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1. Developments in Risk Assessment: Violence Risk and Sexual Violence Risk

1. Developments in Risk Assessment: Violence Risk and Sexual Violence Risk. Kirk Heilbrun, Ph.D. Drexel University kirk.heilbrun@drexel.edu http://www.drexel.edu/psychology/ research/labs/heilbrun/publications/. 2 . Goals . Describe risk assessment (RA) tools

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1. Developments in Risk Assessment: Violence Risk and Sexual Violence Risk

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  1. 1. Developments in Risk Assessment: Violence Risk and Sexual Violence Risk Kirk Heilbrun, Ph.D. Drexel University kirk.heilbrun@drexel.edu http://www.drexel.edu/psychology/ research/labs/heilbrun/publications/

  2. 2. Goals • Describe risk assessment (RA) tools • Describe sexual violence RA tools • Review empirical studies on violence and offending in different populations • Describe scientifically-supported, scientifically-unsupported, and controversial uses of risk assessment

  3. 3. Important Conceptual Advances Since 1980 • Short vs. long-term prediction • Use of term “risk assessment” • Risk-Need-Responsivity (RNR) and risk-needs assessment • Particular attention to situational variables • Actuarial vs. SPJ vs. unstructured professional judgment

  4. 4. Components of “dangerousness” • Risk factors, protective factors – variables used to predict outcome • Harm (nature and severity) • Risk level – probability that harmwill occur

  5. 5. Nature of risk factors • dynamic ‑ changeable via intervention with individual (treatment, monitoring) or control of situation (living setting, access to weapons) • stable • acute • static ‑ not changeable via such intervention; may include personal characteristics (age, gender) and certain kinds of disorders or deficits (psychopathy, mental retardation)

  6. 6. Legal Contexts • Criminal responsibility • Sexually Violent Predators • Capital sentencing • Civil commitment • Correctional transfer • Workplace disability

  7. 7. Legal Contexts • Child custody • Child protection • Juvenile disposition and transfer • Tarasoff

  8. 8. Legal Standards: Risk Assessment Components • Nature of risk factors • Level of risk • Severity of harm • Length of outcome period • Context in which harm may occur

  9. 9. Steps in FMHA Risk Assessment • Is violence risk part of the evaluation? • Selection of data sources • Conducting interviews, administering measures, and reviewing records • Interpretation of results • Communication of findings • Judicial decision

  10. 10. Forensic Mental Health Concepts • Context – domains, FMHA risk assessment • Purpose – why conducting the evaluation • Populations – with whom • Parameters – structuring it • Approach – procedures and specialized tools

  11. 11. Purpose • Prediction/classification • Management/intervention planning • Both (risk-needs)

  12. 12. Population • Age • Gender • Mental health status • Location • Racial/ethnic group

  13. 13. Parameters • Target behavior • Frequency • Probability/risk category • Settings • Outcome period • Risk and protective factors

  14. 14. Approach • Actuarial (predictive, risk-needs) • Structured professional judgment (risk-needs) • Anamnestic (needs) • Unstructured clinical judgment

  15. 15. Empirical Foundations and Limits Actuarial - formal method using equation, formula, graph or table to arrive at a probability or expected value of some outcome. Uses quantified predictor variables validated through empirical research

  16. 16. Empirical Foundations and Limits Structured Professional Judgment – uses specified risk factors, not necessarily from one dataset. Items are carefully operationalized so their presence can be reliably coded. Evaluators then weight the presence of risk factors and anticipated intensity of management/treatment needs is drawing conclusion about risk

  17. 17. Empirical Foundations and Limits Anamnestic – process using applied behavior analytic strategies, seeking detailed information from the individual regarding previous behavior similar to the target outcome. “Individualized” risk factors are then derived.

  18. 18. Psychosis as Risk Factor for Violence • MacArthur Risk Study – psychosis alone not risk factor; combined with substance abusehighest risk (slightly higher than SA alone) • Douglas, Guy & Hart (2009) meta-analysis—psychosis results in 49-68% increase in odds of violence; moderated by study design, definition and measurement of psychosis, and comparison group

  19. 19. Using Actuarial Measures with Individuals: Debate • Discussants • Hart et al. (2007) • Harris & Rice (2007) • Mossman (2007) • Confidence intervals • Wilson’s formula (N=1)

  20. 20. Empirical Evidence on Actuarial Prediction • Longstanding area of study (Meehl, 1954) • Meta-analyses • Bonta, Law, & Hanson (1998) • Gendreau, Goggin, & Smith (2002) – PCL-R vs. LSI-R • Walters (2003) – PCL-R vs. Lifestyle Criminality Screening Form • Leistico et al. (2008) – PCL-R • MacArthur Risk Study

