Victimization Experiences and Executive Dysfunction as Discriminating Risk Indicators for Youth Offender Typologies

Abstract

Research is becoming increasingly nuanced in its examination of offenders, and thus typological distinctions according to generalist and/or specialization offense profiles may be notable for targeted intervention efforts within and between classifications of offenders. There is a significant body of evidence identifying early-life victimization and executive function deficits as critical developmental antecedents to sexual and non-sexual offending alike, but they have not been exhaustively evaluated as a discernable experience among criminally versatile offenders (youth who commit both sexual and non-sexual crimes). This study aims to address gaps by examining associations between early-life victimization, other traumatic experiences in the home, and executive functioning deficits and then test how disparate offending groups differentially experience these early risks. Using a sample of juvenile-justice-involved youth (N = 200), who committed sexual only offenses (n = 41), non-sexual only offenses (n = 124), and criminally versatile offenders (n = 27), multivariate analysis of variance tests and bivariate correlations were conducted. Results revealed that there were statistically significant correlations between measures of executive functioning and specific incidents of victimization, particularly sexual, physical, and emotional. There were also significant group differences in measures of sexual abuse, physical and emotional abuse, and executive functioning with criminally versatile offenders showing higher rates of physical and emotional abuse and sexual only offenders showing higher rates of sexual abuse and some executive functioning deficits. Practice and research implications are discussed.

Keywords

juvenile sex offenders offender typologies executive functioning

Many individuals below the age of 25 have impairments in abilities to plan, organize, regulate behaviors, or understand consequences of decision making. Such deficits in executive functioning can contribute to a host of behavioral problems among youth including propensities to commit criminal or delinquent acts. In fact, there may be greater than average deficits in executive functioning capabilities among youth involved in the criminal justice system (Kelly, Richardson, Hunter, & Knapp, 2002; Morais, Joyal, Alexander, Fix, & Burkhart, 2016; White et al., 1994; Zou et al., 2013). Developmental antecedents commonly linked to delinquency, such as trauma, may contribute to elevated executive functioning problems (Fago, 2003; Veneziano, Veneziano, LeGrand, & Richards, 2004; Zou et al., 2013); early victimization and trauma has been indicated as a significant risk in the formation of executive functioning among the general population (Kirke-Smith, Henry, & Messer, 2014; Nikulina & Spatz Widom, 2013; Vasilevski & Tucker, 2016), and even among specialized types of youthful offenders including those who commit sexual crimes (Morais et al., 2016; Yoder, Grady, & Precht, 2019a). Nevertheless, there is a dearth of evidence exploring these differential risk indicators among disparate offending groups, including youth sexual, non-sexual, and criminally versatile offenders (youth who commit both sexual and non-sexual crimes).

Literature Review

Typological Distinctions

Research is becoming increasingly nuanced in its examination of offenders, and thus typological distinctions may be notable for targeted intervention efforts within and between classifications of offenders (Hunter, Figueredo, Malamuth, & Becker, 2003; Rajilic & Gretton, 2010). Often, risk-based typologies are based on victim profile (Hunter et al., 2003; Morais et al., 2016) or perpetrator personality characteristics (Craig, Browne, Beech, & Stringer, 2004; Freeman, Dexter-Mazza, & Hoffmanl, 2005; Rajilic & Gretton, 2010; Worling, 2001). However, research has also classified offenders according to generalist and/or specialization offense profiles. Some juvenile offenders do not specialize in one offense pattern and may be criminally versatile in that they commit sexual crimes concurrently or successively with other delinquent offenses (Lussier, 2005). Consequently, a dialogue has emerged regarding the uniqueness of sexual offending, as many scholars posit that sexual offending behaviors may not have exclusive risk factors, per se, but that certain risk indicators are heightened among certain offending typologies (Caldwell, 2002; Lussier, Leclerc, Cale, & Proulx, 2007; Skilling, Doiron, & Seto, 2011; Smallbone, 2006; Wanklyn, Ward, Cormier, Day, & Newman, 2012). For example, compared with research on single-dimension offenders, criminally versatile youth offenders show greater complexity in risk factors and offending pathways (Rajilic & Gretton, 2010). To continue this exploration, comparative research distinguishing risks between offending groups is necessary. Much of the research has identified early-life victimization and executive function deficits as critical developmental antecedents to sexual and non-sexual offending alike, but they have not been exhaustively evaluated as discernable experiences among criminally versatile offenders.

Early-Life Victimization

Victimization experiences among juvenile justice populations can include sexual abuse, physical abuse, emotional abuse, exposure to violence, abandonment, neglect, or bullying (Costello, Erkanli, Fairbank, & Angold, 2002; Finkelhor, Ormrod, Turner, & Hamby, 2005; Ford, Chapman, Mack, & Pearson, 2006; Tsang, 2018; Yoder, Hodge, & Ruch, 2019b). It is conservatively estimated that between 40% and 60% of juvenile offenders have been victimized at least once (Currie & Tekin, 2006; Ford, Chapman, Hawke, & Albert, 2007; Stahl, 2006). Compared with general population youth, among youth offenders, there are higher rates of childhood trauma, particularly physical abuse (Zou et al., 2013). Within groups of youth offenders, those who commit sexual crimes have histories marked with more physical and sexual victimization relative to youth who commit non-sexual crimes (Jespersen, Lalumière, & Seto, 2009; Levenson et al., 2017; Seto & Lalumière, 2010; Yoder, Dillard, & Leibowitz, 2017). Furthermore, in some studies, juveniles who commit sexual crimes have a greater prevalence of physical victimization, general exposure to sexual violence, emotional abuse, and emotional neglect (e.g., lack of emotional support) (Seto & Lalumière, 2010). Such research has hypothesized that the intra-familial experiences of juvenile sex offenders may differ from those of other youth offender groups, particularly related to parental/domestic violence (Ford & Linney, 1995), sexual violence, overall violence (Seto & Lalumière, 2010), emotional abuse, and forced sex (Yoder et al., 2019b). Such elevated rates of victimization among youth sexual offenders may offer predictive insight into etiological discrepancies between only youth who commit sexual offenses and criminally versatile youth.

There is still limited knowledge pertaining to victimization histories among criminally versatile youth. Research comparing three groups of youth offenders—criminally versatile (sexual and non-sexual offenders), violent non-sexual offenders, and sexual only offenders—found that criminally versatile and violent non-sexual offenders report greater childhood victimization within family systems relative to sexual only offenders (Wanklyn et al., 2012). However, comparative analyses integrating more than two groups of offenders are limited, and most studies distinguish between criminally versatile youth and other groups using two-group analyses. For example, in a two-group comparison of criminally versatile youth (sexual with delinquent histories) and only sexual offenders, the criminally versatile group had higher rates of childhood maltreatment and greater parental substance use and criminality (Way & Urbaniak, 2008). Differential developmental risk experiences may exist among criminally versatile offenders, compared with both non-sexual and sexual only adolescent offenders (Rajilic & Gretton, 2010). Yet the summation of literature focusing on early-life victimization can be both contradictory and inconclusive, besides the well-established correlation between prior sexual abuse and sexual perpetration (Aebi et al., 2015; Seto & Lalumière, 2010). More research using three-group analyses is needed to disentangle how specific early-life victimization experiences and other salient developmental risks, including executive functioning, may or may not contribute differentially to typologies.

