Changes in Risk Assessment

New Norms The Impact of Aging

Seduction to Child Porn Justin Berry $50 Sit bare-chested in front of Webcam for 3 minutes (Eichenwald, 2006) (Eichenwald, 2006)

Praise “They complimented me all the time... They told me I was smart, they told me I was handsome.” (Eichenwald

Escalating Requests $100 pose in underwear (Eichenwald, 2006) (Eichenwald, 2006)

Gifts Amazon wish list (Eichenwald, 2006) (Eichenwald, 2006)

Equipment Asante four-port hub (multiple cameras) Viking memory upgrade Color Webcam Intel Deluxe USB camera HP camera (Eichenwald, 2006)

Seduction Jason Berry UndressingShoweringMasturbating Having Sex (Eichenwald, 2006) (Eichenwald, 2006)

Enticement Computer camp Computer camp Invited to Michigan – sex with a girl Invited to Michigan – sex with a girl (Eichenwald, 2006)

Facilitating Helped with Pornographic website Justinscam.com Yahoo, AOL, MSN Free instant message services w/ video Stream live video free – if president could watch Sites – paid ads from teens & vote for favorites

Seduction Audience 1500 Hundreds of Thousands of Dollars (Eichenwald, 2006) (Eichenwald, 2006)

Who? Analyzed 300 of 1500 DoctorsLawyersBusinessTeachersEtc.

Money $45/month $300 hour long private shows (Eichenwald, 2006) (Eichenwald, 2006) Gil Tunno Intel employee Thousands meet for sex Signed apartment lease

Escalation Father helped New web site Live sex with prostitutes $35 monthly Discounts for 3 months, 6 months and annual memberships Cocaine & marijuana

Soliciting Signed up other teens

Three Generations of Risk Assessment Clinical JudgmentClinical Judgment Actuarial AssessmentActuarial Assessment Actuarial Plus DynamicActuarial Plus Dynamic

Approaches to Risk Assessment dSubjectsStudies Unstructured clinical.431,7239 Structured professional judgment Actuarial (sex).7014,16055 (Hanson & Morton-Bourgon 2007)

Decline in Violent Crime 2000 Lowest in 20 years (Butts & Travis, 2002)

Decline in Juvenile Crime Largest of any age group

Decline in Crime 2008 Property Crime Decreased 32%

Decline in Crime 2008 Violent Crime Decreased 41%

Decline in Crime 2008 Decline in Rape & Sexual Assault %

Multiple Norms Routine Sex Offenders (CSC) Routine Sex Offenders (CSC) Treatment Samples Treatment Samples Nonroutine Samples Nonroutine Samples High Risk Samples High Risk Samples

Base Rates Matter MoreOrFewer Reoffenders for each score

Which Norms to Use Correctional Services of Canada Routine Cases N = 2406 No screening procedures No pre-selection for tx, or civil commitment

Which Norms To Use? Preselected for Treatment Referred for sex offender specific treatment during current or prior incarceration Selected but no beds still selected

Which Norms to Use High Risk Sample Preselected for risk Preselected for risk Factors external to Static-99 Factors external to Static-99 SVP referral, mentally disordered, not guilty by reason of insanity, referred for intensive treatment SVP referral, mentally disordered, not guilty by reason of insanity, referred for intensive treatment

Non-routine Treatment sample Treatment sample High risk samples High risk samples Preselected for other reasons, e.g., offense severi Preselected for other reasons, e.g., offense severi

Norms “Most cases will use routine correctional sample” “Most cases will use routine correctional sample”

New Norms 10 Years ScoreRoutine5 Observ11ed Routine Adjusted Treatment Need High Risk

Scores Versus Recidivism Original Norms ScoreRiskYears ,1Low6% 9%10% 2,3Med/Low10% 14%18% 4,5Med/High29% 33%38% 6+High39% 45%52%

High Risk Sample Bengtson, 2008 Bengtson, 2008 Pre-trial psychiatric eval in Denmark Suspected of retardation or psychosis Bonta & Yessine, 2005 Bonta & Yessine, 2005 Dangerous Offenders- Dangerous Offenders- Indeterminate sentences Potential Dangerous Offenders Violent Offense after MR

High Risk Sample Haag, 2005 Haag, 2005 All Canadian offenders released at MR Knight and Thornton, 2007 Knight and Thornton, 2007 Massachusetts Treatment Center- Assessed or treated between Sexually dangerous persons

High Risk Samples Nicholaichuk, 2001 Nicholaichuk, 2001 Treated at Clearwater treatment program – maximum security forensic mental health facility Wilson & colleagues Wilson & colleagues Detained in prison until MR

Relative Risk vs Absolute Risk Relative risk consistent across 22 samples Relative risk consistent across 22 samples Absolute risk not consistent Absolute risk not consistent

Charges vs Convictions 13 samples used charges 15 used convictions

Reconviction Vs. Rearrest Rearrest = 1.4 x reconviction 10 Years RearrestReconviction Static %21% Static %27%

Child Molesters vs Rapists 53% child molesters 47% rapists

Treatment % Primarily treated samples Only one untreated sample

Samples N = samples Helmus N = samples

Sample Size Static99 = 8,893 Logistical regression 10 years 2,528

Sample Sizes High risk sample 722

Samples Sizes Routine2,406 Routine2,406 Non-Routine1,642 Non-Routine1,642 Treatment 866 Treatment 866 High Risk 722 High Risk 722

