Abstract

Prior studies have indicated that that there is an “antisocial” type of juvenile sex offender (JSO) that resembles juvenile non-sex offenders (JNSOs). However, a single categorization of all antisocial JSOs may be too broad given that there are different types of antisocial behavior (e.g., authority conflict, overt, covert). To clarify potential differences between JSOs and JNSOs, different antisocial behavior patterns should be explored and compared between these two groups. This study examined data on Canadian male incarcerated adolescent offenders to identify whether behavioral antecedents differed within JSOs (n = 51), and between JSOs and JNSOs (n = 94). Latent class analysis identified three behavioral groups. For both JSOs and JNSOs there was a Low Antisocial, Overt, and Covert group. Risk factors including offence history, abuse history, and family history were more strongly associated with the Overt and Covert groups compared to the Low Antisocial group. Overall, there were important within-group differences in the behavioral patterns of JSOs, but these differences resembled differences within their JNSO counterpart. Clinical implications for responding to incarcerated JSOs with behavioral problems are discussed.

Keywords: Sex offending, antisocial behavior, non-sex offending, juveniles

Despite a number of meta-analytic studies and research reviews (Becker, 1998; Caldwell, 2002; McCann & Lussier, 2008; van Wijk et al., 2006; Seto & Lalumière, 2010), the developmental origins of juvenile sex offending have remained a neglected area of empirical research (e.g., Carpentier, Leclerc & Proulx, 2011; Lussier & Healey, 2010; Lussier, van den Berg, Bijleveld, & Hendriks, 2012). Smallbone (2006) suggested the origins of juvenile sex offending could be clarified by describing the progression of antisocial behavior across developmental stages and transitions (birth, school entry, puberty, etc.). Some (e.g., Lussier & Healy, 2010) have argued that empirical studies have not focused on the early antisocial behavior of JSOs because those theories that suggest JSOs differ from juvenile non-sex offenders (JNSOs) do not consider antisocial behavior to be relevant in explaining the development of sex offending.

Identifying factors that are shared between JSOs and JNSOs has been somewhat disregarded in favor of factors that are hypothesized to be specific to the JSO population, including sexual abuse, exposure to sexual violence, psychosocial deficits, and deviant sexual behavior (e.g., Seto & Lalumiere, 2010). Some of these factors have been suggested to be related to victim selection, which has lead to attempts to use victim characteristics to classify JSOs based on these factors (e.g., Hunter & Figueredo, 2000; Hunter, Figueredo, Malamuth, & Becker, 2003; Hunter, Figueredo, Malamuth, & Becker, 2004; Richardson, Kelly, Bhate, & Graham, 1997; Smith, Monastersky, & Deisher, 1987; Worling, 2001). However, another method of classifying JSOs is based on the presence of a history of antisocial behavior. In developmental studies, a sex crime committed by a youth has been found to be: (a) part of a general delinquency pattern already fully established, often referred to as the “antisocial” JSO type (Elliott, 1994; Becker, 1998; Butler & Seto, 2002; Lussier et al., 2012), (b) a precursor to a nonsexual criminal pattern in adulthood (Lussier et al., 2012), and; (c) co-occurring with other minor forms of delinquency (Lussier et al., 2012).

The current study was based on the assumption that antisocial behavior is pivotal in the etiology of juvenile sex offending, but its role is more complex than previously discussed. Contrary to what has been argued elsewhere (e.g., Becker, 2000), the current study considered that possibility that there is not just one ‘antisocial’ JSO type, but rather, there are different antisocial pathways escalating to sex offenses that require distinct explanations. This area of research should be studied in order to identify the nature of the hypothesized different antisocial pathways, and whether these antisocial pathways require different intervention and treatment strategies. To address these issues, the current study used retrospective longitudinal data from a Canadian sample of incarcerated offenders to examine the developmental patterns of a sample of JSOs (n = 51) and JNSOs (n = 94). Although the specificity of this sample limited generalizability, this was also the first study that examined antisocial behavior pathways of JSOs and should be used to provide a framework for future research. First, we theoretical positions on the development of sex offending are reviewed.

