Adverse Childhood Experiences Among Sexual Offenders: Associations With Sexual Recidivism Risk and Psychopathology

Abstract

Adverse childhood experiences (ACEs) are increasingly recognized as a public health crisis. Cumulative effects of these experiences lead to a wide range of deleterious physical and psychological outcomes. Prior research has identified higher prevalence rates of ACEs and increased criminal behavior in samples of individuals who have committed sexual offenses. In a sample of civilly committed individuals who have committed sexual offenses (N = 317), we examined the prevalence of ACEs (cumulative scores and the two components of child harm and family dysfunction) and their association with risk for sexual recidivism and adult psychopathology. ACEs were much more prevalent in this sample compared with the general population and to lower risk samples of individuals who had committed sexual offenses. Although ACE scores were unrelated to risk for sexual recidivism, higher ACE scores were associated with increased risk of psychopathology, including anxiety disorders, depressive disorders, substance use disorders, and Antisocial Personality Disorder. ACEs related to family dysfunction were uniquely associated with Alcohol Use Disorder and the presence of a dual diagnosis of a paraphilia and personality disorder. Results suggest that higher risk individuals who commit sexual offenses may have greater need for trauma-informed models of care that recognize the effect of these experiences on their mental health and offense-related behavior.

Keywords

adverse childhood experiences (ACE)trauma-informed care sexual offenses psychopathology sexual recidivism

Until two decades ago, research was limited on the co-occurrence of childhood abuse and household dysfunction, and the long-term impact of these early events on health outcomes in adulthood. The Adverse Childhood Experiences (ACE) study, a large collaborative research project involving over 17,000 participants, shed light on the rate at which the general population reported adverse experiences during childhood (Centers for Disease Control and Prevention [CDC], 2013; Felitti et al., 1998). This groundbreaking study highlighted 10 items in two ACE domains of early adversity: child maltreatment (emotional and physical neglect; physical, emotional, and sexual abuse) and household dysfunction (witnessing domestic violence; parent separation, having a household member incarcerated; and being raised with a mentally ill or substance abusing household member). In the general population, two thirds of adults reported experiencing at least one form of childhood trauma and 13% reported four or more.

These 10 ACEs frequently co-occur, producing dose–response relationships between ACE scores and a myriad of health and social problems in adolescence and adulthood (Copeland et al., 2018; De Venter et al., 2013; Dong et al., 2004; Dube et al., 2001; Kelly-Irving et al., 2013; Lalor & McElvaney, 2010; Liu et al., 2016; Ramiro et al., 2010; Suliman et al., 2009). Exposure to abuse, neglect, and other stressors during childhood and adolescence affects development and functioning of the brain as well as neuroendocrine processes related to stress responsiveness and hyperarousal (e.g., Nemeroff, 2004). These altered physiological processes carry forward as a biological embedding of stress sensitization and can create pathways to later psychopathology (Danese et al., 2009; Jaffee & Christian, 2014). Problematic adult outcomes associated with ACEs include substance abuse, depression, suicide attempts, and problematic sexual behavior (e.g., promiscuity, sexually transmitted diseases) in addition to detrimental effects on brain development (Anda et al., 2010; Anda et al., 2006; Cicchetti, 2013; Dube et al., 2003; Felitti et al., 1998; Teicher et al., 2003). As the number of adverse childhood events increases, physical and mental health problems in adulthood accumulate. The impact of multiple ACEs is not only additive, but multiplicative, with individuals who experience four or more ACEs demonstrating greater susceptibility to negative outcomes (Putnam et al., 2013). Indeed, the presence of multiple ACEs greatly increases risk for mental disorders, substance use, and overall stress levels, as well as increasing the likelihood of comorbid physical and mental health conditions (Anda et al., 2006).

Emerging research suggests that ACEs are common among individuals who have committed sexual offenses in adulthood (Jespersen et al., 2009; Reavis et al., 2013). ACEs are also higher in this group compared with general population samples, and may be associated with increased risk for future recidivism (Levenson et al., 2016, 2017) and psychopathology (J. K. Lee et al., 2002). The current study sought to examine the prevalence of ACEs in a sample of males civilly committed as sexually violent persons (SVPs), as well as to explore the impact of ACEs on sexual recidivism risk and psychopathology. Examining the prevalence of ACEs in a civilly committed sample is especially relevant given their greater perceived likelihood of reoffending and increased rates of psychopathology.

ACEs in Sex Offending Populations and Links to Criminality

Early theoretical models and subsequent research examining ACEs in those who have committed sexual offenses focused on the link between childhood sexual abuse and adult sexual offending (e.g., Garland & Dougher, 1990; Glasser et al., 2001; Groth, 1979; Hanson & Slater, 1988; Jespersen et al., 2009; Ogloff et al., 2012; Seghorn et al., 1987; Seto, 2008; Seto & Lalumière, 2010; Ward et al., 2006; Widom & Ames, 1994). Subsequent and broader research found an array of ACEs to be common among those who have committed sexual crimes (e.g., Leach et al., 2016; Levenson et al., 2016; Reavis et al., 2013; Widom & Massey, 2015), and that those who have committed sexual offenses report ACEs at higher rates than the general population (Levenson et al., 2016) and non-sexual offenders (Reavis et al., 2013). For example, a prospective longitudinal study following a large birth cohort in Queensland found that sexual offending in adolescence and young adulthood was associated with multiple types of prior maltreatment, such as physical, sexual, emotional abuse and neglect (Leach et al., 2016). More recently, prevalence rates of ACEs in a mixed sample of 679 individuals who committed sexual offenses (28% civil commitment and 72% outpatient) were compared with the general population sample from the original CDC study (Levenson et al., 2016). Less than 16% of men with sexual offense histories had a score of zero on the ACE scale (compared with 38% of males in the general population) while almost half (46%) of the study sample endorsed four or more ACE items (compared with 9% of males in the general population). Notably, the odds of having experienced childhood sexual abuse (odds ratio [OR] = 3.22) and physical abuse (OR = 1.71) were far higher, compared with the general population (Levenson et al., 2016).

