Pedophilia: Research on Men Who Have Sex with Children

1. Pedophilia: Research on Men Who Have Sex with Children workshop for psychiatric residents Dr. Grant Harris August, 2004 (www.mhcp-research.com)

2. Who are Child Molesters? Males vs. Females Working Definitions Child Molesters Heterosexual Homosexual Bisexual Incest Pedophilia “Mixed” Offenders Effects of child molestation

3. Scientific Study (of Anything) Formal Measurement Systematic, Controlled Falsifiable hypothesis testing for... Explanation Prediction Consilience Objective?

4. Who are Child Molesters? History and Geography Perpetration vs. Victimization Incidence and Prevalence Offense Topographies Offender Typologies “Mixed” Offenders

5. Clinical Characteristics of Child Molesters Personality Mental Disorder Substance Abuse Emotionality Sexuality

6. Measurement of Sexual Preference Instrumentation Child Molester Studies Admitters vs. Not Validity and Reliability Faking Limitations

7. Measuring Men’s Sexual Interests:

11. Phallometry and Pedophilia Procedures Scoring and Interpretation Stimuli Faking Diagnostics Ethics New Methods

12. Research on the Prediction of Recidivism among Sex Offenders

13. Prediction of Violence Before Mid-80’s Examples Baxstrom (Steadman, 1973) Quinsey & Ambtman, 1979 Pasewark, Bieber, Bosten, Kiser, & Steadman, 1982 Monahan (1981)

14. Predictors of Violence in Offenders Big: Psychopathy, Juvenile delinquency, Childhood aggression, Employment problems, Didn’t live with natural parents Medium: Youthfulness, Criminal history, Adult violence, Antisocial personality, Prior psych admissions, Never married, Alcohol Small: Clinical opinion, IQ Not: Psychological distress, Remorse, Violent offense, Mood disorder, NGRI/NCR Inverse: Low self esteem; Psychosis

15. Prediction Among Child Molesters Child molester recidivism (Quinsey, 1986) 3 consistent predictors of sexual recidivism Number of previous sexual offenses Male victims Unrelated victims Frisbie & Dondis (1965) 1509 child molesters “sexual psychopaths” 3 above, + younger, more psychopathic

16. Sex Offender Recidivism Hanson & Bussiere (1996) Meta- Analysis of Predictors of Sexual Recidivism Strongest predictors had to do with sexual deviancy preference for children measured phallometrically Sexual criminal history Prior sexual offenses early onset of sexual offending Male victim Stranger victim Extrafamilial victim

17. Hanson & Bussiere Meta-Analysis (cont) Predictors (cont) Demographic Age (-ve) Never married Criminal lifestyle Total prior offenses Antisocial personality disorder Clinical Presentation Failure to complete treatment

18. Hanson & Bussiere Meta-Analysis (cont) Surprising nonpredictors Being sexually abused as a child Length of treatment Treatment motivation Denial of offense Depression Social skills

19. Characteristics of Psychopaths Glibness/Superficial charm Grandiose sense of self-worth Pathological lying Conning/manipulative Lack of remorse or guilt Shallow affect Callous/Lack of empathy Failure to accept responsibility Criminal versatility Promiscuous sexual behaviour Many short-term marital relationships

20. Characteristics of psychopaths Need for stimulation Parasitic lifestyle Poor behavioural controls Early behaviour problems Lack of realistic longterm goals Impulsivity Irresponsibility Juvenile delinquency Revocation of conditional release

21. Combining Predictors Clinical vs. Actuarial Prediction Grove & Meehl 1996 “We know of no social science controversy for which the empirical studies are so numerous, varied, and consistent as this one.” (p.318) Mossman 1994

22. Development of the VRAG 618 “mentally disordered offenders” Predictor Variables Demographic Criminal Psychiatric Childhood

23. Development of the VRAG 7 years average time at risk 31% committed a new violent offense Definition of violent offense

24. Development of the VRAG Analyses Multiple regression Divided sample into halves Univariate analyses Nuffield weighting system