Literature Review

To make sense of the growing number of theoretical perspectives on sex offending, Lussier et al. (2005) categorized these perspectives into three distinct models: the general model, the specific model, and the general-specific model (see also Harris, Mazerolle, & Knight, 2009; Seto & Lalumiere, 2010). First, the main principle of the general model is that sex offending is simply a manifestation of a general antisocial tendency and therefore specific theoretical explanations of sex offending are not needed (Elliott, 1994; LeBlanc & Loeber, 1998). The general model was the only model to emphasize the importance of understanding the development of antisocial behavior for the prevention of sexual offending (Lussier et al., 2005). Yet, because proponents of this model asserted that JSOs cannot be distinguished from JNSOs, JSO antisocial behavior is assumed to be the same as JNSO antisocial behavior. From this perspective, situational and contextual factors (e.g., the presence of a vulnerable victim, the absence of guardianship) are the main factors used to explain the commission of a sex crime. Second, the main principle of the specific model is that sex offending is part of an abnormal sexual development (e.g., sexual victimization, sexual compulsivity, excessive and early masturbation, deviant sexual interests) (Lussier et al., 2005). Proponents of this explanation argued that sex offending, if untreated, may lead to sexual recidivism in adulthood. In their meta-analysis, McCann and Lussier (2008) found support for the specific model because although sexual recidivism was rare, sexual deviancy was significantly related to sexual recidivism. Third, the main principle of the general-specific model is that various risk factors, including those related to an abnormal sexual and antisocial development, were operating at the time of the sex offence (e.g., Lussier et al., 2005; Seto & Lalumière, 2010; Sims & Sims-Knight, 2003).

Proponents of the general model have asserted that sex offending is unrelated to issues with sexual development because JSOs are more likely to non-sexually recidivate, and are also unlikely to sexually recidivate (Caldwell, 2002; McCann & Lussier, 2008). However, although sex offenders are unlikely to continue to sexually recidivate (e.g., Caldwell, 2002), there is still the question of whether factors that influenced the onset of sex offending differ from factors that influenced the onset of non-sexual offending. In particular, will the general model principle of sex offending as a manifestation of a general antisocial tendency (e.g., Elliott, 1994) be supported when examining whether the antisocial behavior pathways of JSOs are the same as the antisocial behavior pathways of JNSOs?

Seto and Lalumière (2010) conducted a meta-analysis to determine whether individual characteristics between JSOs and JNSOs are similar, different, or both. Overall, seven risk factors distinguished JSOs from JNSOs: (1) JSOs had less extensive criminal histories, (2) JSOs had fewer substance abuse issues, (3) JSOs had fewer antisocial peers, (4) JSOs scored lower on measures of psychopathy (5) JSOs were more likely to have experienced different forms of abuse, particularly sexual abuse (6) JSOs were more likely to have been exposed to violence, including sexual violence in the form of pornography, and (7) JSOs were more likely to have atypical sexual interests and were more likely to be characterized by high anxiety and low self-esteem. In other words, JSOs differed from JNSOs in terms of sexual development (the specific model) as well as in terms of risk factors used to explain general offending (the general model).

Seto & Lalumière (2010) found that JSOs engaged in less criminal behaviour than JNSOs. Therefore, it should be expected that JSOs also engage in less early antisocial behavior (i.e. truancy, stealing, not listening to authority, fighting) compared to JNSOs. Yet, other studies have indicated that early antisocial behavior problems do not differ between JSOs and JNSOs (Ford & Linney, 1995; Jacobs, Kennedy, & Meyer, 1997; Butler & Seto, 2002; van Wijk, Vreugdenhill, & Bullens, 2004; van Wijk et al., 2005a; Hunter et al., 2007; Ronis & Borduin, 2007; Leibowitz et al., 2012). This contradiction in the empirical literature may be related to three key conceptual issues of research that has compared JSOs to JNSOs. The first conceptual issue concerns research design. Retrospective studies have limited ability to indicate whether JSOs are different from JNSOs because of differences in their sexual development (e.g., JSOs engaged in more sexual compulsivity and deviant sexual interests), or whether differences in the sexual behavior of JSOs and JNSOs was related to a shift in the JSO’s sexual development after the onset of their sexual offence. This conceptual issue is related to a concern with the studies included in Seto and Lalumière’s (2010) meta-analysis because these studies could not determine whether JSO and JNSO differences could be identified before the onset of the JSO’s sexual offence.