Adverse childhood experiences are linked to juvenile and adult criminality more generally, emerging as a potential predictor of future violent and aggressive behavior (Craig et al., 2017; Krischer & Sevecke, 2008; L. A. Marshall & Cooke, 1999; Reavis et al., 2013; Topitzes et al., 2011; Widom & Maxfield, 2001). Research focusing on sexual offenders, in particular, has found higher ACE scores to be associated with more police contacts for both general and sexual criminality. A recent study examining ACEs and sexual homicide found that the odds of having a record of sexual homicide increased with additional experiences of childhood maltreatment/victimization (DeLisi & Beauregard, 2018). In a mixed sample of both civilly committed and outpatient sexual offenders, higher ACE scores were associated with more arrests for a range of crimes, including driving offenses, property crime, non-sexual assault and battery, and sexual offenses (Levenson & Socia, 2016). Increased ACEs were also linked to heightened risk for future sexual recidivism, using a simulated risk score from the Static-99R (Levenson et al., 2016).

Increased odds of abuse among those who have sexually offended are consistent with theoretical frameworks that suggest adverse developmental experiences may be an etiological factor contributing to the commission of sexual offenses as an adult (Beech & Ward, 2004). However, a more integrated theory of sexual offending suggests that multiple interacting causal factors related to biological, ecological (i.e., social, cultural), and neuropsychological conditions interact to produce clinical disturbances including offense-related thoughts and fantasies (Ward & Beech, 2006). Exposure to early adversity in the form of abuse, neglect, or chaotic home environments contributes to neurobiological changes in the brain such as self-regulation deficits, distorted cognitive schema, disorganized attachment styles, and poor boundaries, which increases risk for sexual and other criminal offending (Cicchetti & Banny, 2014; Grady et al., 2016; W. L. Marshall, 2010). Thus, integrated and trauma-informed theories of sexual offending provide a foundation for understanding the link between childhood adversity and adult criminality. As our understanding of sexually abusive behavior is refined, effective treatments and prevention strategies are more likely to be developed. Examining the prevalence rates among high-risk civilly committed samples may help guide the development of treatment and prevention efforts using trauma-informed approaches.

ACEs and Psychopathology

Adverse childhood experiences also play a role in the development of serious psychopathology and maladaptive personality traits, especially when they co-occur and produce a cumulative effect. In the seminal ACE study, those who had experienced four or more ACEs had up to 12 times greater risk for substance abuse, depression, and suicide attempts, compared with those with no ACEs (Felitti et al., 1998). In a large national sample of U.S. adults, the presence of three or more ACEs further increased the odds (OR range 2.5 to 4.6) of complex adult psychopathology, while in contrast, the absence of ACEs served as a protective factor against the development of adult psychopathology (Putnam et al., 2013). Congruent with this research, latent class analyses of national epidemiological survey data found groups identified as having multiple ACEs to show increased likelihood of both internalizing (e.g., Major Depressive Disorder, Generalized Anxiety Disorder) and externalizing (e.g., Alcohol Use Disorder, Antisocial Personality Disorder) forms of psychopathology (Curran et al., 2016).

Adverse experiences during childhood are also believed to impact personality development (e.g., Battle et al., 2004; Bierer et al., 2003; Tyrka et al., 2009). Among an Australian community sample, as the number of ACEs increased, the odds for neuroticism and negative affect also increased (OR = 2.6), as did the odds for behavioral inhibition or dissocial behavior (OR = 1.7; Rosenman & Rodgers, 2006). Several studies have demonstrated associations between ACEs and Antisocial Personality Disorder (Bierer et al., 2003; Douglas et al., 2011), even after controlling for other psychopathology and related demographic variables (Afifi et al., 2011). The development of personality pathology in response to relational trauma is theorized to derive from the child’s dilemma of dependence on caregivers who are simultaneously absent or dangerous (Carlson & Sroufe, 1995; Jovev & Jackson, 2004). In addition, chronic and cumulative abuse, neglect, or family dysfunction in childhood creates a suspended stress response leading to hypervigilance and pervasive scanning of the environment for potential danger (van der Kolk, 2006). The excess of stress hormones can alter the brain’s architecture, causing the amygdala to become over active, and misperceive benign environmental triggers as threatening (Alink et al., 2012). At the same time, areas of the brain that are involved in executive functioning may not develop as expected, leading to dysregulation, impulsivity, and impaired relationship skills (Cheng et al., 2019; Holley et al., 2017). These impairments can have a lasting impact into adulthood leading to the development of internalizing and externalizing forms of psychopathology.

The influence of ACEs on development of psychopathology among individuals who have committed sexual offenses or exhibit symptoms of paraphilic diagnoses is unclear. A comparison of ACEs in offender groups (sexual offenders versus a comparison property offender group) found individuals who had experienced emotional abuse, sexual abuse, and family dysfunction had increased odds (OR range 3.32 to 3.88) of receiving a paraphilic diagnosis, though physical abuse was unrelated to any paraphilic diagnosis (J. K. Lee et al., 2002). The specific ACEs of emotional/verbal abuse and family dysfunction were associated with the development of pedophilia, exhibitionism, and having multiple paraphilias (J. K. Lee et al., 2002). Other research examining underlying symptomatology of paraphilic diagnoses in a large twin sample found that sexually coercive behavior, symptomatic of Sexual Sadism, was more common (OR = 2.31) among those with a history of maltreatment (Forsman et al., 2015).

In summary, although previous research has examined the frequency of ACEs in individuals who have committed sexual offenses, no prior study has focused exclusively on a high-risk sample, such as those who have been civilly committed because of their increased risk to sexually reoffend. In addition, although Levenson and colleagues (2016) found a significant association between ACEs and recidivism risk, two thirds of their participants were being treated as outpatients and might be classified as lower risk. Furthermore, their recidivism risk score was simulated to approximate the Static-99R, rather than the actual Static-99R score. Examining this association among high-risk sexual offenders is important for conceptualizing the impact of ACEs on the development of abusive behavior and incorporating trauma-informed models that might enhance treatment effectiveness. Furthermore, increased risk of psychopathology (e.g., depression, anxiety, and substance abuse) has been linked to ACEs in the general population, and thus a better understanding of ACEs and psychiatric diagnoses among those who are civilly committed may contribute to improved responses to their complex treatment needs.