Executive Function Deficits

Executive functioning is the ability to demonstrate higher order cognitive processing, planning or anticipating future events, reasoning, demonstrating flexibility, or completing tasks (Gioia, Isquith, Retzlaff, & Espy, 2002). Executive functioning formation occurs in the prefrontal cortex (Aupperle, Melrose, Stein, & Paulus, 2012). Manifestations of executive dysfunctional behavior non-exhaustively include impulsivity (Craig et al., 2004; Kelly et al., 2002; Stinson, Becker, & Sales, 2008; White et al., 1994), emotion dysregulation (Hoaken, Allaby, & Earle, 2007), and incorrect interpretation of social cues (Hoaken et al., 2007; Kelly et al., 2002; White et al., 1994).

There is growing evidence to support a relationship between executive function deficits and youth criminality (Burton, Demuynck, & Yoder, 2016; Hoaken et al., 2007; Kelly et al., 2002; Morais et al., 2016; Zou et al., 2013). Relative to general population youth, juvenile offenders show higher rates of impairments in executive functioning including lower intellectual capacity exhibited by lower IQ scores and inhibited abilities related to executive functioning (Zou et al., 2013). In attempting to demarcate subtypes of juvenile offenders, research reveals clinical deficits in executive functioning features of meta-cognition and behavioral regulation among juveniles who commit sexual crimes (Burton et al., 2016). Further between-group comparative analyses suggest similar impaired levels of executive functioning among youth who commit sexual and non-sexual crimes, although the presentation of such impairments may differ depending on offender subtype (Morais et al., 2016; Veneziano et al., 2004). For example, adolescents who commit sexual crimes with child victims had greater deficits on higher order executive functioning relative to sexual offenders with peer victims and youth who commit non-sexual crimes (Morais et al., 2016).

Therefore, severe executive dysfunction may be linked to more severe offending patterns. Serious offenders have been reported to exhibit even higher rates of impairment on some executive functioning domains compared with less serious offenders (i.e., non-violent offenders), including attention, working memory, planning, and impulse control (Frías-Armenta, Valdez-Ramírez, Nava-Cruz, Figueredo, & Corral-Verdugo, 2010; White et al., 1994; Zou et al., 2013). Severe offending patterns may be reflected in typological distinctions, such that youth who commit certain types of crimes may be deemed more or less severe (Yoder et al., 2019b). For instance, research has found that versatile offenders (those committing sexual and non-sexual offenses) and violent non-sexual offenders had greater childhood conduct problems relative to sex-only (only committing a sexual crime) offenders (Butler & Seto, 2002), suggesting that perhaps typologies represent offense severity that can be partially determined via developmental risks. Nevertheless, there has been no research on distinguishable characteristics in executive functioning between youth with specialization typologies including sexual, non-sexual, or versatile offending, even when the level of violence underlying the criminal behavior is not considered.

Relationship Between Trauma and Executive Functioning

There are strong theoretical and empirical associations between victimization and neurological impairments (Mothes et al., 2015; Perry, Pollard, Blakley, Baker, & Vigilante, 1995; Schore, 2001). Children with histories of victimization exhibit significant impairments on domains of executive functioning, such as attention and working memory, compared with age- and gender-matched peers with no prior trauma (Bücker et al., 2012; Vasilevski & Tucker, 2016). Among individuals in the general population, early victimization has been prospectively linked to executive functioning difficulties (Nikulina & Spatz Widom, 2013). Research using samples of children found that those exposed to child maltreatment, compared with those that were not, had worse executive function outcomes (Kirke-Smith et al., 2014). Exposure to complex trauma has also been correlated to deficiencies in cognition and behavioral control including poor impulse control, task completion, and planning ability (Cook et al., 2017). Nevertheless, there is still much to be learned about the relationship between specific victimization experiences and executive functioning among juvenile-justice-involved youth.

Maltreated youth with executive functioning impairments may have heightened vulnerability to engage in risky behaviors (Spann et al., 2012); the relation between trauma and executive function deficits may be particularly significant for juvenile offenders who experience victimization at rates twice as high as general population youth (Coleman, 2005; Coleman & Stewart, 2010). Some research has begun to explore sexual abuse experiences as a distinguishable antecedent to executive functioning among youth who commit sexual and non-sexual crimes (Morais et al., 2016). Sexual victimization, in particular, may have stronger effects on meta-cognitive deficits compared with other types of victimization and trauma among juvenile justice youth (Yoder et al., 2019a). Given that victimization is an indicated precursor to executive functioning among the general population (Augusti & Melinder, 2013; Nikulina & Spatz Widom, 2013), research should continue to explore the relation between early-life victimization and executive functioning deficits among samples of youth in the criminal justice system and how such experiences could distinguish offender specialization typologies.

This Study

Despite emerging research on offender typologies, there is limited research differentiating developmental antecedents between types of youth offenders, specifically criminally versatile youth. Prior research has thoroughly explored the high rates of both early-life victimization experiences (Coleman, 2005; Coleman & Stewart, 2010; Currie & Tekin, 2006; Ford et al., 2007; Stahl, 2006; Yoder et al., 2019b; Zou et al., 2013) and executive functioning deficits (Kelly et al., 2002; Morais et al., 2016; White et al., 1994; Zou et al., 2013) in the manifestation of sexual and non-sexual offending behaviors among youth. Furthermore, although the relationship between victimization and executive functioning deficits is well established among general population youth, there is a need for further evidence exploring the differential forms of victimization associated with types of executive dysfunction among juvenile justice populations. Such developmental risks need to be distinguished among offending groups, including youth sexual, non-sexual, and criminally versatile offenders. This study aims to address these gaps in the literature by examining associations between early-life victimization, other traumatic experiences in the home, and executive functioning deficits. This study also aims to test how disparate offending groups differentially experience these early risks. Therefore, the study proposes two different research questions: (a) What are the associations between different forms of victimization and different forms of executive dysfunction among juvenile justice youth? (b) Do groups of youth offenders, including criminally versatile offenders, have differential experiences of early victimization and executive function?

Method

Data Collection

This study received university institutional review board (IRB) approval and support from the state Sex Offender Management Board and the state Department of Youth Services. Data were collected with adjudicated youth (N = 200) involved in juvenile justice facilities in a western state. Youth reported committing crimes that were sexual only (n = 41), non-sexual only (n = 124), or both (n = 27). In this cross-sectional study, youth assented or consented to participate and were asked to complete a battery of validated and researcher-developed instruments. In general, the instrument measured concepts of early-life victimization, home environments, and executive functioning capacities. The youth completed paper and pencil surveys in classroom settings that lasted approximately 50 to 70 min. Youth were given pizza or gift card incentives for their participation, depending on what was allowable by each agency. The youth did not report emotional distress, but a mental health professional was available in the event that youth would become distressed. The exclusionary criteria for this study included the following: (a) developmental delay and fifth grade or higher reading level; (b) youth below the age of 12 or above the age of 20; and (c) a serious psychotic disorder as indicated by a mental health professional in the agency.