25. Violence Risk Appraisal Guide Psychopathy Checklist Score Elementary school maladjustment Age at index offense* DSM III personality disorder Separation from parents before age 16 Failure on prior conditional release History of nonviolent offenses

26. Violence Risk Appraisal Guide Never married DSM III schizophrenia* Victim injury in index offense* History of alcohol abuse Male victim in index offense

29. How good is the instrument? What if we change the followup period? 3.5 years Baserate = 15% 7 years Baserate = 31% 10 years Baserate = 43%

30. How good is the instrument? What if we count only more serious or more frequent violent offenses? Count only things more serious than one assault or one armed robbery (>50 on our offense severity scale) 29% serious violent recidivism Equal accuracy in all cases

31. 

32. Replications (n=35)

33. Prediction of Violence Among Sex Offenders Do we need a special instrument? Higher rates of recidivism among sex offenders What do we want to predict?

34. The Sex Offender Risk Appraisal Guide (SORAG) Psychopathy Checklist Score Elementary school maladjustment Age at index offense* DSM III personality disorder Separation from parents before age 16 Failure on prior conditional release History of nonviolent offenses

35. The Sex Offender Risk Appraisal Guide (SORAG) Never married DSM III schizophrenia* History of alcohol abuse History of violent offenses History of sex offense convictions Male or adult victim (ever) Phallometric deviance

36. The VRAG for Sex Offenders Rice & Harris, 1997 159 new sex offenders 10 yr baserate= 58% r=.44 Barbaree & Seto, 1998 Hanson & Harris, 1998

37. Any prediction of true “sexual predators”? Survival analyses Sexual Recidivism Psychopaths vs. not Sexually deviant vs. not Interaction- “True sexual predators” (Rapists vs. child molesters)

39. Penetanguishene 1998 Study N= 417 sex offenders with an opportunity to reoffend 100 federal sex offenders from Kingston Pen 98 federal sex offenders from Abbotsford Regional Psychiatric Centre 219 sex offenders assessed in Oak Ridge approx. 119 were inpatients approx. 100 were outpatients

40. Summary Prediction Accuracy Risk is long-term Psychopathy and Sexual Deviance Incest Offenders Treatment Evaluation

41. Implications for Criminal Justice Policy Dangerous Offenders Dangerous Mentally Disordered Offenders Longterm Offenders Sexual Predators

42. Illustrative VRAG ROC areas

43. The future of prediction efforts Improving performance of actuarial tools Constant followup No missing items Reliably scored Actual items vs. approximations

44. Optimizing ROC areas E.g. VRAG predicting violent recidivism: Area Mean followup, all subjects .73 No missing data (N= 46) .80 Exact 3 yr. followup + .84 no missing data

45. Using the SORAG and other actuarial methods The basis for decisions The basis for policy Procedural fairness Therapeutic jurisprudence Testifying in court and in other forums The legal criteria for expertise The adversarial process

46. The Psychosocial History Essential for assessment and planning Multiple sources Collateral sources Biography not Autobiography A standardized clinical task

47. Conclusions We can do a good job of predicting violence Must use an actuarial approach to combine variables Reliability Predictive validity Norms, percentiles, SEM Probabilistic statement Can improve public safety without detaining more patients

48. Research on Father-Daughter Child Molesters: Implications for Explanation and Assessment -What we’re talking about is a kind of incest that virtually no one would condone or joke about-What we’re talking about is a kind of incest that virtually no one would condone or joke about

49. What is incest? Legal definition: Criminal Code of Canada Every one commits incest who, knowing that another person is by blood relationship his or her parent,child, brother, sister, grandparent or grandchild, as the case may be, has sexual intercourse with that person. (“brother” and “sister” include half-brother and half-sister) Research/clinical definition: No need for blood relationship No need for sexual intercourse Research mostly involves children < approx. 16 Universality of incest taboos -Incest avoidance is a fundamental organizing principle of every human societyUniversality of incest taboos -Incest avoidance is a fundamental organizing principle of every human society