Current Study

The first aim of the current study was to understand the frequency of ACEs in a sample of high-risk civilly committed sexual offenders and compare this rate to other samples (general population and other individuals with histories of sexual offending). The second aim was to examine the relationship between ACEs and risk for sexual recidivism with a commonly used risk assessment instrument for sexual offenders, the Static-99R. Based on previous research (Levenson et al., 2016), we hypothesized that patients with higher ACE scores would be at greater risk for sexual recidivism. A third aim was to examine associations between ACE scores and diagnoses of adult psychopathology in our sample, including anxiety, depression, substance use, paraphilias, and Antisocial Personality Disorder. Congruent with past research, we hypothesized that higher incidents of ACEs would increase the odds of both externalizing and internalizing psychopathology. Following recent calls to “unpack” (or examine separately) various risk factors including ACEs, we also examined whether the two underlying ACE domains (childhood maltreatment and household dysfunction) were differentially related to sexual recidivism risk and adult psychopathology (Atzl et al., 2019; Masten & Narayan, 2012; Narayan et al., 2017). Although we made no specific hypotheses regarding these different domains, prior research suggests childhood maltreatment and household dysfunction may have differential effects on adult psychopathology (e.g., Higgins & McCabe, 2003).

Method

Participants

The sample for the study consisted of 317 adult males who had committed sexual offenses and were currently civilly committed at Sand Ridge Secure Treatment Center, a maximum-security forensic hospital, under Wisconsin Statute 980 pertaining to the civil commitment of sexually violent persons (SVPs). The mean age was 51.38 years (SD = 10.48). The primary ethnic category was Caucasian (69.1%), followed by African American (23.3%), Native American (4.7%), Hispanic (2.2%), and Other (0.6%). Because of the relatively low frequency of ethnic groups other than Caucasian, the participants were dichotomized into two different ethnic groups: “Minorities” (0) and “Caucasians” (1) for analytic purposes. Data were collected from participants as part of routine clinical practice or during yearly risk evaluations.

Measures

Adverse childhood experiences

The Adverse Childhood Experiences (ACE) scale (Felitti et al., 1998) is a self-report tool consisting of 10 dichotomous (yes/no) items yielding a total score ranging from 0 (having experienced zero ACEs on the scale) to 10 (having experienced all 10 ACEs). The ACE items were adapted from the Conflict Tactics Scale (Straus & Gelles, 1990), the Child Trauma Questionnaire (Bernstein et al., 1994), and survey questions about sexual abuse (Wyatt, 1985). The ACE scale includes five items regarding child harm (Emotional Abuse, Physical Abuse, Sexual Abuse, Emotional Neglect, and Physical Neglect), and five items regarding household dysfunction (Parental Separation/Divorce, Family/Domestic Violence, Household Substance Abuse, Household Mental Illness, and Incarceration of a Household Member). Several prior studies have shown the ACE scale demonstrates adequate test–retest reliability (Dube et al., 2004; Mersky et al., 2017; Pinto et al., 2014). Internal scale consistency for the total ACE score in the current sample was acceptable (α = .79; Cortina, 1993) and consistent with past reliability estimates (e.g., Easton, 2012). Internal scale consistency for the child maltreatment and household dysfunction scales were .73 and .64, respectively. Descriptive statistics of the ACE scale in this sample are presented in the results section.

Static-99R

The Static-99R (Hanson & Thornton, 1999) is an actuarial measure that assesses items which have an empirical relationship to sexual recidivism. It is a 10-item scale, completed by a trained rater, with a total score range of −3 to 12. The 10 items include age, criminal history (e.g., prior sex offenses and number of prior sentencing dates), and victim characteristics (e.g., stranger, male, or unrelated victims). Total scores are interpreted to reflect five relative risk categories: very low risk (−3 to −2), below average risk (−1 to 0), average risk (1 to 3), above average risk (4 to 5), and well above average risk (6 to 12). The scale assesses the likelihood of sexual recidivism in adult male sexual offenders who are 18 years old or older at the time of release into the community. In a meta-analysis of 23 samples including over 8,000 subjects, the Static-99R was found to adequately predict sexual recidivism (area under the curve [AUC] of .705) over an average follow-up period of approximately 8 years (Helmus et al., 2012). More recent studies also support the use of Static-99R scores, finding AUCs for predicting sexual recidivism in the range of .734 to .824 in Canadian (Hanson et al., 2015) and California samples (Hanson et al., 2014). In the current sample, Static-99R scores ranged from 0 to 10 (M = 5.54; SD = 1.57).

DSM-5 diagnoses

Psychiatric diagnoses, (Diagnostic and Statistical Manual of Mental Disorders 5th ed. DSM-5; American Psychiatric Association, 2013) were taken from the most recent annual risk assessment evaluations conducted by licensed forensic psychologists and medical records where the patient was treated by a staff psychiatrist. Pedophilic Disorder was the most common diagnosis in this population, with 52% of patients meeting criteria. Approximately 40% had another paraphilic disorder diagnosis (e.g., Other Specified Paraphilic Disorder, Exhibitionistic Disorder, or Sexual Sadism Disorder). Almost half of the patients were diagnosed with an Alcohol Use Disorder (47%), while a third (33%) were diagnosed with another substance use disorder (e.g., Opioid Use Disorder or Stimulant Use Disorder). About 21% were diagnosed with an anxiety disorder (e.g., Generalized Anxiety Disorder, Posttraumatic Stress Disorder) and 28% were diagnosed with a depressive disorder (e.g., Major Depressive Disorder, Persistent Depressive Disorder [Dysthymia]). The most common personality disorder was Antisocial Personality Disorder (ASPD), with 53% of the patients receiving this diagnosis.

Diagnostic categories of (a) any anxiety disorder, (b) any depressive disorder, (c) Pedophilic Disorder, (d) any other paraphilic disorder, (e) Alcohol Use Disorder, (f) other substance use disorder, and (g) Antisocial Personality Disorder were created. A category was also created for individuals who presented with both a paraphilic disorder and any personality disorder. The creation of this category was intended to be a proxy for the presence of sexual deviance and psychopathy, which prior research suggests distinguishes a unique group of sexual offenders that is higher risk (e.g., Hawes et al., 2013). All categories were coded as 0 = not present, 1 = present.