The average age of the youth was 17.19 years (SD = 2.52 years), and the last grade completed on average was 10th grade (SD = 1.82 grades). The average number of months youth lived in any residential placement for any reason was 22 months (SD = 22.81). The racial and ethnic make-up of the group included Caucasian (n = 73; 36.5%), African American (n = 33; 16.5%), Hispanic/Latino (n = 63; 31.5%), Asian (n = 3; 1.5%), Native American (n = 9; 4.5%), and other ethnicities (n = 16; 8%). The youth were raised by two parents (n = 88; 44.0%), by single mothers (n = 70; 35.0%), single fathers (n = 12; 6.0%), grandparents (n = 17; 8.5%), other relatives (n = 4; 2.0%), or in foster homes (n = 7; 3.5%). In determining group differences on these demographics, results showed a statistically significant difference between the three offender groups on race (χ² = 20.27, p < .001); youth who committed a sexual crime, relative to a non-sexual crime were more likely to be White. There were no statistically significant differences between offending groups and other demographic variables, including age (t = 1.22, p = .226), grade level (χ² = 11.03, p = .087), length of time spent in any residential or detention facility (t = −1.02, p = .320), or family structure (χ² = 8.45, p = .295).

Measures

Dependent variables

Early victimization

Early victimization was measured using the Childhood Trauma Questionnaire (CTQ; Bernstein et al., 1994). The CTQ is a 25-item standardized measure that asked youth to report how often (0 = never, 1 = rarely, 2 = sometimes, 3 = often, 4 = very often) they experienced abuse while growing up. Five subscales were included: (a) physical neglect (e.g., I didn’t have enough to eat; I had to wear dirty clothes) had weak internal consistency (α = .646); (b) emotional abuse or experiencing direct psychological abuse (e.g., I felt that someone in my family hated me; I thought my parents wished I had never been born) had good internal consistency (α = .830); (c) physical abuse (e.g., I was punished with a belt, board, cord, or some other hard object; people in my family hit me so hard, it left me with bruises or marks) with good internal consistency (α = .885); (d) sexual abuse (e.g., someone molested me; someone tried to make me do sexual things or watch sexual things) with good internal consistency (α = .883); and (e) emotional neglect which has been operationalized as a lack of emotional support (e.g., I felt loved; people in my family felt close to each other—all reverse coded) had strong internal consistency (α = .926). Due to the unacceptable internal consistency, physical neglect was not used other than in bivariate correlations. Among the entire sample, 92 youth (46%) reported at least one physical abuse experience, with an average score of .62 (SD = 1.02); 49 youth (24.5%) reported at least one sexual abuse experience, with an average score of .31 (SD = .76); 122 youth (61%) reported at least one emotional abuse experience, with an average score of .84 (SD = 1.08); 157 youth (78.5%) reported at least one physical neglect experience, with an average score of 1.44 (SD = 1.35); and 138 youth (69%) reported at least one emotional neglect experience, with an average score of .71 (SD = .77).

Domestic trauma experiences

Other experiences of childhood trauma in the home were measured through a 12-item questionnaire used in similar studies of justice-involved youth (e.g., Burton, Duty, & Leibowitz, 2011). This instrument asked youth to describe experiences of indirect violence or traumatic events in the home with example items such as “having a parent with an alcohol or drug problem” or “hitting, slapping, punching or other violence between parents and children.” The response items were 0 = not at all like my home; 1 = a little like my home; 2 = somewhat like my home; 3 = a lot like my home; 4 = exactly like my home and the internal consistency was strong (α = .846). Among the sample, 170 youth (85%) reported at least one domestic traumatic experience, with an average score of .70 (SD = .68).

Executive functioning

Executive Functioning was measured using the Behavior Rating Index of Executive Function-Self Report (BRIEF-SR; Guy, Isquith, & Gioia, 2004). The BRIEF assesses youths’ executive functioning deficits and includes 80 items measured on a three-point scale (0 = never; 1 = sometimes; 2 = often). The instrument was validated with two overarching dimensions of executive functioning: Behavioral Regulation Index (BRI) and Meta-cognition Index (MI). Taken together, all of the items create the Global Executive Composite (GEC) score. The BRI includes four factors: Inhibit (e.g., “I blurt things out”) (α = .889), Behavioral Shift (e.g., “I have trouble changing from one activity to another”) (α = .844), Emotional Control (e.g., “I get upset easily”) (α = .877), and Cognitive Shift (e.g., “I have trouble thinking of a different way to solve a problem”) (α = .906). Among the sample, 175 youth (87.5%) endorsed at least one problem with inhibitions, with an average score of .57 (SD = .48); 148 youth (74%) endorsed at least one problem with behavior shift, with an average score of .52 (SD = .48); 150 youth (75%) endorsed at least one problem with cognitive shift, with an average score of .43 (SD = .42); and 162 youth (81%) endorsed at least one problem with emotional control, with an average score of .47 (SD = .44).

The MI includes four factors: Working Memory (e.g., “I have trouble remembering things”) (α = .847), Planning (e.g., “I don’t think ahead about possible problems”) (α = .897), Organizing Materials (e.g., “My backpack is a mess”) (α = .787), and Task Completion (e.g., “I have difficulty finishing a task on my own”) (α = .901). Among the sample, 166 youth (83%) endorsed at least one problem with working memory, with an average score of .45 (SD = .42); 159 youth (79.5%) endorsed at least one problem with planning and organizing, with an average score of .42 (SD = .42); 138 youth (69%) endorsed at least one problem with organization of materials, with an average score of .38 (SD = .42); and 142 youth (71%) endorsed at least one problem with task completion, with an average score of .39 (SD = .44).

Independent variable

Offender classifications

The sample (N = 200) consisted of youth who committed sexual crimes only, non-sexual crimes only, or both sexual and non-sexual crimes. To determine these classifications, youth were asked whether they have committed a sexual or a non-sexual crime that would get them in trouble with the law (0 = no; 1 = yes). The original variables were cumulated so that a positive response to both questions (= 2) equated to a third category of criminal versatility. Three total groups were included in the analyses: (a) sexual offenders only (SO; n = 41); (b) non-sexual offenders only (NSO; n = 124); and (c) criminally versatile offenders (CVO; n = 27).

Analyses

Data were analyzed using IBM Statistical Software Package SPSS for Windows version 24 (IBM Corp., 2016). There was less than 5% missing data on all dependent variables, and listwise deletion was employed (Cheema, 2014). The results were conducted in two steps. The first step was a bivariate correlation table to determine statistically significant associations between dependent variables of interest.

