an interpretative label (e.g., high risk) than those that provide statistical results.

Keywords: Static-99R, communication, risk assessment, sexual offender

Summary of the Research

Risk and recidivism of sexual offenders has become a captivating topic in psychology and law, prompting an increase in research surrounding risk assessment. However, discrepancies between actual sexual recidivism and public perception of risk necessitate research regarding the effectiveness of expert communication of risk to juries. Varela, Boccaccini, Cuervo, Murrie, and Clark examined juror interpretation of varying Static-99R score communication formats to investigate whether these factors impact layperson perception of sexual offender risk.

The Static-99R is a risk assessment tool utilized frequently by forensic evaluators to report on the level of risk of an individual brought to the criminal justice system. This instrument “allows evaluators to convey results in terms of risk category (e.g., low, moderate, high), relative risk (compared with other sexual offenders), or normative sample recidivism rate formats (e.g., 30% reoffended in 5 years).” However, little is know about whether judge and juror interpretation of Static-99R scores is dependent upon communication format.

Based on previous research findings that judges and jurors may be confused by statistical explanations of risk and seem to devalue expert opinions that indicate low risk of violence, the current study “compared the influence of three Static-99R risk communication formats—categorical, risk estimate, and relative risk—on venirepersons’ perceptions of sexual offenders” (p. 420). A final sample of 211 prospective jurors read one of six case descriptions, which “varied across two dimensions—the offender’s Static-99R score (i.e., risk level) and risk communication format. The low-scoring offender was assigned a Static-99R score of 1 and the high-scoring offender was assigned a Static-99R score of 6” (p. 420).

“After reading the case description and Static-99R results, participants were asked to make three ratings related to the hypothetical offender—likelihood of committing a new sexual offense in the next 5 years, dangerousness to community members, and support for the use of the “most strict and expensive supervision strategies.” They rated each of these items on a scale ranging from 1 (not likely at all/not at all dangerous) to 6 (very likely/very dangerous). Based on previous research examining jurors’ perceptions of offender risk (e.g., Boccaccini, Murrie, Clark, & Cornell, 2008), we expected that ratings on these items would be moderately to highly correlated and that we would combine them to form a single risk composite variable. In other words, those who view the offender as likely to reoffend should also view him as dangerous to the community and in need of the most strict supervision strategies” (p. 420).

The authors found that ratings on the three items were, in fact, moderately to strongly correlated. However, “Participants rated the low-scoring offender as lower risk than the high-scoring offender in some but not all of the communication format conditions. When risk communication was in the form of a categorical message, participants assigned lower risk ratings to the low-scoring offender than the high-scoring offender. When the risk communication was in the form of a relative risk message, participants assigned only somewhat lower risk ratings to the low-scoring offender. Finally, when presented a recidivism rate message, participants assigned nearly identical risk ratings to the low- and high-scoring offenders. Overall, these findings indicate that participants viewed the high- and low-scoring offenders as having significantly different levels of risk when Static-99R results were communicated using a categorical format, but not when results were communicated using relative risk or recidivism rate formats” (p. 421).

Taken together, the results indicate that varying risk communication formats of the Static-99R may result in different conclusions drawn by legal decision-makers.

Translating Research into Practice

The finding that prospective jurors rated the high-scoring hypothetical offender as more dangerous and more likely to reoffend when risk was communicated categorically as opposed to numerically should raise awareness to forensic evaluators about effective communication formats. The finding that the prospective jurors in this study rated the low-scoring hypothetical offender as “similarly likely to reoffend” as the high-scoring offender when the risk information was presented numerically has serious implications. The authors suggest that this may be the result of layperson overestimation of risk or layperson misunderstanding and misapplication of numerical data. Regardless, practitioners who perform Static-99R evaluations and testify in court proceedings should consider this research and take caution in the communication format they choose to utilize. It appears that jurors may be more receptive to categorical communication formats as opposed to formats that involve normative groups or statistical explanations.