Procedures

The current study used archival data. The data were generated as part of annual forensic examinations or intake procedures. As part of a trauma-informed care (TIC) treatment initiative, the ACE scale was administered to all patients who were participating in treatment at the facility during the calendar years of 2015 and 2016. Six patients declined to complete the ACE form. Static-99R scores were obtained from the annual risk evaluations conducted for patients in 2016. Psychiatric diagnoses were taken from two sources: the 2016 annual risk evaluation and the institution medical file. In general, these records are consistent; however, where a discrepancy was present, the most recent diagnostic data were used. IQ scores were obtained from an institution database where intake test results are stored. Institutional Review Board approval for the study was obtained for the use of archival data from the Institutional Review Board at Sand Ridge Secure Treatment Center, and all authors were listed on the application.

Data Analytic Plan

Prevalence of ACEs and comparison to other samples were calculated using frequency distributions, odds ratio comparisons, point-biserial correlations, and phi coefficients of association (φ). Hierarchical linear regression was used to examine the association between the ACE and Static-99R total scores, controlling for race and full scale IQ, as measured by the Wechsler Adult Intelligence Scale, Fourth Edition (WAIS-IV; Wechsler, 2008). We controlled for race due to past research showing African Americans score higher on the Static-99R (Hanson et al., 2014; S. C. Lee & Hanson, 2017). Similarly, IQ was used as a control variable as prior research has suggested lower IQ scores are associated with higher Static-99R scores (Stephens et al., 2018). Linear regression models were also used to assess whether the underlying ACE domains of child harm and household dysfunction were differentially related to risk for sexual recidivism.

Binary logistic regression was used to assess associations between ACE total scores and DSM-5 diagnoses. We also conducted logistic regression analyses to explore the underlying ACE domains as they related to the coded DSM-5 diagnostic categories. Race was included in all logistic regression models as it was significantly correlated with many of the outcome variables (r’s ranging from .12 to .34). In addition, age was included to determine whether any associations were consistent across the large age range in our sample (range = 26–84). Model fit measures are reported as recommended by Field (2009) using both Cox and Snell R² and Nagelkerke’s R². Unstandardized beta (b), standardized beta (b*), and odds ratios (OR) with 95% confidence intervals are included for relevant regression models. SPSS v. 24 and Excel 2010 (for odds ratio comparisons) were used for analyses.

Results

Prevalence of ACEs

The mean ACE total score for this population of civilly committed sex offenders was 4.85 (SD = 2.80), which is significantly higher than the mean total score of 3.50 (SD = 2.74) found in a large mixed sample of outpatient and civilly committed male sex offenders, t(316) = 8.60, p < .001 (Levenson et al., 2016). The average score for the child harm domain (M = 2.69, SD = 1.69) was significantly higher, t(317) = 5.88, p < .001, than the average score for the household dysfunction domain (M = 2.16, SD = 1.54). Table 1 provides the proportion of individuals who endorsed each individual ACE item. Experiencing child harm, such as physical or verbal abuse, was more prevalent than household dysfunction, such as witnessing domestic violence or having a household member incarcerated. ACE items that were most frequently endorsed included physical abuse (67.5%), verbal abuse (60.3%), parents being separated/divorced (59.9%), sexual abuse (56.8%), and experiencing substance abuse by a family member in the home (58.0%).

Table 1.

Comparison of ACE Item Endorsement of Current Sample With Prior National Sample and Sample of Sex Offenders.

ACE items	Current sample (n = 317)	Male CDC (n = 7,970)	Odds ratio A	Levenson et al. (n = 679)	Odds ratio B
Verbal abuse	67.5%	7.6%	25.26 [19.69, 32.41]	53.3%	1.82 [1.38, 2.41]
Physical abuse	60.6%	29.9%	3.60 [2.86, 4.53]	42.2%	2.10 [1.50, 2.76]
Sexual abuse	56.5%	16%	6.81 [5.41, 8.57]	38%	2.12 [1.51, 2.77]
Emotional neglect	52.1%	12.4%	7.67 [6.09, 9.65]	37.6%	1.80 [1.38, 2.36]
Physical neglect	32.5%	10.7%	4.02 [3.14, 5.13]	15.9%	2.55 [1.86, 3.48]
Parents divorced/separated	60.3%	21.8%	5.44 [4.32, 6.85]	54.3%	1.28 [0.97, 1.67]
Domestic abuse in the home	33.8%	11.5%	3.92 [3.08, 5.00]	24%	1.61 [1.21, 2.16]
Substance abuse in the home	57.7%	23.8%	4.37 [3.48, 5.50]	46.7%	1.56 [1.19, 2.04]
Mental illness in the home	32.8%	14.8%	2.81 [2.21, 3.58]	25.9%	1.40 [1.04, 1.87]
Incarcerated household member	32.5%	4.1%	11.26 [8.68, 14.60]	22.6%	1.65 [1.23, 2.22]

Note. Levenson et al. refers to the Levenson et al. (2016) publication and Male CDC refers to the CDC (2013) publication. Odds ratios are calculated to compare rates of ACEs in the SRSTC population to the Male CDC sample (A) and Levenson et al. sample (B). ACE = adverse childhood experiences; CDC = Centers for Disease Control and Prevention.

Table 1 also shows the proportion of patients endorsing each ACE item compared with ACE item endorsement rates in both a mixed (outpatient and civil commitment) male sex offender sample (Levenson et al., 2016) and a general male population from the CDC (2013). The current SVP sample reported higher rates of ACEs compared with both a general population sample and comparison sex offender sample (CDC, 2013; Levenson et al., 2016). Odds ratios used to compare the prevalence of ACEs among groups revealed that, compared with a general population sample (CDC, 2013), the odds of having experienced verbal abuse during childhood were 25 times higher for the current SVP sample. In addition, the odds of experiencing sexual abuse and emotional neglect were seven times higher and the odds of having experienced physical abuse were three times higher for a civil commitment sample. When comparing to a lower risk sex offender sample (Levenson et al., 2016), the frequencies of ACEs were more similar, yet still higher among the current sample. For example, the odds of experiencing physical abuse, sexual abuse, and physical neglect were all two times higher for the current SVP sample.