Second, a multivariate analysis of variance (MANOVA) was used to test offending group differences (independent variable) on dependent variables of interest including childhood trauma experiences, domestic trauma experiences, and executive functioning. A MANOVA is a suitable statistical test to determine how the independent grouping variable can explain some of the mean differences among multiple correlated dependent variables (Carey, 1998). For all significant univariate tests of analyses of variance, Levene’s statistic test was used to reject or fail to reject the assumption of equal variances. This informed the post hoc test to make differential determinations of significant group differences. Scheffé’s test was performed if equal variances were assumed (p > .05) and the Games–Howell test was used if equal variances were not assumed (p < .05). These tests were selected as the most conservative for unequal sample sizes among groups (Shingala & Rajyaguru, 2015). The results also report the partial eta squared statistic or measure of the effect that indicates the proportion of the variance explained in the dependent variables by the independent variables while holding all other variables constant (Richardson, 2011).

Results

Correlations

The bivariate correlation revealed statistically significant associations between multiple variables. Emotional abuse was significantly positively correlated (p < .05) with all domains, including the larger domains of executive function including behavioral regulation, meta-cognition, and global executive composite. Sexual abuse was significantly positively correlated (p < .05) with all aspects of executive functioning except cognitive shift and emotional control. Physical abuse was significantly positively correlated (p < .05) with all aspects of executive functioning except behavioral and cognitive shift and working memory. Physical neglect, although positively correlated with almost all aspects of executive functioning, was eliminated from the final model due to poor internal consistency in the scale. Emotional neglect had few statistical associations with executive functioning. Domestic trauma events were positively correlated with many, but not all domains of executive functioning. Furthermore, there was a high statistically significant correlation between physical and emotional abuse (r = .778, p < .001), suggesting that they should be combined for analyses. For the full correlation results, see Table 1.

Table 1.

Bivariate Correlations between Executive Dysfunction and Child Maltreatment.

	SxAb	EmAb	PhNg	EmNg	Dom	Inh	BeSh	CgSh	EmCn	BRI	WkMem	Pln/Org	OrgMat	TskCo	MI	GEC
Physical Abuse	.446***	.778***	.185***	.365***	.482***	.168*	.098	.083	.154*	.154*	.117	.202**	.156*	.154*	.176*	.175*
Sexual Abuse		.487***	.121	.123	.278***	.247**	.178*	.125	.131	.204**	.187*	.304***	.263***	.294***	.276***	.252***
Emotional Abuse			.035	.378***	.519***	.319***	.253***	.224**	.303***	.321***	.232**	.318***	.308***	.291***	.326***	.337***
Physical Neglect				.135	−.019	−.248**	−.275***	−.295***	−.294***	−.303***	−.294***	−.296***	−.296***	−.268***	−.323***	−.322***
Emotional Neglect					.238* *	.121	.173*	.117	.051	.123	.113	.066	.017	.058	.062	.090
Domestic Trauma						.225**	.145*	.140	.228**	.220**	.120	.180*	.124	.114	.155*	.194**
Inhibitions							.769***	.718***	.733***	.924***	.759***	.760***	.713***	.738***	.811***	.887***
Behavioral Shift								.804***	.749***	.898***	.725***	.800***	.695***	.774***	.825***	.881***
Cognitive Shift									.768***	.878***	.718***	.784***	.688***	.789***	.825***	.872***
Emotional Control										.900***	.659***	.741***	.648***	.671***	.761***	.848***
BRI											.797***	.852***	.760***	.815***	.890***	.966***
Working Memory												.820***	.741***	.773***	.896***	.876***
Planning/organizing													.810***	.873***	.955***	.933***
Organization of Materials														.811***	.890***	.853***
Task Completion															.929***	.902***
MI																.976***

Note. BRI = Behavioral Regulation Index; MI = Meta-cognition Index; GEC = Global Executive Composite.

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

MANOVA

The one-way MANOVA revealed a statistically significant multivariate main effect for youth groups, Wilks’ λ = .809, F(12, 200) = 3.29, p < .001, partial eta squared = .101. There was sufficient power to detect the effect at .996. The overall test was significant, and therefore the main effects were examined. Only the statistically significant group difference results will be presented.

The results revealed statistically significant mean differences between offending groups on sexual abuse, F(2, 180) = 7.81, p < .001, partial eta squared = .08; physical/emotional abuse, F(2, 180) = 6.25, p = .002, partial eta squared = .07; working memory, F(2, 180) = 3.83, p = .023, partial eta squared = .04; planning and organizing, F(2, 180) = 3.42, p = .001, partial eta squared = .04; and organization of materials, F(2, 180) = 4.03, p = .019, partial eta squared = .04. For the full MANOVA table, see Table 2.

Table 2.

Descriptive Statistics and Multivariate Analysis of Variance Results.

Dependent variables	Sexual offenders only (SO)	Non-sexual offenders only (NSO)	Criminally versatile offenders (CVO)	Multivariate analysis of variance
Dependent variables	Sexual offenders only (SO)	M (SD)	M (SD)	M (SD)	pη2
Sexual abuse	0.68 (1.02)	0.17 (0.57)	0.52 (0.95)	7.81***	.08
Physical/emotional abuse	0.92 (1.04)	0.65(0.82)	1.36 (1.35)	6.26**	.07
Working memory	0.59 (0.50)	0.39(0.38)	0.50 (0.44)	3.83*	.04
Planning/organizing	0.55 (0.40)	0.37 (0.38)	0.50 (0.46)	3.43*	.04
Organization of materials	0.56 (0.48)	0.34 (0.36)	0.40 (0.46)	4.03*	.04

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

Post hoc results

Games–Howell post hoc test results revealed significant pairwise mean differences between sexual only offenders (SO) and non-sexual offenders (NSO) (Mean difference = .51, p = .014) on rates of sexual abuse; the SO group had a higher mean score. Games–Howell post hoc tests also revealed significant pairwise mean differences between non-sexual offenders (NSO) and criminally versatile offenders (CVO) (Mean difference = .71, p = .039) on rates of physical and emotional abuse; the CVO group had a higher mean score.

Scheffe’s post hoc test results revealed significant pairwise mean differences between sexual offenders only (SO) and non-sexual offenders (NSO) (Mean difference = .21, p = .030) on rates of working memory domains of executive functioning; the SO group had a higher mean score. Scheffe’s post hoc test results also revealed significant pairwise mean differences between sexual offenders only (SO) and non-sexual offenders (NSO) (Mean difference = .18, p = .046) on rates of planning and organizing domains of executive functioning; the SO group had a higher mean score. Finally, Scheffe’s post hoc test results revealed significant pairwise mean differences between sexual offenders only (SO) and non-sexual offenders (NSO) (Mean difference = .21, p = .019) on rates of organization of materials domains of executive functioning; the SO group had a higher mean score.