  21. 21. Empirical Evidence on SPJ • 13 studies (12 published, 1 dissertation) • 11 suggest SPJ judgments are significantly predictive of violent recidivism • 2 did not support this relationship • 5/5 studies concluded that SPJ “final judgment” adds incremental predictive validity to the actuarial combination of tool elements • Heilbrun, Douglas, & Yasuhara (2009)

  22. 22. Empirical Evidence on SPJ vs. Actuarial Approaches • Limited evidence • 4 studies compared approaches • 2 found no differences; 2 favored SPJ in predictive accuracy • Enhanced structure associated with actuarial or SPJ approaches increases accuracy (Monahan, 2008) • Kroner et al. (2005) “coffee can” study—may be reaching ceiling on predictive accuracy

  23. 23. Hanson & Morton-Bourgon sex offender meta-analysis (2009) • 118 samples (N=45,398), 63% unpublished • Best support for actuarial (e.g., Static-99) and mechanical (e.g., add scales on SVR-20) approaches • Intermediate support for SPJ approaches, although SVR-20 stronger • Weakest support for unstructured clinical judgment • No support for “adjusted actuarial”

  24. 24. Actuarial vs. SPJ Evidence on Predictive Efficacy • Depends on tool • Limited evidence comparing them directly • Existing evidence suggests the two approaches are comparable (Heilbrun, 2009)

  25. 25. Singh/FazelMetareview (2010) • Investigated quality and consistency of findings in reviews and meta-analyses • 40 reviews comprising 2,232 studies; nine main findings • Clinical, actuarial, SPJ: 5/6 meta-analyses found more support for actuarial than clinical prediction; 6th meta-analysis found actuarial and SPJ comparable • Measures: No one measure was consistently better than all others

  26. 26. Singh/FazelMetareview (2010) • Country of study inconclusive—two reviews found larger effects in U.S., a third concluded the opposite • Gender: 11/13 reviews concluded that tools worked comparably in males and females • Ethnicity: 5 reviews found no differences; 3 reported that greater effects resulted from higher proportion of Whites • Psychiatric populations: 1 meta-analysis found larger effects in PP; 3 found no diffs

  27. 27. Singh/FazelMetareview (2010) • Definitions of outcome: included rearrest, reconviction, reincarceration, nonaggressive misconduct, general aggression, physical violence, verbal aggression, and property destruction • Length of outcome period: 4/6 meta-analyses found that length of outcome period was not related to effect size • Risk factors: both static and dynamic risk factors linked to repeat offending

  28. 28. Singh/Grann/FazelMetaregression (2011) • Systematic review and meta-analysis using 9 risk assessment instruments (HCR-20, LSI-R, PCL-R, SORAG, SVR-20, SARA, Static-99, SAVRY, and VRAG) • 68 studies/25,980 participants/88 independent samples • Highest predictive validity: SAVRY • Lowest predictive validity: LSI-R, PCL-R

  29. 29. Yang/Wong/CoidMeta-analysis (2010) • Meta-analysis using 9 risk assessment instruments (HCR-20, LSI/LSI-R, PCL-R, PCL-SV, VRS, OGRS, RM2000V, and GSIR) • 28 studies published between 1999-2008 • 25% of variance related to differences between tools; 85% of study heterogeneity was methodological • All 9 were moderately successful and hence interchangeable except PCL-R with men

  30. 30. Major Developments in Risk Assessment Tools • See Otto & Douglas (2009) for overview of major risk assessment tools • Prediction • VRAG, SORAG • RRASOR, Static-99, Static-2002 • COVR • Risk Reduction • Analysis of Aggressive Behavior

  31. 31. Major Developments in Risk Assessment Tools • Risk-Needs • HCR-20, SVR-20 • RSVP • Stable 2000, Stable 2007 • Acute 2000, Acute 2007 • VRS, VRS-SO version • LS/CMI • SARA • SAVRY, YLS-CMI, WAJA

  32. 32. SAVRY (Borum et al., 2005) • Structured clinical assessment • 25 items • Items are scored -/+ • Historical items • Social/Contextual items • Individual/Clinical items • Protective items

  33. 33. SAVRY (Borum et al., 2006) • Historical Items, e.g., • Violence history, non-violent offense history, violence in the home, early onset of delinquent behavior, parental criminality, poor school achievement • Social/Contextual Items • Peer delinquency, peer rejection, poor parental involvement and management, lack of personal and social support

  34. 34. SAVRY (Borum et al., 2006) • Individual/Clinical Items • Impulsivity, substance abuse, anger management problems, psychopathic traits • Protective Items • Prosocial peers, strong social support, strong school commitment, open to intervention, strong attachment to adult role model