Phi coefficients of association (ϕ) between individual ACE items are presented in Table 2. ACEs were highly associated with one another, with significant coefficients in 42 of the 45 coefficients ranging from ϕ = .13 (parental divorce/separation and emotional neglect) to ϕ = .62 (physical and verbal abuse). Other notable coefficients demonstrating a medium effect size included physical abuse and physical neglect (ϕ = .41), physical abuse and domestic violence in the home (ϕ = .38), verbal abuse and domestic violence in the home (ϕ = .38), and verbal abuse and emotional neglect (ϕ = .36). The distribution of ACE scores is shown in Figure 1. Only 5% of the sample said they had experienced no ACEs and two thirds (66%) experienced four or more ACEs.

Table 2.

Phi Coefficients (ϕ) of Association Between ACE Items.

ACE Items	1	2	3	4	5	6	7	8	9
1. Verbal abuse
2. Physical abuse	.62***
3. Child sexual abuse	.33***	.32***
4. Emotional neglect	.36***	.30***	.25***
5. Physical neglect	.32***	.41***	.29***	.36***
6. Parental divorce/separation	.20***	.18***	.07	.13*	.21***
7. Domestic violence	.38***	.39***	.29***	.31***	.35***	.30***
8. Substance abuse in the home	.35***	.29***	.17***	.20***	.32***	.23***	.35***
9. Mental illness in the home	.32***	.25***	.23***	.29***	.30***	.25***	.32***	.30***
10. Incarcerated household member	.15***	.13*	.06	.01	.20***	.25***	.21***	.29***	.14*

Note. ACE = adverse childhood experiences.

p < .05. ***p ≤ .001.

Figure 1.

Distribution of ACE scores in a sample of civilly committed sexual offenders.

ACEs and Risk for Sexual Recidivism

Past research found a significant relationship between ACE scores and a simulated Static-99R risk score (Levenson et al., 2016). We examined directly whether the ACE total score was associated with risk for sexual recidivism as measured by the Static-99R. The results are presented in Table 3. After controlling for race and full scale IQ, the association between ACE and Static-99R total scores was not significant (b* = .07, p = .20, b = .04, 95% CI [−.022, −.103]). In exploring whether the two underlying dimensions of the ACE score were uniquely related to recidivism risk, neither child harm (b* = .05, p = .51, b = .04, 95% CI [−.083, − .167]) nor household dysfunction (b* = .07, p = .57, b = .04, 95% CI [−.097, −.176]) were significant predictors of sexual recidivism risk.

Table 3.

Association between ACE scores and Static-99R.

	Static-99R total score
Variables	b [95%CI]	SE	b*	p	R ²
Model 1
Race	−.22 [4.26, 6.31]	.20	−.07	.27	.06
IQ	.01 [−0.01, 0.01]	.01	.02	.68
ACE total	.04 [−0.02, 0.10]	.03	.07	.20	.09
Model 2
Race	−.22 [−0.63, 0.18]	.21	−.07	.28	.06
IQ	.01 [−0.01, 0.01]	.01	.02	.68
ACE child harm	.04 [−0.08, 0.17]	.07	.04	.51	.09
ACE household dysfunction	.04 [−0.10, 0.18]	.07	.04	.57

Note. IQ measured using the WAIS-IV (Wechsler, 2008). b* = standardized beta; b = unstandardized beta; CI = confidence interval; ACE = adverse childhood experiences.

ACEs and Psychopathology

Table 4 shows results of binary logistic regression analyses of ACE total scores with DSM-5 diagnoses, controlling for age and race. ACE total score was a significant predictor of an anxiety disorder diagnosis, with each additional ACE item reported the odds of experiencing an anxiety disorder increased by 19%. Similarly, ACE total score was a significant predictor of a depressive disorder diagnosis, with each additional ACE reported the odds of receiving a depressive disorder diagnosis increased by 10%. For substance use disorders, with each additional ACE item endorsed by a patient the odds of having an Alcohol Use Disorder diagnosis increased by 10%. ACE scores were not significantly associated with a diagnosis of any other substance use disorder.

Table 4.

Associations Between ACE Total Scores and Psychopathology.

Models	b (SE)	Odds ratio	95% CI
Anxiety diagnosis^a
Age	−0.05*** (.02)	0.95	[0.93, 0.98]
Race	0.19 (.33)	1.21	[0.64, 2.30]
ACE total	0.17** (.06)	1.19	[1.10, 1.32]
Depression diagnosis^b
Age	0.00 (.01)	1.00	[0.98, 1.02]
Race	0.49 (.29)	1.64	[0.93, 2.89]
ACE total	0.09* (.05)	1.10	[1.00, 1.21]
Alcohol use disorder^c
Age	0.02* (.01)	1.03	[1.00, 1.05]
Race	−0.22 (.25)	0.80	[0.49, 1.30]
ACE total	0.10* (.04)	1.10	[1.01, 1.20]
Other substance use diagnosis^d
Age	0.01 (.01)	1.01	[0.99, 1.04]
Race	−1.10*** (.26)	0.33	[0.22, 0.55]
ACE total	0.03 (.05)	1.03	[0.94, 1.12]
Pedophilia^e
Age	0.02 (.01)	1.02	[0.99, 1.04]
Race	1.60*** (.27)	4.94	[2.90, 8.42]
ACE total	0.06 (.05)	1.07	[0.98, 1.16]
Other paraphilia^f
Age	0.04** (.01)	1.04	[1.01, 1.06]
Race	0.34 (.26)	1.40	[0.85, 2.31]
ACE total	0.05 (.04)	1.05	[0.96, 1.14]
Antisocial personality disorder^g
Age	−0.01 (.01)	1.00	[0.98, 1.02]
Race	−1.06*** (.26)	0.35	[0.21, 0.58]
ACE total	0.10* (.04)	1.11	[1.02, 1.21]
Paraphilia and personality disorder^h
Age	0.03** (.01)	1.03	[1.01, 1.05]
Race	0.09 (.25)	1.10	[0.67, 1.79]
ACE total	0.14** (.04)	1.14	[1.05, 1.25]

Note. b = unstandardized beta, CI = confidence interval; ACE = adverse childhood experiences.