50. Human Incest: Frequency (legal) Overall, how prevalent is incest? Depends how we define it, of course, and how we measure it. But it is thankfully relatively rare in the general population. Toronto 1994-1996 2736 sexual assault incident reports, only 65 instances of incest. Of course, no number except 0 is small enough. --incest charges in 1961 in England and Wales-- Remember, we’re talking about the criminal definition of incest here! --notice how few are mother-son and none are grandmother-son!Over a 10 yr. Period, there were in all 15 trials of females for incest as against 1372 males!Overall, how prevalent is incest? Depends how we define it, of course, and how we measure it. But it is thankfully relatively rare in the general population. Toronto 1994-1996 2736 sexual assault incident reports, only 65 instances of incest. Of course, no number except 0 is small enough. --incest charges in 1961 in England and Wales-- Remember, we’re talking about the criminal definition of incest here! --notice how few are mother-son and none are grandmother-son!Over a 10 yr. Period, there were in all 15 trials of females for incest as against 1372 males!

51. Incest avoidance among non-humans Animal studies Many animals avoid incest by juvenile dispersal sex differences in the age of maturation lack of sexual interest in individually recognized relatives Mammalian Examples Rhesus monkeys Deer mice Prairie dogs Juvenile dispersal = young all move away, or 1 sex moves Most mammals have incest avoidance mechanisms -Rhesus monkeys: When a male rhesus monkey matures, he will copulate with females of the same age as his mother, but not with his mother -Deer mice: If individually caged at weaning and subsequently placed in opposite-sexed pairs at maturity, littermates are considerably more reluctant to mate than are strangers -Prairie dogs: In nature, a yearling female prairie dog will come into estrus in the absence of her father but will delay first estrus if he is still around Juvenile dispersal = young all move away, or 1 sex moves Most mammals have incest avoidance mechanisms -Rhesus monkeys: When a male rhesus monkey matures, he will copulate with females of the same age as his mother, but not with his mother -Deer mice: If individually caged at weaning and subsequently placed in opposite-sexed pairs at maturity, littermates are considerably more reluctant to mate than are strangers -Prairie dogs: In nature, a yearling female prairie dog will come into estrus in the absence of her father but will delay first estrus if he is still around

52. The puzzle of father-daughter sexual assault Deleterious effects of inbreeding Especially among first and second degree relatives Costs to females versus costs to males -Inbreeding depression: Abundant data from many animal species including humans demonstrate that matings of close relatives produces offspring of reduced fertility and viability...Everyone carries a few rare deleterious recessive genes that are not normally expressed, and some of these rare recessives, duplicated by immediate descent in close kin, become homozygous in the progeny of inbreeding…. There is also an increase in close kin in the variance of the genetic liability to multifactorial conditions, thus increasing the risk of common congenital malformations and of mental retardation ..Thus, there is a substantial selection pressure in natural populations to avoid inbreeding…Studies of parent-child and brother-sister incest among humans show that they are very much more likely than offspring of unrelated parents to suffer abnormality, mental retardation,and death. Offspring of 2nd degree relatives, much less but still lots higher than unrelated. By the time we get to 3rd degree (eg. 1st cousins), not much elevated over unrelated. So, is it just a coincidence then that marriage laws tend to draw the line at around 3rd degree relatives? True even in societies who don’t know what the data say.. -And the cost of incest to females is much higher than for males. Because males can mate an almost unlimited number of times, he can afford to engage in risky sexual behaviors- risky, that is, from the point of view of the likelihood of producing offspring who themselves survive to reproduce. He can afford to engage in incestuous matings-- if the offspring survive to reproduce, he has gained a lot. If not (or even if so) he can engage in other nonincestuous matings where the offspring have a greater chance of survival to reproduce -But for females, incestuous matings are very costly as she can only have a limited number of pregnancies and can only rear a very limited number of children. So, more reason for females to avoid incest than for males -Inbreeding depression: Abundant data from many animal species including humans demonstrate that matings of close relatives produces offspring of reduced fertility and viability...Everyone carries a few rare deleterious recessive genes that are not normally expressed, and some of these rare recessives, duplicated by immediate descent in close kin, become homozygous in the progeny of inbreeding…. There is also an increase in close kin in the variance of the genetic liability to multifactorial conditions, thus increasing the risk of common congenital malformations and of mental retardation ..Thus, there is a substantial selection pressure in natural populations to avoid inbreeding…Studies of parent-child and brother-sister incest among humans show that they are very much more likely than offspring of unrelated parents to suffer abnormality, mental retardation,and death. Offspring of 2nd degree relatives, much less but still lots higher than unrelated. By the time we get to 3rd degree (eg. 1st cousins), not much elevated over unrelated. So, is it just a coincidence then that marriage laws tend to draw the line at around 3rd degree relatives? True even in societies who don’t know what the data say.. -And the cost of incest to females is much higher than for males. Because males can mate an almost unlimited number of times, he can afford to engage in risky sexual behaviors- risky, that is, from the point of view of the likelihood of producing offspring who themselves survive to reproduce. He can afford to engage in incestuous matings-- if the offspring survive to reproduce, he has gained a lot. If not (or even if so) he can engage in other nonincestuous matings where the offspring have a greater chance of survival to reproduce -But for females, incestuous matings are very costly as she can only have a limited number of pregnancies and can only rear a very limited number of children. So, more reason for females to avoid incest than for males