Discussion

This study aimed to determine associations between early-life victimization, other traumatic experiences in the home, and executive functioning deficits. Furthermore, this study aimed to test how disparate offending groups differentially experience these early risks. The results revealed that there were statistically significant associations between sexual, physical, and emotional abuse on almost all domains of executive functioning. This suggests that perhaps, among this sample of juvenile justice youth, early direct forms of victimization may be associated with deficits in neurological processing. This finding fits within the broader research given that youth involved in the juvenile justice system have higher than average rates of early-life victimization (Currie & Tekin, 2006; Ford et al., 2007; Stahl, 2006) and may be at formative risk for a host of multiple adverse behavioral or cognitive outcomes (Kelly et al., 2002; Morais et al., 2016; White et al., 1994; Zou et al., 2013). In particular, sexual, emotional, and physical abuse experiences may be critical developmental risks associated with sexual and non-sexual behavior problems in youth (Cook et al., 2017; Costello et al., 2002; Finkelhor et al., 2005; Ford et al., 2006; Tsang, 2018; Yoder et al., 2019b). The nature of these direct forms of victimization, being severe, and in some cases violent in magnitude, may be internalized differently than other indirect experiences (Caputo, Frick, & Brodsky, 1999). This could explain why the direct and harsh forms of victimization contributed to executive function deficits to a greater degree than the indirect forms or even neglect. However, further research is needed to parse out severity, frequency, dosage, or developmental timing of these experiences as they contribute to various adverse outcomes including executive functioning.

In addition, as research is beginning to highlight the linkages between trauma experiences and neurological impairments (Perry et al., 1995; Schore, 2001; Steinberg, 2008), this study may contribute to better understanding the etiology of criminal behavior among youth populations. There is a strong theoretical and empirical base connecting early victimization to a disruption in the development of necessary neurological processes during childhood and adolescence (Jaffee & Maikovich-Fong, 2014; Perry et al., 1995; Schore, 2001). As such, neurological pathways that would be created from an enriching environment are interrupted for youth who undergo trauma or victimization. Consequently, neurological connections are made in areas of the brain responsible for fight and flight and youth can become hypervigilant and aroused in otherwise benign or non-threatening situations (Perry et al., 1995). This can partially explain why there may be a high concentration of traumatized youth in the criminal justice system. This may also explain why traumatized youth may display behavioral, social, or cognitive processing problems (Jaffee & Maikovich-Fong, 2014; Steinberg, 2008). Further research is needed to test differential experiences of trauma and neurological links between youth typologies to better understand how these experiences may or may not be differentiated between offending groups.

This study found mixed results for how developmental risk factors contribute differentially to certain specialization typologies. For instance, the sexual offending group had higher scores of certain domains of executive function compared with the non-sexual offending group. In particular, youth who commit only sexual crimes had higher impairments in working memory, planning and organizing, and organization of materials. This suggests that perhaps these deficits could contribute to offense patterns differentially such that youth who only commit sexual crimes may not be as astute in assessing consequences or the impact of behavior. Some of these characteristics have been previously studied, and although researchers have documented disinhibitions and limited behavioral and emotional regulation among youth who commit sexual crimes (Burton et al., 2016; Miner, 2002; Stinson et al., 2008), there is inconclusive evidence underlying how such deficits actually predict criminal behavior. Further prospective research needs to evaluate these executive functioning capacities in relation to the criminal behavior perpetrated by the youth, as some offenses may require more planning, thought, and strategy, whereas others may be linked to more impulsivity; such distinctions may also depend on certain trait characteristics of offenders (Lawing, Frick, & Cruise, 2010; van Wijk et al., 2006). This finding can also be contextualized, conceivably, by the higher rates of sexual abuse among youth who commit sexual crimes, as found in this study, and consistent with a significant body of extant research (Burton, Miller, & Shill, 2002; Seto & Lalumière, 2010; van Wijk et al., 2006). Sexual victimization may contribute to greater executive dysfunction among youth sexual offenders (Yoder, Grady, & Precht, 2019a). Conceivably, sexual victimization experiences create vulnerabilities in higher order processing that contribute to sexual violence (Blanco et al., 2015; De Bellis, Spratt, & Hooper, 2011). Certainly, additional research is needed on executive functioning capacities of youth who commit sexual crimes to further understand how prefrontal cortex processing can contribute to patterns of sexual violence and how these may be a function of sexual victimization experiences.

One particularly interesting finding from this study was that youth who are criminally versatile had higher rates of physical and emotional abuse compared with youth who were non-sexual offenders. Given that youth offenders, in general, have higher rates of childhood physical abuse experiences relative to general population youth (Zou et al., 2013), this finding may suggest that there are criminal severity patterns that may be accounted for by early-life abuse experiences. The seriousness of an offense—although examined as a proxy via specialization typologies—should be further tested as a function of early abuse or victimization. Some research has begun to better understand how differential abuse experiences influence serious or non-serious offending patterns (Yoder et al., 2019b). Furthermore, youth who commit sexual crimes may be criminally versatile in their reoffense patterns, as they are more likely to commit a subsequent non-sexual crime (Caldwell, 2016; Mulder, Vermunt, Brand, Bullens, & van Marle, 2012; Nisbet, Wilson, & Smallbone, 2004; Rajilic & Gretton, 2010; Waite et al., 2005). Therefore, the field requires longitudinal research that tests the sequential nature of sexual and non-sexual violence and the developmental antecedents to such experiences.

Implications

There are multiple implications resulting from this study. First, the findings can inform existing trauma screens for youth involved in the juvenile justice systems. Youth who experience abuse or victimization ought to be screened for executive functioning impairments to determine areas of intervention. Given the preponderance of youth with traumatic histories in the juvenile justice system, tools such as the BRIEF (Guy et al., 2004) can be instituted uniformly in detention, incarceration, or community correctional settings. Findings from this study could inform the enhancement of programming to become more developmentally congruent. For example, our findings align with models like the Neurosequential Model of Therapeutics (NMT; Perry, 2006, 2009) in which professionals map child behavioral trajectories according to their experiences of early adversity. Treatment plans can then be tailored to each child, reflecting children’s distinct developmental maps. These findings can be disseminated to treatment providers to tailor timing of initial intervention; dosage or how frequently services are needed; or how, when, and who to target to address malleable areas and intentionally build in buffering agents. Juvenile justice programming may in turn become more attuned to changing victimization and executive functioning trajectories and efforts can be made to train professionals to use and implement developmentally responsive approaches, including well-known evidence-based practices such as trauma-focused cognitive behavioral therapy (Cohen, Mannarino, Kliethermes, & Murray, 2012), relational experiential therapy (Perry, 2009), or narrative therapy (Deblinger, Mannarino, Cohen, Runyon, & Steer, 2011). Such trauma-informed models can begin to be instituted more uniformly in juvenile justice settings to detect trauma triggers that associate with cognitive patterns (Levenson, 2014). Doing so in a safe setting may be critical for youth to develop healthy coping strategies (Rasmussen, 2012).