Additionally, since “findings also suggest that venirepersons either neglect risk ratios or do not understand them, especially when the risk ratio suggests low risk,” clinicians in this field should take care in communicating low-risk findings to ensure optimal juror understanding (p. 425). Though evaluators may not necessarily be able to reverse layperson overestimation of risk, attempts to clarify may assist in legal decision-making. “Researchers and clinicians in forensic psychology are understandably focused on developing and properly using instruments, including actuarial instruments. But until the field can communicate to decision makers the results of these measures—in understandable and constructive ways—the practical value of rigorous assessment methods will be greatly constrained” (p. 425).

Other Interesting Tidbits for Researchers and Clinicians

“Confirmation bias may help explain the varied pattern of participants’ responses to risk communication messages. Confirmation bias is the tendency to selectively seek and interpret information in a manner consistent with one’s beliefs and expectations. In our study, nearly all participants, across all experimental conditions, reported that the offender would likely reoffend within the next 5 years. It is reasonable to assume that many participants in our study assumed that most sexual offenders reoffend, as have participants in other research. Therefore, a risk communication indicating that a sexual offender was at low risk for reoffending would have been incongruent with participants’ expectations about sexual offenders and easy to dismiss as unpersuasive or difficult to understand. These findings add to the small but growing body of research suggesting that judges and jurors may simply discount or devalue low-risk messages, perhaps because low-risk messages are incongruent with their expectations that those who have offended in the past will offend again” (p. 424).

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Authored By: Marissa Zappala

DarkBlue-Forensic-Training-AcademyZappalaMarissa - PictureMarissa is currently enrolled in the Master of Arts in Forensic Psychology program at John Jay College of Criminal Justice located in New York City. She completed her undergraduate work at Penn State University, where she obtained a B.A. Psychology and B.A. Criminology. Her aspirations involve the pursuit of a Clinical Forensic PhD program, and an eventual career in Forensic Psychological Evaluation. To contact Marissa, please e-mail marissa.zappala@gmail.com.

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Communication Format Influences Perceptions of Offender Risk

lhbPerceptions of risk vary by the communication format used and laypersons appear more receptive to communication messages that provide an interpretive label than those that provide statistical results. This is the bottom line of a recently published article in Law and Human Behavior. Below is a summary of the research and findings as well as a translation of this research into practice.

Featured Article | Law and Human Behavior | 2014, Vol. 38, No. 5, 418-427

Same Score, Different Message: Perceptions of Offender Risk Depend on Static-99R Risk Communication Format

Authors

Jorge G. Varela, Sam Houston State University
Marcus T. Boccaccini, Sam Houston State University
Veronica A. Cuervo, Sam Houston State University
Daniel C. Murrie, University of Virginia
John W. Clark University of Texas at Tyler

Abstract

The popular Static-99R allows evaluators to convey results in terms of risk category (e.g., low, moderate, high), relative risk (compared with other sexual offenders), or normative sample recidivism rate formats (e.g., 30% reoffended in 5 years). But we do not know whether judges and jurors draw similar conclusions about the same Static-99R score when findings are communicated using different formats. Community members reporting for jury duty (N = 211) read a tutorial on the Static-99R and a description of a sexual offender and his crimes. We varied his Static-99R score (1 or 6) and risk communication format (categorical, relative risk, or recidivism rate). Participants rated the high-scoring offender as higher risk than the low-scoring offender in the categorical communication condition, but not in the relative risk or recidivism rate conditions. Moreover, risk ratings of the high-scoring offender were notably higher in the categorical communication condition than the relative risk and recidivism rate conditions. Participants who read about a low Static-99R score tended to report that Static-99R results were unimportant and difficult to understand, especially when risk was communicated using categorical or relative risk formats. Overall, results suggest that laypersons are more receptive to risk results indicating high risk than low risk and more receptive to risk communication messages that provide an interpretative label (e.g., high risk) than those that provide statistical results.

Keywords

Static-99R, communication, risk assessment, sexual offender

Summary of the Research

“Research suggests that between 75% and 80% of laypersons believe that sexual offenders will reoffend. In contrast, meta-analytic research has found a sexual recidivism rate of approximately 11.5%. This large discrepancy between public perceptions and the research that forms the basis of risk estimates highlights the importance of examining how risk messages are understood and used in legal decision making…Evaluators who use risk assessment instruments must effectively communicate their findings to those who actually make decisions about offenders, including judges and jurors. Risk assessment results are of little value if experts cannot effectively communicate their findings to legal decision makers. Thus, the primary goal of the current study was to examine whether different risk communication formats for the same Static-99R score lead venirepersons (i.e., community members who presented for jury duty) to reach the same or different conclusions about recidivism risk. A secondary goal was to examine whether venirepersons view some risk communication message formats as more useful or understandable than others” (pp. 418-419).