The second conceptual issue, related to all studies comparing JSOs to JNSOs, is that JSO and JNSO within-group heterogeneity must be accounted for to increase the likelihood that differences between JSOs and JNSOs are observed (Johnson & Knight, 2000; Hunter, Figueredo, Malamuth, & Becker, 2003; Freeman, Dexter-Mazza, & Hoffman, 2005; van Wijk et al., 2005b). To account for within-group differences, sex offenders have been separated based on victim characteristics (i.e. gender, age) (Ford & Linney, 1995; Seto & Lalumière, 2010), offending characteristics (i.e. co-offender, offending histories, offence motivations) (Knight & Prentky, 1993; Butler & Seto, 2002; Bijleveld & Hendricks, 2003; Hunter et al., 2003), and offending trajectories and criminal career patterns (Carpentier et al., 2010; Lussier et al., 2012). Studies that previously indicated no differences in the prevalence of antisocial behavior between JSOs and JNSOs did not account for JSO and JNSO within-group heterogeneity. If JSO and JNSO within-group heterogeneity were not accounted for (e.g., Loeber & Stouthamer-Loeber, 1998) it may have been difficult to identify early antisocial behavior differences between JSOs and JNSOs. If studies included offenders from different samples, this difficulty would be exacerbated. For example, meta-analytic studies (e.g., Seto and Lalumière (2010) that compared JSOs and JNSOs contained studies that sampled from both incarcerated/residential offender populations and community-based populations. Therefore, the differences Seto and Lalumière (2010) identified between JSOs and JNSOs may actually have reflected differences between incarcerated/residential populations and community-based populations rather than unique risk factors that differentiated the development of JSOs and JNSOs.

The third conceptual issue is related to how antisocial behavior is measured and compared between JSOs and JNSOs. Loeber and Hay (1994) argued against unidimensional measures of antisocial behavior (i.e., one general measure to encompass all forms of antisocial behavior). Loeber and Hay (1994) developed a developmental pathway model of antisocial behavior, and based on this model suggested that there are three distinct types of antisocial behavior: (1) authority-conflict behavior (e.g., stubbornness, defiance, authority avoidance), (2) covert behavior (e.g., lying/deceitfulness, theft, property damage), and; (3) overt behavior (e.g., minor aggression, reactive aggression, instrumental aggression) (see also, LeBlanc & Bouthillier, 2002). This model has received considerable empirical support, particularly in regard to different developmental pathways of antisocial behavior associated with serious and violent youth (e.g.,Loeber, Farrington, Stouthamer-Loeber, & White, 2008; Loeber, Farrington, Stouthamer-Loeber, Moffitt, & Caspi, 200). Yet, Loeber and Hay’s (1994) developmental pathway model has rarely been used to examine the antisocial behavior of sex offenders (Lussier et al., 2007). Conversely, in their model, Loeber and Hay (1994) did not make any reference to sexual criminal behavior aside from rape, described as an overt antisocial behavior (Elliott, 1994; Loeber & Hay, 1994).

In their pathway model, Loeber and Hay (1994) emphasized the linear, hierarchical, and predictable manner in which different behaviors (authority conflict, covert, and overt) develop. This model can provide a framework to address Lussier et al.’s (2005) concern that prior research has not focused enough attention on the critical behavioral problems that likely distinguish sex offenders. Loeber and Hay (1994) specified that different types of offenders follow different developmental pathways of antisocial behavior, which is critical considering the documented importance of accounting for within-group heterogeneity within JSOs (Johnson and Knight, 2000; Hunter et al., 2003; Freeman et al., 2005; van Wijk et al., 2005). The within-group behavioral heterogeneity of JSOs and JNSOs must be accounted for in order to provide more reliable assertions regarding whether between-group behavioral differences of JSOs and JNSOs exist, and if so, to what degree. If these assertions can reliably be made, important theoretical and clinical implications will follow.