  35. 35. YLS/CMI (Hoge & Andrews, 2002) • Prior and Current Offenses/Dispositions • Family Circumstances/Parenting • Education/Employment • Peer Relations

  36. 36. YLS/CMI (Hoge & Andrews, 2002) • Substance Abuse • Leisure/Recreation • Personality/Behavior • Attitudes/Orientation

  37. 37. Level of Service/Case Management Inventory (LS/CMI) • Andrews, Bonta, & Wormith (2004) • Actuarial risk-needs tool, RNR influence • Designed for correctional population • Highly reliable (internal consistency) • Predictive validity comparable to or better than PCL-R (Gendreau et al., 2002)

  38. 38. Violence Risk Scale (VRS) • Actuarial risk measure, RNR-based • 6 static, 20 dynamic items • Male adult offenders • Good reliability (ICCC > .80) • Good predictive validity (AUC=.75 for violent reconviction, .72 for nonviolent reconviction (Wong & Gordon, 2006)

  39. 39. Historic-Clinical-Risk Management (HCR-20) • Webster et al. (1997) • SPJ risk-needs tool, risk factors in 3 domains • Historic: largely static • Clinical: dynamic • Risk Management: dynamic • Validation research has been conducted predictively, using H domain

  40. 40. Violence Risk Appraisal Guide (VRAG) • Almost entirely historical and static factors • Derived on Canadian sample of mentally disordered offenders • Relatively long outcome period (means of 7 and 10 years, respectively) • Actuarial tool, strength is prediction

  41. 41. Classification of Violence Risk (COVR) • Based on data obtained from MacArthur risk project (Monahan et al., 2001) and additional 2 sites (Monahan, Steadman, Robbins et al., 2005) • Chart review, brief interview, computer entry/scoring, decision tree methodology • Civil commitment, not criminal • Good reliability and validity (Monahan, Steadman, Appelbaum et al., 2005)

  42. 42. Sexual Offender Risk Appraisal Guide (SORAG) • Quinsey et al. (2006); 14 risk factors (13 static) • Predictors of recidivism in last decade: sexual deviance, young age, offending hx, juvenile antisociality, psychopathy or personality disorder, alcohol abuse, extrafamilial victims, abused or lived apart from parents as a child

  43. 43. Static-99 • Hanson & Thornton (1999); Harris et al. (2003) • Ten items4 risk levels • Created merging RRASOR & SACJ-Min • Highly reliable (inter-rater) • Predictive validity: AUC values around .70 (good) (Anderson & Hanson, 2009)

  44. 44. Static-2002 • Updated version of Static-99 (Hanson & Thornton, 2003) • Limited available research suggests comparable reliability and validity to Static-99 • For use with adult males charged w/ or convicted of offense w/sexual motive • Official records needed

  45. 45. Stable 2000, Stable 2007 • Dynamic risk factors account for variance beyond static predictors (Anderson & Hanson, 2009) • Measures stable dynamic needs (contrast w/acute) for sexual offenders • From Sex Offender Needs Assessment Rating • Can be combined w/Static-99, Static-2002

  46. 46. Acute 2000, Acute 2007 • See Anderson & Hanson (2009) • Aggregated “acute” measures predicted better than recent acute measures • AUC=.77 for Static-99; AUC=.81 for Static-99 + Stable 2007 (Hanson et al., 2007) • Suggests preference for stable factors and aggregated acute measures in FMHA

  47. 47. Sexual Violence Risk-20 (SVR-20) • Boer et al. (1997) • SPJ risk-needs tool; structure is somewhat similar to HCR-20 • Fewer dynamic risk factors • Three domains • Psychosocial adjustment • Sexual offenses • Future plans

  48. 48. Risk for Sexual Violence Protocol (RSVP) • SPJ tool • SVR-20 and RSVP conceptualize risk to include nature, severity, imminence, frequency, and likelihood (contrast w/actuarial) • Civil and criminal applications, males 18+ • Reliability good to excellent

  49. 49. Risk for Sexual Violence Protocol (RSVP) • 22 items in 5 domains: sexual violence hx, psychosocial adjustment, mental disorder, social adjustment, manageability • Limited validity data to date, but looks promising (Hart & Boer, 2009)

  50. 50. Violence Risk Scale-Sexual Offender version (VRS-SO) • Adapted from VRS • 7 static, 17 dynamic items • Good reliability (ICCC=.74 - .95) (Beyko & Wong, 2005) • Good predictive validity (static AUC=.74, dynamic AUC=.67, total AUC=.72) (Wong & Olver, 2009)

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