“The current study extends risk communication research into the domain of sexual offender proceedings, in which risk communication, particularly based on the Static-99R, is ubiquitous. [The authors] compared the influence of three Static-99R risk communication formats—categorical, risk estimate, and relative risk—on venire- persons’ perceptions of sexual offenders (e.g., dangerousness and likelihood of reoffense). Existing research suggests that venirepersons view categorical messages as more useful than those with statistical information and, as a result, we should expect the greatest differences in perceptions of dangerousness and likelihood of reoffending between high- (Static-99R = 6) and low- (Static-99R = 1) scoring offenders when information is presented categorically. Existing research also suggests that venirepersons may devalue risk assessment results when they indicate low risk, suggesting that we should expect our participants to report that Static-99R findings are less useful when they indicate low risk. We also should expect venirepersons to be especially likely to report being confused by relative risk messages, because they combine technical statistical information with a comparison to the undefined ‘typical’ sex offender” (p. 420).

“Participants read a two-page document that included one of six versions of a sex offender risk assessment case…The case descriptions varied across two dimensions—the offender’s Static-99R score (i.e., risk level) and risk communication format. The low-scoring offender was assigned a Static-99R score of 1 and the high-scoring offender was assigned a Static-99R score of 6.

The three risk communication formats were categorical, risk estimate, and relative risk. In the categorical conditions, the offender’s risk was communicated in the following manner: ‘According to the Static-99R developers, Mr. Donaldson’s score of 1 (or 6) places him in the Low (or High) risk category for being charged with another sexual offense.’ In the relative risk conditions, the case description reported the Static-99R score and the offender’s risk was described as ‘three fourths the recidivism rate of the typical sex offender’ for the low-score condition and ‘2.91 times the recidivism rate of the typical sex offender’ for the high-score condition…In the risk estimate conditions, the case description read ‘in the Static-99R research sample, 9.4% (or 31.2%) of men who scored 1 (or 6) on the Static-99R (like Mr. Donaldson) were rearrested for a sexual offense within five years’” (p. 420).

Participants were 211 adult community members called for jury duty in an urban jurisdiction. The average age was 44.12 years (SD = 14.03) and the racial/ethnic breakdown was: 53.1% White, 44.1% Black, and 2.9% other ethnicity. Participants were asked to make several ratings regarding the hypothetical offender, including their perceptions of likelihood of committing a new sexual offense in the next 5 years, level of risk, and importance of the Static-99R results.

Perceptions of the Offender

“Overall, 95% of participants indicated that the offender would commit a new sex offense in the next 5 years. Given this lack of variance, [the authors] did not compare responses across study conditions” (p. 421).

With respect to the ratings of risk, “[o]verall, the findings indicate that participants viewed the high- and low-scoring offenders as having significantly different levels of risk when Static-99R results were communicated using a categorical format, but not when results were communicated using relative risk or recidivism rate formats” (p. 421).

“There was also some evidence that participants who read about the same Static-99R score viewed the offender differently depending on risk communication format. Among participants who read about a Static-99R score of 6, those who read a categorical message assigned higher risk composite ratings than those who read a recidivism rate message and those who read a relative risk message. Among participants who read a Static-99R score of 1, those who read a categorical message assigned the lowest composite ratings, although they were not significantly lower than those from participants who read recidivism rate and relative risk messages” (pp. 421-422).

Perceptions of the Static-99R Results

In terms of perceptions regarding the importance of the Static-99R results, participants rated the Static-99R results as being more important in the high-score condition. With respect to the type of communication used, in the high-score condition, the categorical message was rated as the most important whereas in the low-risk condition, it was rated as the least important.