R² = .08 (Cox & Snell), .13 (Nagelkerke). Model χ²(3) = 27.99, p < .001. ^bR² = .02 (Cox & Snell), .04 (Nagelkerke). Model χ²(3) = 7.86, p = .05. ^cR² = .03 (Cox & Snell), .04 (Nagelkerke). Model χ²(3) = 8.90, p < .05. ^dR² = .06 (Cox & Snell), .09 (Nagelkerke). Model χ² (3) = 20.30, p < .001. ^eR² = .12 (Cox & Snell), .16 (Nagelkerke). Model χ²(3) = 41.06, p < .001; ^fR² = .03 (Cox & Snell), .05 (Nagelkerke). Model χ²(3) = 11.03, p = .01. ^gR² = .07 (Cox & Snell), .09 (Nagelkerke). Model χ²(3) = 21.86, p < .001; ^hR² = .04 (Cox & Snell), .06 (Nagelkerke). Model χ²(3) = 13.44, p < .01.

p < .05. **p < .01. ***p < .001.

Total ACE scores were unrelated to a diagnosis of Pedophilic Disorder or any other paraphilic disorder. Total ACE scores were significantly related to a diagnosis of Antisocial Personality Disorder, with the odds of having ASPD increasing by 11% for each additional ACE item endorsed. Total ACE scores were also significantly related to comorbid paraphilic and personality disorder diagnoses; the odds of having a personality disorder and a paraphilic diagnosis increased by 14% for each additional ACE reported.

Results from exploring the relationship between the underlying dimensions of the ACE scale and psychopathology are presented in Table 5. The child harm domain was not a significant predictor of any diagnostic category. Household dysfunction was a predictor of Alcohol Use Disorder diagnosis, as well as the diagnostic duo of a paraphilic and personality disorder diagnosis. With each additional household dysfunction experience, the odds of having an Alcohol Use Disorder increased by 23%. Similarly, the odds of having both a paraphilic disorder and personality disorder diagnosis increased by 22% with each additional household dysfunction experienced before the age of 18.

Table 5.

Associations Between ACE Domain Scores and Psychopathology.

Models	b (SE)	Odds ratio	95% CI
Anxiety diagnosis^a
Age	−0.05*** (.02)	0.95	[0.93, 0.98]
Race	0.17 (.34)	1.19	[0.61, 2.31]
ACE child harm	0.19^† (.11)	1.21	[0.98, 1.49]
ACE household	0.16 (.11)	1.17	[0.94, 1.45]
Depression diagnosis^b
Age	0.00 (.01)	1.00	[0.98, 1.03]
Race	0.53 (.30)	1.70	[0.95, .3.06]
ACE child harm	0.06 (.09)	1.06	[0.89, 1.27]
ACE household	0.14 (.10)	1.15	[0.94, 1.39]
Alcohol use disorder^c
Age	0.03* (.01)	1.03	[1.00, 1.05]
Race	−0.13 (.26)	0.88	[0.53. 1.46]
ACE child harm	0.01 (.08)	1.01	[0.86, 1.18]
ACE household	0.20* (.09)	1.23	[1.02, 1.47]
Other substance use diagnosis^d
Age	0.01 (.01)	1.01	[0.99, 1.04]
Race	−1.00*** (.27)	0.37	[0.22, 0.62]
ACE child harm	−0.08 (.09)	0.92	[0.78, 1.10]
ACE household	0.15 (.10)	1.16	[0.95, 1.41]
Pedophilia^e
Age	0.01 (.01)	1.01	[0.99, 1.04]
Race	1.51*** (.28)	4.53	[2.62, 7.83]
ACE child harm	0.16 ^† (.09)	1.17	[0.99, 1.40]
ACE household	−0.04 (.10)	0.96	[0.80, 1.16]
Other paraphilia^f
Age	0.04** (.01)	1.04	[1.01, 1.06]
Race	0.38 (.27)	1.46	[0.87, 2.48]
ACE child harm	0.00 (.08)	1.00	[0.85, 1.18]
ACE household	0.10 (.09)	1.10	[0.92, 1.32]
Antisocial personality disorder^g
Age	−0.01 (.01)	1.00	[0.98, 1.02]
Race	−1.00*** (.27)	0.37	[0.22, 0.63]
ACE child harm	0.04 (.08)	1.04	[0.89, 1.23]
ACE household	0.17^† (.09)	1.18	[0.99, 1.42]
Paraphilia and personality disorder^h
Age	0.03** (.01)	1.03	[1.01, 1.06]
Race	0.15 (.26)	1.16	[0.70, 1.94]
ACE child harm	0.08 (.08)	1.09	[0.92, 1.28]
ACE household	0.20* (.09)	1.22	[1.02, 1.46]

Note. b = unstandardized beta, CI = confidence interval; ACE = adverse childhood experiences.

R² = .09 (Cox & Snell), .13 (Nagelkerke). Model χ²(4) = 28.02, p < .001. ^bR² = .03 (Cox & Snell), .04 (Nagelkerke). Model χ²(4) = 8.09, p = .09. ^cR² = .03 (Cox & Snell), .04 (Nagelkerke). Model χ²(4) = 10.58, p < .05. ^dR² = .07 (Cox & Snell), .09 (Nagelkerke). Model χ²(4) = 22.20, p < .001. ^eR² = .13 (Cox & Snell), .17 (Nagelkerke). Model χ²(4) = 42.67, p < .001. ^fR² = .04 (Cox & Snell), .05 (Nagelkerke). Model χ²(4) = 11.41, p < .05. ^gR² = .07 (Cox & Snell), .09 (Nagelkerke). Model χ²(4) = 22.52, p < .001. ^hR² = .04 (Cox & Snell), .06 (Nagelkerke). Model χ²(4) = 14.02, p < .01.

†

p < .07. *p < .05. **p < .01. ***p < .001.

Discussion

The prevalence of ACEs in this sample of sex offenders committed under an SVP law was significantly higher than those identified in a mixed sample of individuals who had committed sexual offenses (Levenson et al., 2016), as well as for males in the general population (Felitti et al., 1998). The current sample exhibited increased odds of all ACEs, especially those related to child harm, such as physical abuse, sexual abuse, and physical neglect. A minority (5%) of the current sample reported experiencing zero ACEs, while over two thirds reported experiencing four or more ACEs. Occurrence of four or more ACEs is considered a threshold by which extreme early trauma is measured, and findings in the current sample are consistent with research showing associations between higher ACE scores and a diverse range of poor mental health and criminal outcomes (Anda et al., 2006; Mersky et al., 2012, 2013).