From a theoretical perspective, if the qualitative and quantitative nature of antisocial behavior differed between JSOs and JNSOs, then the general model’s premise that sex offending does not differ from non-sex offending is questionable. Moreover, if JSOs generally engaged in less antisocial behavior, then the general model’s premise that sex offending occurred at the endpoint of an increasingly serious criminal career (Elliott, 1994) is also questionable. The complexity of antisocial behavioral pathways (Loeber & Hay, 1994; Loeber & Stouthamer-Loeber, 1998) insinuates that the relationship between antisocial behavior and sex offending should also be complex. Thus, sex offending cannot be explained, in all cases, as a manifestation of a general antisocial tendency. Moreover, because the same type of antisocial behavior is not engaged in by all offenders, within-group heterogeneity likely exists within offenders with a general antisocial tendency. The purpose of the current study was to address antisocial behavior patterns of JSOs and JNSOs in order to add to the longstanding theoretical debate surrounding whether the development of sex offending is unique from the development of non-sex offending. From a clinical perspective, whether antisocial behavior differences can be observed between JSOs and JNSOs will be helpful for case management and treatment planning. If JSOs are more antisocial than JNSOs, treatment will need to focus on the factors that influenced the offender’s antisocial tendency in order to reduce general offending. If Seto and Lalumière’s (2010) finding that JSOs engaged in less antisocial behavior than JNSOs is supported, clinicians must consider which specific factors contributed to the youth’s sexual offence, and whether these factors place the youth at risk of future sexual and non-sexual offending.

In the current study, Loeber and Hay’s (1994) behavioral pathway model was used as a new approach to examining the diversity of early behavioral antecedents to juvenile sex offending, and identifying whether the early behavioral antecedents of JSOs differ compared to JNSOs. There are different rationales for examining behavioral antecedents. Behavioral antecedents can be seen as: (1) an orderly sequence of behaviors, progressing in severity, that unfold over time and expose individuals to different opportunities, including the opportunity for sex offending (Loeber & Hay, 1994), (2) a manifestation of a general antisocial propensity, where sex offending is one type of manifestation (Elliott, 1994; Loeber et al., 2008), (3) an influence on trajectories related to the onset, persistence, and desistence of sex offending (Lussier, van den Berg, Bijleveld, & Hendriks, 2012), and (4) a form of maladaptive behaviors which increase the probability of risk of sex offending (Lussier, et al., 2012; Knight, Ronis, & Zakireh, 2009). In the current study, Loeber and Hay’s (1994) behavioral pathway model was used to explore whether antisocial behavior pathways are more diverse and complex than what was suggested by proponents of the general model of sex offending. Using latent class analysis, we introduced the concept of behavioral profiles to unravel the heterogeneity of latent behavioral profiles related to sex offending and to understand whether these behavioral profiles between JSOs and JNSOs.

Method

Sample

The current study was based on a sample of incarcerated young offenders who were interviewed in open and secure custody facilities in British Columbia, Canada between 2005 and 2011 during the second wave of data collection as part of the [Name of Study Withheld for Blind Review]. The sample used was very specific (e.g., Canadian, incarcerated offenders, males), which could limit generalizability. For example, approximately 30% of offenders in the current study were Aboriginal, which was dissimilar from most incarcerated samples in the United States (e.g., Teplin et al., 2013). Additionally, all offenders were incarcerated at the time of their interview. As such, these offenders could have differed from other juvenile offenders who received a less severe non-custody based sentencing option (e.g., probation). The purpose of this study was to collect self-report and official file information on the risk factors associated with the onset of adolescent criminal activity and to determine the risk factor profiles associated with the development of serious and violent offending. Informed consent was provided by the British Columbia Ministry of Children and Family Development (MCFD). MCFD served as the legal guardian to all youth in custody, and their consent allowed this project to approach all youth in various custody centres throughout the province during the study period.