Translating Research into Practice

“Every day, the justice system makes decisions about sexual offenders after considering risk communication, particularly based on the Static-99R. Yet, so far, no studies have examined how decision makers understand or use this risk communication. [These authors] found that different risk communication formats for the same Static-99R score might lead venirepersons to different conclusions about recidivism risk. When the offender had a high Static-99R score, participants rated him as more dangerous and likely to reoffend when the risk communication included a categorical message than a numerical message (i.e., relative risk or risk estimate). When the offender had a low Static-99R score, risk ratings were generally high but similar across the three risk communication conditions. Indeed, participants viewed the high- and low-scoring offender as similarly likely to reoffend when risk was communicated numerically.

Participants’ responses to questions about the importance and understandability of Static-99R results may help explain the relatively high-risk ratings in the low-score conditions. Participants presented with a low Static-99R score were more likely than those presented with a high score to report that the Static-99R results were difficult to understand, and they also rated the Static-99R results as relatively unimportant. These patterns applied more clearly to participants presented with categorical and relative risk communication messages than those presented with recidivism risk messages. Indeed, participants who were presented with recidivism rate messages responded similarly to each of [the] measures, regardless of whether they read a risk communication message that corresponded with a high or low Static-99R score” (p. 424).

“Confirmation bias may help explain the varied pattern of participants’ responses to risk communication messages. Confirmation bias is the tendency to selectively seek and interpret information in a manner consistent with one’s beliefs and expectations. In [this] study, nearly all participants, across all experimental conditions, reported that the offender would likely reoffend within the next 5 years. It is reasonable to assume that many participants in [this] study assumed that most sexual offenders reoffend, as have participants in other research…One implication of these findings is that experts and attorneys (most likely defense/respondent attorneys) should consider directly addressing jurors’ a priori beliefs about sexual offenders…But confirmation bias cannot completely explain [these] findings, as the risk communication format also seemed to influence perceptions of offender risk. For example, [the] findings suggest that participants perceived only some of the Static-99R high-score messages as actually conveying higher risk than the corresponding low-score messages. Participants clearly assigned higher risk ratings to the high- scoring than low-scoring offender when risk was communicated using categorical messages. In contrast, there was only a small difference in risk ratings between the high- and low-score (risk) conditions when participants were presented a relative risk message and almost no difference when participants were presented a recidivism rate message.

The finding that community members were most responsive to risk communication formats that provide interpretive guidance (i.e., categorical labels) is consistent with clinicians’ preferences for communicating risk using nonnumerical messages. But one danger in using categorical labels is that clinicians become less descriptive and more prescriptive, implicitly recommending a course of action to the court rather than simply providing factual data. Thus, even using categorical messages requires conscientious clinicians to communicate with caution and clarity” (p. 424).

“[These] findings also suggest that venirepersons either neglect risk ratios or do not understand them, especially when the risk ratio suggests low risk. Participants presented with a low score and a relative risk message should have reported that the offender was less likely than other offenders to reoffend. Yet, almost 80% of participants in the low-score/relative risk condition reported that the offender was more likely than other offenders to reoffend, despite having just read that his recidivism rate was ‘approximately three fourths’ that of the typical offender.

There are several possible explanations for this finding. The first is that jurors simply view all offenders as at a high risk for reoffending, regardless of risk communication messages. Again, a second possible explanation is that innumeracy may have led to a misunderstanding of the risk message. Regardless of the explanation, the implication for practice is that experts need to spend time explaining the recidivism risk of the typical offender. In other words, relative risk communication information may need to be accompanied by a thorough explanation of its basis and application. Testimony explaining the meaning of risk ratios and how they apply to a specific case may be necessary to ensure that decision makers understand the risk information when formulating risk” (p. 425).

“Overall, the findings of the current study suggest that venirepersons approach decision making with the expectation that sexual offenders are dangerous and quite likely to sexually reoffend. Their expectations appear resistant to influence by risk assessment messages, especially when they are informed an offender’s risk is low. Researchers and clinicians in forensic psychology are understandably focused on developing and properly using instruments, including actuarial instruments. But until the field can communicate to decision makers the results of these measures—in understandable and constructive ways—the practical value of rigorous assessment methods will be greatly constrained “ (p. 425).