53. Rice & Harris (2002) 82 “incest” offenders: 52 molested their own biological daughters 30 molested stepdaughters or other non-genetically related “daughters” 37 of the above also had extrafamilial female victims 102 extrafamilial offenders vs. females

54. Characteristics of intra- and extra-familial child molesters Offender sexually abused as a child 35% Incest in offender’s family 17% Had drug or alcohol problems 33% -Offender sexually abused as a child is measured by self-report after the offender is apprehended -Mostly similar to findings in review paper by Williams & Finkelhor (1990) and their empirical study of 1995-Offender sexually abused as a child is measured by self-report after the offender is apprehended -Mostly similar to findings in review paper by Williams & Finkelhor (1990) and their empirical study of 1995

55. Father-daughter and other child molesters - In general, incest offenders lower risk on everything than nonincest - In general, genetic lower risk than other incest -In general, genetic & step lower risk than mixed- In general, incest offenders lower risk on everything than nonincest - In general, genetic lower risk than other incest -In general, genetic & step lower risk than mixed

56. Father-daughter and other child molesters - In general, incest offenders lower risk on everything than nonincest - In general, genetic lower risk than other incest -In general, genetic & step lower risk than mixed- In general, incest offenders lower risk on everything than nonincest - In general, genetic lower risk than other incest -In general, genetic & step lower risk than mixed

57. % with deviant preferences 3 slides 1. Results did NOT support hypotheses- Biological fathers were least deviant Not surprisingly, fathers who molested children inside and outside the home were the most deviant Next slide 2. How did they compare to extrafamilial child molesters? Next slide 3. How did they compare to controls?3 slides 1. Results did NOT support hypotheses- Biological fathers were least deviant Not surprisingly, fathers who molested children inside and outside the home were the most deviant Next slide 2. How did they compare to extrafamilial child molesters? Next slide 3. How did they compare to controls?

58. Mean VRAG and SORAG scores and rates of violent recidivism

59. VRAG/SORAG predicting recidivism (ROC areas)

60. Incest Offenders Importance of risk assessment Importance of careful history Importance of sexual deviance Incest avoidance -- where is it?

61. Four explanatory factors Sexual preferences and pedophilia Failure of incest avoidance Mate deprivation; opportunity Psychopathy, antisociality

62. Practical Implications Similar to other child molesters: Importance of careful history Don’t assume no extrafamilial victims Importance of sexual deviance Importance of risk assessment Instruments developed for other offenders work just as well for incest offenders -Idea of having fathers look after daughters and be more involved in child-rearing? -Idea of having fathers look after daughters and be more involved in child-rearing?