Youth were approached on their unit within the custody centre and asked if they wanted to participate in a research study for [Name of University Withheld for Blind Review]. Only five percent of youth declined to participate. If subjects indicated they wished to participate, research assistants (RAs) brought the subject to an isolated interview room away from their living unit, other youth, and custody staff. All subjects were read and given a copy of an information sheet explaining the purpose of the study, how information would be collected (e.g. interview and file information), and that all information would be kept confidential by law, with the exception of the subject making a direct threat against themselves or someone else. Participants were also assured that although there were no physical risks of participating in the study, some questions may touch on uncomfortable topics, such as abuse. Youth who agreed to participate in the study were asked to sign a consent form signifying that they had been read and understood the details of the study that had been provided in the information sheet.

Participants were included in the study based on three criteria (1) English-speaking; (2) demonstrated an understanding of interview questions. Youth who indicated directly (i.e., told RAs) or indirectly (i.e, RAs inferred from subject responses) that they could not understand interview questions due to their level of functioning were excluded; and (3) were willing to provide accurate information. If subjects persistently lied about known information (e.g., age, offence resulting in incarceration), then they would be permanently removed from the interview schedule. In addition to these three criteria, despite all incarcerated offenders being recruited, offenders with more serious offences were prioritized in the interview schedule (e.g. a subject in custody for an offence of murder would be prioritized over other offenders). In total, one offender was excluded because he did not speak English, four offenders were excluded because they persistently lied to research assistants and refused to give accurate information, and two offenders were excluded because they did not appear to understand the research questions.

The final sample consisted of 51 JSOs and 94 JNSOs. To be identified as a JSO, the subject had to have received an official criminal charge for a sexual offence that involved sexual contact or attempted sexual contact1. Offences such as exhibitionism were not part of the operationalization of a sexual offence. None of the JNSOs had been charged with a sexual offence, which included offences such as exhibitionism.2 A commonality between JSOs and JNSOs was that they both were considered by the courts to be serious and violent young offenders3. Thus, any differences detected between JSOs and JNSOs could not be attributed to sampling from different types of populations (e.g., community or treatment-based samples to incarcerated samples). JSOs and JNSOs were compared in Table 1 on demographic characteristics as well as risk factors from three domains: offence history, individual-oriented factors, and family background. Comparisons were made using either chi-square analyses or t-tests, depending on the variable’s level of measurement. There were no significant differences between JSOs and JNSOs within the individual-oriented and family risk factor domains. However, chi-square analyses indicated that JSOs were significantly (p < .05) more likely to be Aboriginal compared to JNSOs. JNSOs were significantly more likely have been identified as a chronic offender (at least eight prior charges) and had a significantly greater mean number of criminal charges compared to JSOs. Information pertaining to the characteristics of the sex offences, including age and gender of the victim and relationship between victim and offender were also included in Table 1. Although the most common victim-type was an extrafamilial female peer, less than 50% of the sample offended against this type of victim.

--Insert Table 1 about Here--

Procedure

Self-report information was collected through confidential one-on-one interviews between the youth and a trained research assistant at the graduate or undergraduate level. Offence history information was collected from the Corrections Network (CORNET), an integrated system used for tracking all offenders in provincial institutions within British Columbia. RAs were granted access to each subject’s case management file, which contained subjects’ pre-sentence reports and information on their behavior while in the institution. Some subjects lied about their age or the offence they were incarcerated for, and also underreported the numbers of offences they committed. RAs were trained to address these issues in a non-confrontational manner, such as by reminding the subject that their participation was voluntary and that they were welcome to refuse to answer questions that they were not comfortable with.