Other Interesting Tidbits for Researchers and Clinicians

“A consistent finding across risk, understandability, and importance measures was that participants who read about recidivism rates responded similarly, regardless of whether they read about the rate for a low or high Static-99R score. One possible explanation for this pattern of findings is that laypersons so consistently and so greatly overestimate recidivism risk that actual estimated rates have little impact on their opinions. Another possible explanation is that the difference in recidivism rates (9.4% vs. 31.2%) was too small to be salient or meaningful, despite having used rates from the Static-99R normative group with the highest recidivism rates (high risk/needs). A final possibility is simply that innumeracy (i.e., lack of understanding and facility with numbers and mathematical concepts) left [the] participants unable to make use of recidivism rate data. Scholars have demonstrated that innumeracy is a significant problem among legal decision makers and has hindered mock jurors’ perceptions of violence risk.

One implication of these findings is that it is unlikely that the difference between high and low Static-99R score recidivism rates from other Static-99R normative groups will be salient to jurors. The Static-99R & Static-2002R Evaluator’s Workbook suggests that rates from the routine sample norms, which are lower than the high-risk/need norms used in the current study, are appropriate in most sex offender evaluations. Using the routine sample norms, the estimated 5-year sexual recidivism rates for scores of 1 and 6 are 3.8% and 14.7%, respectively. Because only 4% of offenders score higher than 6 on the Static-99R, most of the 5-year recidivism rates reported by evaluators will be 14.7% or below” (p. 425)

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Upcoming Training Dates for Risk Assessment Workshops

Consolidated Continuing Education & Professional Training (CONCEPT) is pleased to offer Continuing Education (CE) credit for workshops provided by our partner, ProActive ReSolutions, who will be holding several upcoming in-person workshops on violence risk assessment and management. Workshop dates are listed below.

As always, online training on risk assessment and management is available at any time. Descriptions of our risk assessment and management training programs can be found on our Programs page as well as below.

In-Person Training Workshops

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  • Advanced Violence Risk Assessment and Management Workshop for Higher Education

Dates: May 25-29, 2015
Location: Burlington, Ontario, Canada
Instructors: Drs. Stephen Hart, Laura Guy, & Kelly Watt
More Information: Click here for further information about this training course, including schedule, course objectives, and description. 

Click here to Register for CE Credits for this Workshop | 30 CEs | $125

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Online Training Programs

  • Foundations of Threat Assessment

The Foundations of Threat Assessment training program accommodates varying levels of experience in threat assessment and risk management and focuses on the most common forms of violence (e.g., general violence, intimate partner violence, stalking).

This Foundations of Threat Assessment training program provides an opportunity to learn new skills and build on existing skills in assessing and managing risk for violence. In addition, general principles of threat assessment and risk management as well as best practices supported by researchers and practitioners around the world are discussed.

More information about this training program can be found here.

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  • Advanced Issues in the Assessment of Risk for Violence: Case Formulation

This training program will provide practitioners with a summary of the most up-to-date research findings relevant to violence and sexual violence, provide an overview of the most recent clinical guidance on risk assessment and management using a structured professional judgement approach, and give practitioners the opportunity to advance their practice in respect of clinical interviewing skills, risk formulation, risk management planning, and risk communication through relevant exercises and case studies.

More information about this training program can be found here.

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  • Assessment of Risk for Violence using the HCR-20 Version 3

This training program on the Evaluation of Risk for Violence using the HCR-20 Version 3 was developed by Drs. Stephen Hart and Kevin Douglas and is presented in partnership with ProActive ReSolutions.

This training program focuses on the revised HCR-20 (now called HCR:V3) in the U.S. and describes why and how the HCR-20 was revised; how Version 3 differs from its predecessors; initial research validation of Version 3; what its risk factors are and how to rate them; and how to complete case formulation and risk management planning using Version 3. Participants will also have the opportunity to complete the HCR:V3 on a practice case.

More information is available about this training program here.

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  • Evaluation of Risk for Sexual Violence using the RSVP

This training program on the Evaluation of Risk for Sexual Violence using the RSVP was developed by Dr. Stephen Hart and is presented in partnership with ProActive ReSolutions.

The Risk for Sexual Violence Protocol (RSVP) is a set of structured professional guidelines that can also be considered a psychological test. This training program describes the RSVP and takes the trainee through a series of video modules on the use of the RSVP for guiding judgements of risk for sexual violence. The trainee also works through three case studies to practice applying the RSVP to case formulation.

More information about this training program can be found here.