Furthermore, results from this study can inform services to become more responsive to differential patterns of offending among youth. Supporting the risk principle and matching risk levels with appropriate judicial responses (Andrews, Bonta, & Wormith, 2011) is a necessary juvenile justice response. Therefore, youth with more severe offending patterns that may or may not be reflected by multiple forms of offending ought to receive higher doses and intense rehabilitative services. Similarly, youth ought to receive rehabilitation responses that align closely with the risk factors that contributed to their criminal behaviors. As such, risk assessments should be empirically guided and structured such that incidents of trauma and neurological processing are integrated more consistently. Furthermore, risk assessment tools, although developed for either general offending or sexual offending, can be refined to integrate risk indicators for patterns of criminal versatility.

Limitations

The results of this article should be presented in the context of the limitations. First, this was a cross-sectional study, with limited ability to conduct analyses on the causal pathways between constructs; statistical findings are correlational and not causal. Furthermore, the data were retrospective and youth could have inaccuracies in their ability to remember information according to the time frames given. There should be more prospective longitudinal research studies to determine whether these findings would hold up over time. The self-report data have limitations and should be triangulated with other data sources including official record data.

The findings from this study can only be generalized to the youth who completed the surveys. There were limited youth who were grouped as criminally versatile or sexual only offenders, suggesting that additional research with more robust sample sizes should be conducted in this area. There are also extraneous variables that were not accounted for in this study which could have contributed to the relationships found. Furthermore, the measures in this study may have some limitations. There needs to be enhanced instrumentation for measuring criminally versatile categorizations and consider how these can be composed of data that represent a more robust picture of the types of criminal patterns of youth. The way in which criminal versatility was measured in these data was limited in that it did not account for current criminal patterns and only captured those in the past. Further research should account for classifications of violence by including whether the sexual or non-sexual criminal act was violent. Such nuance can help refine associations with developmental antecedents. In addition, the relationship between trauma and executive functioning should be parsed out according to offender specialization typology to better understand how these groups may have differential risk histories.

Footnotes

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 iD

Jamie Yoder

References

Aebi

Landolt

M. A.

Mueller-Pfeiffer

Schnyder

Maier

Mohler-Kuo

(2015). Testing the “sexually abused-abuser hypothesis” in adolescents: A population-based study. Archives of Sexual Behavior, 44, 2189-2199.

Andrews

D. A.

Bonta

Wormith

J. S.

(2011). The risk-need-responsivity (RNR)model: Does adding the good lives model contribute to effective crime prevention? Criminal Justice and Behavior, 38, 735-755.

Augusti

E. M.

Melinder

(2013). Maltreatment is associated with specific impairments in executive functions: A pilot study. Journal of Traumatic Stress, 26, 780-783.

Aupperle

R. L.

Melrose

A. J.

Stein

M. B.

Paulus

M. P.

(2012). Executive function and PTSD: Disengaging from trauma. Neuropharmacology, 62, 686-694. doi:10.1016/j.neuropharm.2011.02.008

Bernstein

D. P.

Fink

Handelsman

Foote

Lovejoy

Wenzel

. . . Ruggiero

(1994). Initial reliability and validity of a new retrospective measure of child abuse and neglect. American Journal of Psychiatry, 151, 1132-1136.

Blanco

Nydegger

L. A.

Camariollo

Trinidad

D. R.

Schramm

Ames

S. L.

(2015). Neurological changes in brain structure and functions among individuals with a history of childhood sexual abuse: A review. Neuroscience & Biobehavioral Reviews, 57, 63-69.

Bücker

Kapczinski

Post

Ceresér

K. M.

Szobot

Yatham

L. N.

. . . Kauer-Sant’Anna

(2012). Cognitive impairment in school-aged children with early trauma. Comprehensive Psychiatry, 53, 758-764.

Burton

Demuynck

Yoder

(2016). Executive dysfunction predicts delinquency but not characteristics of sexual aggression among adolescent sexual offenders. Sexual Abuse, 28, 707-721.

Burton

Miller

D. L.

Shill

C. T.

(2002). A social learning theory comparison of the sexual victimization of adolescent sexual offenders and nonsexual offending male delinquents. Child Abuse & Neglect, 26, 893-907.

10.

Burton

D. L.

Duty

K. J.

Leibowitz

G. A.

(2011). Differences between sexually victimized and nonsexually victimized male adolescent sexual abusers: Developmental antecedents and behavioral comparisons. Journal of Child Sexual Abuse, 20, 77-93.

11.

Butler

S. M.

Seto

M. C.

(2002). Distinguishing two types of adolescent sex offenders. Journal of the American Academy of Child & Adolescent Psychiatry, 41, 83-90.

12.

Caldwell

M. F.

(2002). What we do not know about juvenile sexual reoffense risk. Child Maltreatment, 7, 291-302.

13.

Caldwell

M. F.

(2016). Quantifying the decline in juvenile sexual recidivism rates. Psychology, Public Policy, and Law, 22, 414-426. doi:10.1037/law0000094

14.

Caputo

A. A.

Frick

P. J.

Brodsky

S. L.

(1999). Family violence and juvenile sex offending: The potential mediating role of psychopathic traits and negative attitudes towards women. Criminal Justice and Behavior, 26, 338-356.

15.

Carey

(1998). Multivariate analysis of variance (MANOVA): I. Theory. Retrieved from http://ibgwww.colorado.edu/~carey/p7291dir/handouts/manova1.pdf

16.

Cheema

J. R.

(2014). Some general guidelines for choosing missing data handling methods in educational research. Journal of Applied Statistical Methods, 13, 53-75.

17.

Cohen

J. A.

Mannarino

A. P.

Kliethermes

Murray

L. A.

(2012). Trauma-focused CBT for youth with complex trauma. Child Abuse & Neglect, 36, 528-541.

18.

Coleman

(2005). Trauma and incarcerated youth. Journal of Evidence-Based Social Work, 2, 113-124. doi:10.1300/J394v02n03_08

19.

Coleman

Stewart

L. M.

(2010). Prevalence and impact of childhood maltreatment in incarcerated youth. American Journal of Orthopsychiatry, 80, 343-349. doi:10.1111/j.1939-0025.2010.01038.x

20.

Cook

Spinazzola

Ford

Lanktree

Blaustein

Cloitre

. . . Mallah

(2017). Complex trauma in children and adolescents. Psychiatric Annals, 35, 390-398.

21.

Costello

E. J.

Erkanli

Fairbank

J. A.

Angold

(2002). The prevalence of potentially traumatic events in childhood and adolescence. Journal of Traumatic Stress, 15, 99-112. doi:10.1023/A:1014851823163

22.

Craig

L. A.

Browne

K. D.

Beech

Stringer

(2004). Personality characteristics associated with reconviction in sexual and violent offenders. Journal of Forensic Psychiatry & Psychology, 15, 532-551. doi:10.1080/14789940412331270726

23.

Currie

Tekin

(2006, April). Does child abuse cause crime? (NBER Working Paper No. 12171). Retrieved from http://www.nber.org/papers/w12171

24.