Old Sample Size Static

Aging and Risk of Sexual Offending

What Difference Does Age Make? Recidivism & aging -.10 (Hanson & Bussiere, 1998) Recidivism rates declined steadily with age Extrafamilial child molesters – maintained risk longer N =3751 (Hanson, 2002)

Age-at-release from custody Recidivism rate (%) Child molesters Rapists Incest offenders

Age & Recidivism Reanalysis of Hanson All groups declined steadily Own data – linear decrease with age N = 468 (Barbaree et al., 2003)

Fitted Sexual Recidivism Rates by Age Graphs

Each one unit increase in age was associated with 98% of the recidivism rate of the previous (younger) age Each one unit increase in age was associated with 98% of the recidivism rate of the previous (younger) age Recidivism rate of 32-year-olds was 98% of recidivism rate of 31 year- olds Recidivism rate of 32-year-olds was 98% of recidivism rate of 31 year- olds

Current age item did not adequately adjust for age Could have left old item and “fitted a complicated curvilinear age adjustment” Decided instead to create a new age item

With New Age Item Age of release does not add significant incremental predictive validity With old age item – Age of release does add predictive validity Meaning: New item adequately controls for age

Comparing Static-99 to Static-99R Validation Sample N = 2,392 ROC 5 Years ROC 10 Years Static Static-99R

New Age Item AgeScore 18 – – –

Score Range -3 to 12

Age 61 Attacked 73-year-old woman Giving him a church tour Stranger assault

Mr. Johnson AgeOffense History 59.5Exposure to officer 58Molestation 6 yr old boy 48Violent rape of 17-year-old boy – beat with chain

Mr. Johnson AgeOffense History 46Attempted molestation of 11-year-old 29“Has a history of sexual assault”

No High Risk Aging Sex Offenders?

When to Over-ride? Recent Offense – within 5 years Recent Offense – within 5 years History of continuous offending History of continuous offending No evidence of impact of aging No evidence of impact of aging

Risk Categories ScoreRisk Category -3 through 1Low 2,3Low-Moderate 4,5Moderate-High 6+High

Do Over-rides Help? Prediction of Recidivism (ROC) Recidivism Type Static-99Static-99 + Over-ride Static-99 + Stable Sexual Any violent

Static, Stable & Acute Static“Non-changeable life factors that Static“Non-changeable life factors that relate to risk for sexual recidivism, generally historical in nature”

Static, Stable & Acute Stable“Personality characteristics, skill deficits, and learned behaviours that relate to risk for sexual recidivism that may be changed through intervention Stable“Personality characteristics, skill deficits, and learned behaviours that relate to risk for sexual recidivism that may be changed through intervention Acute“Risk factors of short or unstable temporal duration that can change rapidly, generally as a result of environmental or intra-personal conditions” Acute“Risk factors of short or unstable temporal duration that can change rapidly, generally as a result of environmental or intra-personal conditions”

Static99R + Stable 2007 Static99R Score 3 Year Recidivism5 Year Recidivism Stable = 5 Stable = 14Routine High Risk 2 3% 7% 5% 12% 5 7% 18% 11% 25% 7 14% 32% 19% 38%

Aging and Psychopaths

Psychopathy and Age Age Period Mean Factor Score Factor 1 Factor 2 PCL-R N = 800+ Harpur & Hare 1994

Before & After Age 40 Male Offenders & Forensic Psychiatric Patients File InfoFile Info + InterviewAlone TotalDecrease.5Decrease 4 Factor 1Increase.5Decrease.5 Factor 2Decrease 1Decrease 4 (Hare, 2003)

Reduction in Criminality with Age 1/2 Reduce Criminal Activity 1/2 Reduce Criminal Activity About 35 to 40 Not for Violent Crime (Hare, McPherson & Forth, 1988; Harris, Rice & Cormier, 1991)

Ages % Any % Violent % Any % Violent Conviction Conviction Psychopaths42.9% 30% Nonpsychopaths40.4% 8.8% (Hare et. Al, 1992)

Psychopathy & Aging Almost ½ of psychopaths convicted of crimes after 40 Percentage of violent crimes increased (Hare et al., 1992)

“It appears that the psychopath’s propensity for violence and aggression may be relatively persistent across much of the life span.” (Hare, 1992, p.295)

Days Free on Conditional Release as a Function of PCL-R & Age Porter et al., 2001 Age Mean # Successful Days N = 224 N = 93

Older Psychopaths & Time in Community Age – days200 days 45 – days100 days (Porter et al., 2001)

“We found no evidence that older offenders scoring high on the PCL-R were more successful than their younger counterparts.” (Porter et al., 2001)

“Clearly, older psychopaths had far less opportunity to offend... This suggests that the age-related decline in criminal charges and convictions for psychopaths was, in part, an artifact, and that the criminal (and violent) propensities of the aging psychopaths may have been greatly underestimated.” (Hare, 2003, p. 62)

MnSOST-R Risk LevelSexual Recidivism Old Samples New Samples 112%15% 225%20% 357%30% Refer72%40%