Similar to past research, ACEs in this population were strongly associated with one another, with the largest effect size occurring between verbal and physical abuse. This is consistent with previous research suggesting traumatic childhood events rarely occur in isolation, and individuals exposed to single forms are often at risk for exposure to other adverse experiences (Baglivio & Epps, 2016; Dong et al., 2004). One especially relevant finding is that over half (56.5%) of this population reported experiencing childhood sexual abuse. This was substantially higher than the 16% rate reported for general population samples (Dong et al., 2003) and higher than previously found in people who have committed sexual crimes (Levenson et al., 2016; Reavis et al., 2013). For example, the rate was 38% for a combined outpatient and civil commitment sample (Levenson et al., 2016), while a rate of 39% was found in another outpatient sample of individuals who had committed sexual offenses (Reavis et al., 2013). Earlier work in other offending samples found rates of sexual abuse that ranged from approximately 24% to 31% (Hanson & Slater, 1988). Jespersen and colleagues (2009) compared rates of sexual abuse in both males and females who have committed sexual offenses across 17 different studies and found rates ranging from 4% to 82%. The operationalization of childhood sexual abuse differs widely across studies and assessment tools, perhaps explaining variations in rates across samples.

Unlike previous research, this study did not find a significant association between ACE scores and measures of risk for sexual recidivism (p values ranged from .20 to .57). The lack of replication of prior findings could be due to the use of different methodology as the prior study used simulated risk scores devised with self-reported information (Levenson et al., 2016). Sample differences between these studies (i.e., mixed outpatient and civil commitment versus exclusively patients committed under SVP laws) may also have contributed to the divergent findings. More specifically, the current sample was likely at a higher risk for recidivating, with the average Static-99R score at the above average risk level (M = 5.54). In contrast, the sample analyzed by Levenson and colleagues (2016) were a lower risk group of individuals, simulated Static99R score M = 3.30, SD = 2.17; t(316) = 25.39, p < .001. To help clarify the association between ACEs and recidivism, future research could employ a longitudinal design that includes recidivism outcomes for individuals who have committed sexual offenses. In addition, given the increasing reliance on criminogenic needs instruments, it may be useful to identify the impact of ACEs on dynamic risk factors, especially in a high-risk population.

Our hypotheses that ACEs would be related to both internalizing and externalizing psychopathology were partially supported. Total ACE scores were associated with increased odds of having an anxiety disorder diagnosis, a depressive disorder diagnosis, an Alcohol Use Disorder diagnosis, a diagnosis of Antisocial Personality Disorder, and comorbid personality and paraphilia diagnoses. In contrast to prior research, ACE total score was unrelated to a diagnosis of Pedophilic Disorder or other paraphilic diagnoses (e.g., Exhibitionistic, Sexual Sadism, or Other Specified Paraphilic Disorders). A more nuanced picture emerged by examining the two components of the ACE scale separately. Household dysfunction was a significant predictor of Alcohol Use Disorder and the dual diagnosis of a personality and paraphilic disorders; the child harm domain did not predict any adult psychopathology. Overall, our findings are generally consistent with prior research demonstrating ACEs increases risk for mental health difficulties in adulthood (e.g., Anda et al., 2006; Felitti et al., 1998). We extend prior work by showing that ACEs related to household dysfunction may increase risk for alcohol use and comorbid psychopathology in this high-risk sample. A stronger link between household dysfunction and adult psychopathology may be explained by the ways a pathogenic relational environment deprives children of experiences that promote adaptive functioning and coping skills across the lifespan. Families fraught with addiction, mental illness, criminality, family violence, or parental absence can model maladaptive behavior and produce in children anxiety, anger, and depression, along with a sense of helplessness. While individuals vary in their responses to trauma, and many people demonstrate resilience following adverse circumstances, traumagenic environments may be most disabling to those with negative personality traits and limited intellectual or social resources (Patterson et al., 1990).

Implications for Trauma-Informed Care (TIC)

We propose that these data have implications for TIC models. TIC is different from trauma-specific interventions, which are designed to reduce PTSD symptoms and improve coping. Trauma-specific therapies might be relevant and helpful for many clients. Trauma-informed models, on the other hand, are ideally infused throughout interventional settings and utilize practices that are compassionate, respectful, and encourage self-determination. In this way, clinicians and other staff view and respond to maladaptive behavior in the context of a person’s collective traumatic experiences. Above all, TIC ensures that the types of disempowering and traumagenic dynamics that characterize abusive families are not replicated by professionals in the helping relationship (Levenson et al., 2017). This can be particularly challenging in a correctional or secure treatment setting, where therapeutic responses must be balanced with ensuring the safety of staff and residents.

Given the prevalence of ACEs in the current sample, it is important to understand the pathways through which childhood ACEs contribute to sexual offending later in life and how TIC models can be applied within this population (Cheng et al., 2019; Grady et al., 2016; Grady & Shields, 2018). For example, ACEs can represent relational trauma characterized by attachment disruption, parental betrayal, and/or intrapersonal invalidation. When a child’s caretakers are dangerous or unavailable, opportunities for modeling of healthy intimacy skills may be severely limited or absent. Accumulated childhood trauma may alter the neurobiology of the brain, as chronic hyperarousal impedes development of emotional and behavioral self-regulation (Cheng et al., 2019; Holley et al., 2017). Children growing up in abusive or chaotic families often adopt maladaptive relational strategies that manifest as aggression, hostility, sexualized coping, intimacy deficits, or emotional congruence with children in adulthood (Beech & Mitchell, 2016).

Our results suggest evidence-based programs treating individuals who have committed sexual crimes may benefit from incorporating TIC models into treatment planning. TIC models utilize knowledge about the neurobiological and psychosocial impacts of trauma to conceptualize the link between past experiences and presenting problems (Levenson et al., 2017). Through this lens of early adversity, clinicians deliver cognitive-behavioral treatment within a context that considers how early experiences shape current thinking, feeling, and behavior. Viewing sexually abusive behavior in this way, we can re-frame treatment targets as trauma-related attachment styles, maladaptive schemas, misguided coping strategies, and dysregulation, all of which contribute to dynamic risk (Levenson et al., 2017). By recognizing the role of trauma in developing and maintaining problematic sexual behaviors, treatment programs can better address the treatment needs of those who sexually offend.