De Bellis

M. D.

Spratt

E. G.

Hooper

S. R.

(2011). Neurodevelopmental biology associated with childhood sexual abuse. Journal of Child Sexual Abuse, 20, 548-587.

25.

Deblinger

Mannarino

A. P.

Cohen

J. A.

Runyon

M. K.

Steer

R. A.

(2011). Trauma focused cognitive behavioral therapy for children: Impact of the trauma narrative and treatment length. Depression and Anxiety, 28, 67-75.

26.

Fago

D. P.

(2003). Evaluation and treatment of neurodevelopmental deficits in sexually aggressive children and adolescents. Professional Psychology: Research and Practice, 34, 248-257. doi:10.1037/0735-7028.34.3.248

27.

Finkelhor

Ormrod

Turner

Hamby

S. L.

(2005). The victimization of children and youth: A comprehensive, national survey. Child Maltreatment, 10, 5-25. doi:10.1177/1077559504271287

28.

Ford

J. D.

Chapman

Hawke

Albert

(2007). Trauma among youth in the juvenile justice system: Critical issues and new directions. Delmar, NY: National Center for Mental Health and Juvenile Justice. Available from www.ncmhjj.com

29.

Ford

J. D.

Chapman

Mack

J. M.

Pearson

(2006). Pathways from traumatic child victimization to delinquency: Implications for juvenile and permanency court proceedings and decisions. Juvenile and Family Court Journal, 57, 13-26. doi:10.1111/j.1755-6988.2006.tb00111.x

30.

Ford

M. E.

Linney

J. A.

(1995). Comparative analysis of juvenile sex offenders, violent nonsexual offenders, and status offenders. Journal of Interpersonal Violence, 10, 56-70. doi:10.1177/088626095010001004

31.

Freeman

K. A.

Dexter-Mazza

E. T.

Hoffmanl

K. C.

(2005). Comparing personality characteristics of juvenile sex offenders and non-sex offending delinquent peers: A preliminary investigation. Sexual Abuse, 17, 3-12. doi:10.1007/s11194-005-1206-8

32.

Frías-Armenta

Valdez-Ramírez

Nava-Cruz

Figueredo

A. J.

Corral-Verdugo

(2010). Executive functions, attention and juvenile delinquency. In Frías-Armenta

Corral-Verdugo

(Eds.), Bio-psycho-social perspectives on interpersonal violence (pp. 29-49). Hauppauge, NY: Nova Science Publishers.

33.

Gioia

G. A.

Isquith

P. K.

Retzlaff

P. D.

Espy

K. A.

(2002). Confirmatory factor analysis of the Behavior Rating Inventory of Executive Function (BRIEF) in a clinical sample [Special issue: Behavior Rating Inventory of Executive Function]. Child Neuropsychology, 8, 249-257. doi:10.1076/chin.8.4.249.13513

34.

Guy

S. C.

Isquith

P. K.

Gioia

(2004). Behavior Rating Inventory of Executive Function Self-Report Version: Professional manual. Lutz, FL: Psychological Assessment Resources.

35.

Hoaken

P. N.

Allaby

D. B.

Earle

(2007). Executive cognitive functioning and the recognition of facial expressions of emotion in incarcerated violent offenders, non-violent offenders, and controls. Aggressive Behavior: Official Journal of the International Society for Research on Aggression, 33, 412-421. doi:10.1002/ab.20194

36.

Hunter

J. A.

Figueredo

A. J.

Malamuth

N. M.

Becker

J. V.

(2003). Juvenile sex offenders: Toward the development of a typology. Sexual Abuse: A Journal of Research and Treatment, 15, 27-48. doi:10.1023/A:1020663723593

37.

IBM Corp. (2016). IBM SPSS Statistics for Windows, Version 24.0. Armonk, NY: Author.

38.

Jaffee

S. R.

Maikovich-Fong

A. K.

(2014). Effects of chronic maltreatment and maltreatment timing on children’s behavior and cognitive abilities. Journal of Child Psychology and Psychiatry, 52, 2184-2194.

39.

Jespersen

A. F.

Lalumière

M. K.

Seto

M. C.

(2009). Sexual abuse history among adult sex offenders and non-sex offenders: A meta-analysis. Child Abuse & Neglect, 33, 179-192.

40.

Kelly

Richardson

Hunter

Knapp

(2002). Attention and executive function deficits in adolescent sex offenders. Child Neuropsychology, 8, 138-143. doi:10.1076/chin.8.2.138.8722

41.

Kirke-Smith

Henry

Messer

(2014). Executive functioning: Developmental consequences on adolescents with histories of maltreatment. British Journal of Developmental Psychology, 32, 305-319.

42.

Lawing

Frick

Cruise

K. R.

(2010). Differences in offending patterns between adolescent sex offenders high or low in callous-unemotional traits. Psychological Assessment, 22, 298-305.

43.

Levenson

(2014). Incorporating trauma-informed care into evidence-based sex offender treatment. Journal of Sexual Aggression, 20, 9-22.

44.

Levenson

Baglivio

Wolff

K. T.

Epps

Royall

Gomez

Kaplan

(2017). You learn what you live: Prevalence of childhood adversity in the lives of juveniles arrested for sexual offenses. Advances in Social Work, 18, 1-18.

45.

Lussier

(2005). The criminal activity of sexual offenders in adulthood: Revisiting the specialization debate. Sexual Abuse: A Journal of Research and Treatment, 17, 269-292.

46.

Lussier

Leclerc

Cale

Proulx

(2007). Developmental pathways of deviance in sexual aggressors. Criminal Justice and Behavior, 34, 1441-1462.

47.

Miner

M. H.

(2002). Factors associated with recidivism in juveniles: An analysis of serious juvenile sex offenders. Journal of Research in Crime and Delinquency, 39, 421-436.

48.

Morais

H. B.

Joyal

C. C.

Alexander

A. A.

Fix

R. L.

Burkhart

B. R.

(2016). The neuropsychology of adolescent sexual offending: Testing an executive dysfunction hypothesis. Sexual Abuse: Journal of Research and Treatment, 28, 741-754.

49.

Mothes

Kristensen

C. H.

Grassi-Oliveira

Fonseca

R. P.

de Lima Argimon

I. I.

Irigaray

T. Q.

(2015). Childhood maltreatment and executive functions in adolescents. Child and Adolescent Mental Health, 20, 56-62. doi:10.1111/camh.12068

50.

Mulder

Vermunt

Brand

Bullens

van Marle

(2012). Recidivism in subgroups of serious juvenile offenders: Different profiles, different risks? Criminal Behaviour and Mental Health, 22, 122-135. doi:10.1002/cbm.1819

51.

Nikulina

Spatz Widom

(2013). Child maltreatment and executive functioning in middle adulthood: A prospective examination. Neuropsychology, 27, 417-427.

52.