64. Sex Offenders with Developmental Disabilities: Sexual Preferences and Risk Assessment Background Our study Method Results History Phallometric Recidivism Discussion Summary, Implications, and Conclusions

65. Background Sex offenses overrepresented in developmentally disabled (Hawk et al., 1993) especially offenses against males () especially against children

66. Developmentally Disabled vs. Other Sex Offenders 58 Developmentally Disabled Sex Offenders Matched to sex offenders of normal IQ ... … on general offense type (n = 45) Mean age 29.8 (17.0) 65% DD Programs vs. 87% Oak Ridge

67. IQ

68. Nonviolent Criminal History

69. Violent Criminal History

70. Violent Sexual History

71. Neurological Problems (%)

72. Prenatal/perinatal problems

73. Difficult Child/Aggression

74. Childhood Abuse Score

75. Male Victims

76. Victims under age 5

77. Total Number of Victims

78. Phallometric Testing

79. Phallometric Response < 5 (z)

80. Sexual Deviance - Age

81. Sexual Deviance - Activity

82. Recidivism

83. Discussion Why are developmentally handicapped child molesters more likely to choose male victims? The maternal immune hypothesis (Blanchard, 2001) Why are developmentally disabled offenders more likely to pick younger victims?

84. Child Molesters’ Paradoxical Sexual Interests?

85. Child Molesters’ Paradoxical Sexual Interests Pragmatic Questions Phallometric testing Viewing time, ratings, attitude/value questions Screening method Theoretical Questions Critical features? Size, body shape, skin texture, behavioral, ... Neoteny?

86. Phallometry and “Older” Stimuli

87. CMs by Victim Age; Female Stimuli; Standardized

88. Waist - Hip Ratio of Female Stimuli IRR: r = .83 Younger Adult Women: .691 Older Adult Women: .790 Pubescent Girls: .800 Girls 5-11 years: .819 Girls under 5 years: .888

89. Aggregate Correlations: Non-Offenders

90. Aggregate Correlations: Child Molesters (n=36)

91. Child Molesters by Victim Ages Victims 12 years or older (n=18): r (Phall::WHR) = -.40 All Victims under 12 years (n=18): r (Phall::WHR) = .10

92. A Tentative Hypothesis About Male Sexual Preferences and Pedophilia

93. Altered WHR and Mean Ratings

94. Non Offenders -- Altered WHR Attractiveness Ratings Between Subjects: E(r/Ho) = 1.0 r = .27 Signed Ranks: p <.10

95. Has the Effectiveness of Sex Offender Treatment Been Established?

96. What Has Been Established About Offender Treatment: Effectiveness can be Achieved Principles of Risk, Need, Responsivity Ineffective interventions Possibility of Harm

97. What has Been Established About Risk Assessment Power of static historical predictors Absence of “Clinical” predictors Contribution of treatment?

98. What has been established about the causes of sex offending Sexual deviance? Antisociality? Social skill or emotional deficits? Cognitive distortions?

99. What has been Established About Sex Offender Treatment Refusing, declining, quitting, being ejected predicts recidivism… Volunteering, persisting, complying, completing predicts success. Opportunity increases recidivism

100. General versus Specific Effects Selection Expectancy Bias … And Other Threats to Internal Validity

101. What has not been Established About Sex Offender Treatment Size of Specific Effect * Elements of Specific Effect * Offender Types * *(if there is one)

102. Sex Offender Treatment and Knowledge Practice: Over 30 years, two random studies Refusers or ?? preferred controls Offender groups Treatment types and elements Nonstandardized outcomes

103. Improving Knowledge Practice Revise the standards? The role of meta-analysis -- what it can and can’t do... ? Low power and sampling error ? General knowledge practice failure

104. Why does it matter; who cares whether the effects are general or specific? Preventing even one victim is worthwhile A placebo effect is still an effect Rigorous standards discourage therapy and evaluation

105. Why does the size of the specific effect matter? Possibility of harm -- victims plus... Resources are limited Opportunities are limited A treatment implies a theory

106. Conclusions: Poor adherence to good KP Random designs Barbaree & Seto Not established <> No effect… But,… We should not give up... But,... And we’re makin’ progress