Limitations

Limitations of the current study exist. First, ACE scores were based on retrospective self-reports. This methodology is common in research studies, but may be prone to bias due to influences such as forgetting, resistance to disclosure, or the effects of a respondent’s mood on reporting negative or positive experiences (e.g., Ackermann & DeRubeis, 1991; Colman et al., 2016; Edwards et al., 2001). However, recall bias and inconsistent reporting only minimally influence the variance of retrospective self-report of maltreatment (Fergusson et al., 2011) and false positives are rare for retrospective reports of ACEs (Hardt & Rutter, 2004). In fact, prior longitudinal follow-ups of adults who had documented childhood abuse demonstrated that retrospective reports of childhood abuse are likely to underestimate the occurrence of abuse (DellaFemina et al., 1990; Williams, 1995). Moreover, even when discrepancies in self-report exist, both prospective and retrospective reports of maltreatment are predictive of poorer life outcomes (Reuben et al., 2016). Nevertheless, other research comparing retrospective self-report at age 18 with prospective measures of maltreatment assessed from ages 5 to 12 in the Environmental Risk Longitudinal Twin Study found agreement between the methods was only slight or fair (Newbury et al., 2018). More specifically, individuals who prospectively reported maltreatment during childhood underreported these experiences at the age of 18. Most individuals who retrospectively reported childhood maltreatment at age 18 did not have a matching prospective report of maltreatment for comparison. This suggests both measurement methods may produce valid measures of childhood maltreatment, but that retrospective reports may be biased toward underreporting of past experiences (Newbury et al., 2018). If this were the case in the present study, then the importance of the reported ACEs in this sample may be understated.

An additional limitation to consider in relying on self-report for this sample is the potential for socially desirable responding or even deception. Individuals who commit sexual offenses are thought to be more vulnerable to impression management due to the social stigma attached to their crimes (Gudjonsson & Sigurdsson, 2000; Tan & Grace, 2008; Tierney & McCabe, 2001). Other research has suggested that individuals who sexually offend may embellish childhood trauma to gain sympathy or rationalize their sexual offenses (Hindman, 1988; Hindman & Peters, 2001). Thus, we acknowledge that our results are limited by the inherent inability to confirm self-report. At the same time, our findings are consistent with past research providing credibility to our conclusions.

A second limitation is related to the ACE measure. The ACE items were constructed as dichotomous variables and therefore can only capture whether a childhood adversity occurred at least one time in early life. It cannot capture the frequency, duration, or severity of these early traumas. Furthermore, cultural differences or adverse experiences that occurred both inside and outside the home may not be adequately addressed in the ACE measure (Cronholm et al., 2015; Finkelhor et al., 2013; Mersky et al., 2017). Recent research has proposed and tested ACE measures to include additional adversities such as death or illness in a family, poverty, homelessness, peer victimization, peer rejection, and exposure to community violence (Finkelhor et al., 2013). A modification of the ACE measure to add additional adversities revealed peer victimization, peer rejection, and exposure to community violence added significantly in the prediction of both physical and mental health difficulties in adulthood (Finkelhor et al., 2015). On the other hand, the ACE measure in its original conception has been widely used in research studies and provides a foundation by which to compare different populations.

A third limitation is the reliance on DSM-5 diagnoses made by one forensic evaluator or treating psychiatrist. That is, given the archival nature of this study, we were unable to assess reliability for DSM-5 diagnoses used as outcomes variables. Research on diagnostic agreement in SVP civil commitment proceedings is mixed and varies depending on the type of reliability statistic used. Packard and Levenson (2006) examined agreement of diagnostic decisions in a sample of 450 SVP evaluations. Proportions of agreement between raters on commonly employed diagnoses in SVP civil commitment proceedings ranged from .68 to .97. Our results should be considered in the context of debates about diagnostic reliability.

Finally, the current research draws no conclusions about the pathways by which the reported ACEs impacted the development of psychopathology or offense-related behavior. However, it is important to move beyond simply examining links or correlations between ACEs and pathological outcomes. In a recent commentary about screening for ACEs, Finkelhor (2018) pointed out that “sexual abuse is not an infection that causes a disease” (p. 176). Empirical evidence points toward mediating processes, such that ACEs operate to influence negative outcomes thereby increasing risk for offending or poor mental health outcomes. One potential pathway from early victimization to aggressive behavior and criminality may involve increased stress sensitization among individuals experiencing childhood adversity (Roberts et al., 2011). Other pathways from ACEs to poor outcomes in adulthood may include poor parent–child attachment, modeling of maladaptive behaviors, limited opportunities for social learning of effective interpersonal skills, disruptions in brain development (e.g., amygdala, hippocampus, and prefrontal cortex) that impede self-regulation, elevated cortisol levels resulting in hyperarousal and aggression, and/or genetic influences (see Beckley et al., 2018, for review). These are all relevant avenues to pursue in future research.

Conclusion

Given the strong connection to an array of negative outcomes, ACEs are now considered a public health crisis in the United States, as well as across the globe. This has prompted recommendations for universal screening of ACEs and the practice of TIC in the pediatric community (American Academy of Pediatrics, 2012a, 2012b; for a review, see Dube, 2018). Implementation of screening is a critical step for prevention efforts to reduce the effects of adverse experiences in childhood and make efforts to intervene in the intergenerational cycle. While this level of prevention does not impact those who have already committed sexual offenses, we should recognize the prevalence of ACEs in these clients. Treatment models incorporating TIC can target the pathways underlying sexual offending and may be most relevant for reducing reoffending and supporting successful rehabilitation.

Footnotes

Authors’ Note

The authors take responsibility for the integrity of the data, the accuracy of the data analyses, and have made every effort to avoid inflating statistically significant results. The views expressed are those of the authors and not necessarily those of the Wisconsin Department of Health Services—Division of Care and Treatment Services.

Krystine Jackson is now affiliated with Sand Ridge Secure Treatment Center, Madison, WI, USA.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Rachel E. Kahn

Krystine Jackson

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