Nisbet

I. A.

Wilson

P. H.

Smallbone

S. W.

(2004). A prospective longitudinal study of sexual recidivism among adolescent sex offenders. Sexual Abuse: A Journal of Research and Treatment, 163, 223-234.

53.

Perry

B. D.

(2006). The Neurosequential Model of Therapeutics: Applying principals of neuroscience to clinical work with traumatized and maltreated children. In Webb

N. B.

(Eds.), Working with traumatized youth in child welfare (pp. 27-52). New York, NY: The Guilford Press.

54.

Perry

B. D.

(2009). Examining child maltreatment through a neurodevelopmental lens: Clinical applications of the Neurosequential Model of Therapeutics. Journal of Loss and Trauma, 14, 240-255.

55.

Perry

B. D.

Pollard

R. A.

Blakley

T. L.

Baker

W. L.

Vigilante

(1995). Childhood trauma, the neurobiology of adaptation, and “use-dependent” development of the brain: How “states” become “traits.” Infant Mental Health Journal, 16, 271-291.

56.

Rajilic

Gretton

H. M.

(2010). An examination of two sexual recidivism risk measures in adolescent offenders: The moderating effect of offender type. Criminal Justice and Behavior, 37, 1066-1086.

57.

Rasmussen

L. A.

(2012). Trauma Outcome Process Assessment (TOPA) model: An ecological paradigm for treating traumatized sexually abusive youth. Journal of Child & Adolescent Trauma, 5, 63-80. doi:10.1080/19361521.2012.646645

58.

Richardson

J. T. E.

(2011). Eta squared and partial eta squared as measures of effect size in educational research. Educational Research Review, 6, 135-147.

59.

Schore

A. N.

(2001). The effects of early relational trauma on right brain development, affect regulation, and infant mental health. Infant Mental Health Journal, 22, 201-269.

60.

Seto

M. C.

Lalumière

M. L.

(2010). What is so special about male adolescent sexual offending? A review and test of explanations through meta-analysis. Psychological Bulletin, 136, 526-575. doi:10.1037/a0019700

61.

Shingala

M. C.

Rajyaguru

(2015). Comparison of post hoc tests for unequal variance. International Journal of New Technologies in Science and Engineering, 2(5), 22-33.

62.

Skilling

T. A.

Doiron

J. M.

Seto

M. C.

(2011). Exploring differences in youth and parent reports of antisociality among adolescent sexual and nonsexual offenders. Psychological Assessment, 23, 1153-1163.

63.

Smallbone

(2006). Social and psychological factors in the development of delinquency and sexual deviance. In Barbaree

H. E.

Marshall

W. L.

(Eds.), The juvenile sex offender (2nd ed., pp. 105-127). New York, NY: Guildford.

64.

Spann

M. N.

Mayes

L. C.

Kalmar

J. H.

Guiney

Womer

F. Y.

Pittman

. . . Blumberg

H. P.

(2012). Childhood abuse and neglect and cognitive flexibility in adolescents. Child Neuropsychology, 18, 182-189. doi:10.1080/09297049.2011.595400

65.

Stahl

A. L.

(2006). Delinquency cases in juvenile court, 2002. Washington, DC: Office of Juvenile Justice and Delinquency Prevention, U.S. Department of Justice. Retrieved from http://www.ncjrs.gov/pdffiles1/ojjdp/fs200602.pdf

66.

Steinberg

(2008). A social neuroscience perspective on adolescent risk-taking. Developmental Review, 28, 78-106.

67.

Stinson

J. D.

Becker

J. V.

Sales

B. D.

(2008). Self-regulation and the etiology of sexual deviance: Evaluating causal theory. Violence and Victims, 23, 35-52.

68.

Tsang

(2018). Troubled or traumatized youth? The relations between psychopathy, violence exposure, posttraumatic stress disorder, and antisocial behavior among juvenile offenders. Journal of Aggression, Maltreatment & Trauma, 27, 164-178. doi:10.1080/10926771.2017.1372541

69.

van Wijk

Vermiern

Loeber

Hart-Kerkhoffs

Doreleijers

Bullens

(2006). Juvenile sex offenders compared to non-sex offenders: A review of the literature 1995-2005. Trauma, Violence, & Abuse, 7, 227-243.

70.

Vasilevski

Tucker

(2016). Wide-ranging cognitive deficits in adolescents following early life maltreatment. Neuropsychology, 30, 239-246.

71.

Veneziano

LeGrand

Richards

(2004). Neuropsychological executive functions of adolescent sex offenders and nonsex offenders. Perceptual and Motor Skills, 98, 661-674. doi:10.2466/pms.98.2.661-674

72.

Waite

Keller

McGarvey

E. L.

Wieckowski

Pinkerton

Brown

G. L.

(2005). Juvenile sex offender re-arrest rates for sexual, violent nonsexual and property crimes: A 10-year follow-up. Sexual Abuse: A Journal of Research and Treatment, 173, 313-331.

73.

Wanklyn

S. G.

Ward

A. K.

Cormier

N. S.

Day

D. M.

Newman

J. E.

(2012). Can we distinguish juvenile violent sex offenders, violent non-sex offenders, and versatile violent sex offenders based on childhood risk factors? Journal of Interpersonal Violence, 27, 2128-2143. doi:10.1177/0886260511432153

74.

Way

Urbaniak

(2008). Delinquent histories of adolescents adjudicated for criminal sexual conduct. Journal of Interpersonal Violence, 23, 1197-1212.

75.

White

J. L.

Moffit

T. E.

Caspi

Bartusch

D. J.

Needles

D. J.

Stouthamer-Loeber

(1994). Measuring impulsivity and examining its relationship to delinquency. Journal of Abnormal Psychology, 103, 192-205. doi:10.1037/002-843X.103.2.192

76.

Worling

J. A.

(2001). Personality-based typology of adolescent male sexual offenders: Differences in recidivism rates, victim-selection characteristics, and personal victimization histories. Sexual Abuse: Journal of Research and Treatment, 13, 149-166. doi:10.1177/107906320101300301

77.

Yoder

Dillard

Leibowitz

(2017). Family experiences and sexual victimization histories: A comparative analysis between youth sexual and nonsexual offenders. International Journal of Offender Therapy and Comparative Criminology, 62, 2917-2936. doi:10.1177/0306624X17738063

78.

Yoder

Grady

Precht

(2019a). Relationships between early life victimization, antisocial traits, and sexual violence: Executive functioning as a mediator. Child Sexual Abuse, 28, 667-689. doi:10.1080/10538712.2019.1588819

79.

Yoder

J. R.

Hodge

A. I.

Ruch

(2019b). Intra- and extra-familial victimization experiences: Differentiating between incarcerated serious youth offenders and youth rapists. Journal of Interpersonal Violence, 34, 3199-3288. doi:10.1177/0886260516669167

80.

Zou

Meng

Deng

Wang

(2013). Executive functioning deficits and childhood trauma in juvenile violent offenders in China. Psychiatry Research, 207, 218-224. doi:10.1016/j.psychres.2012.09.013