Measures

Subjects were interviewed using, amongst other measures the Measurement of Adolescent Social and Personal Adaptation in Quebec (MASPAQ), which has shown relatively high reliability (LeBlanc, 1997). The MASPAQ contained measures of authority conflict, covert and overt behavior. Measures of authority conflict behavior that were used in the latent class analysis included: getting in trouble for disturbing the classroom; getting in trouble for refusing to obey family rules; and, skipping school (tetrachoric ordinal alpha4 = .52). Measures of covert behavior that were used in the latent class analysis included: taking items from others; stealing from a store; getting in trouble for destroying school property; and, taking a car without permission (tetrachoric ordinal alpha = .75). Measures of overt behavior that were used in the latent class analysis included: hitting someone after being teased or threatened; fighting someone after being accidentally bumped in to; getting into a fist fight; and, forcing someone to do something they did not want to do (tetrachoric ordinal alpha = .88). The alphas are within an adequate range, especially considering the small number of items (see Cortina, 1993). The different behavioral indicators used in the latent class analysis have different levels of severity, which is consistent with Loeber and Hay’s (1994) model. Details of the behavioral indicators are provided in the Appendix.

Chi-square analyses revealed no significant (p < .05) differences when comparing the prevalence of the behavioral indicators between JSOs and JNSOs. In other words, JSOs and JNSOs were similar in the type of behavioral antecedents reported. Therefore, in Figure 1 we presented the prevalence of each behavioral indicator for the sample as a whole (n=145).Disturbing the classroom (55.9%), and getting into fist fights (53.8%) were the two most common behaviors, followed by refusing to follow rules at home (46.2%), stealing from stores (44.8%), and stealing from others (36.6%),

A number of covariates were included to examine whether the odds of membership in a particular latent class differed based on three types of offender attributes: criminal history, individual-level risk factors, and family-level risk factors (see Table 1). Criminal history was measured using all official criminal charges a youth received prior to their interview5. For this study, the type of charge was coded into one of three categories: sexual offence, violent non-sexual offence, and ‘other’. Age of onset of offending was measured based on age at first charge. Chronic offenders were offenders with at least eight criminal charges. Individual-level (physical and sexual abuse, substance use, and psychopathology) and family-level (family substance use, abuse, mental illness, and criminal record) covariates were measured through semi-structured interviews with the subject. Certain risk factors such as socioeconomic status and presence of a learning disability were not measured. As such, it could not be examined whether these factors influenced membership in a particular behavioral latent class.

Analytic Strategy

Latent class analysis (LCA) was utilized to construct behavioral profiles of offenders based on Loeber and Hay’s (1994) three pathway model of authority conflict, overt, and covert antisocial behavior. LCA is particularly appropriate when the key theoretical construct is comprised of qualitatively different groups of individuals and the construct cannot be directly measured, such as type of behavior. In LCA, the appropriate number of latent classes is determined by running successive latent class models, beginning with a one-class solution and then comparing changes in penalized log likelihood values represented by Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values (Lanza, Collins, Lemmon & Schaefer, 2007). This technique assigns individuals to mutually exclusive and exhaustive (non-overlapping) latent classes, which represent the underlying construct. In the current study, the authority conflict, covert and overt behavioral types represented latent constructs and were measured by the behavioral indicators that were considered manifestations of each construct. In the current study, each of the eleven behavioral indicators mentioned above were entered into the LCA.

Not all subjects in the current study were of the same age (age ranged from 12-19). We avoided violating LCA’s assumption of local independence (i.e., within a particular latent class, observations for a particular variable must be independent) (see Collins & Lanza, 2010) by setting an age cut-off for the behavioral indicators; otherwise, older individuals, by virtue of having had a longer timeframe to engage in such behavior, would have appeared to have more severe antisocial behavior profiles. In addition, Loeber and Stouthamer-Loeber (1996) found that antisocial behavior patterns of younger offenders differed from older offenders, so it was important that the age differences were controlled for when antisocial behavior profiles were compared. Additionally, developmental theorists have noted that the onset of antisocial behavior needed to be investigated earlier than adolescence in order to identify those most at risk of becoming chronic offenders (e.g., Moffitt, 1993; Cale et al., 2009). Therefore, from a methodological perspective and a theoretical perspective, it was important that only behavior engaged in prior to age 12 was coded. Analyses were conducted using PROC LCA 1.2.6 for SAS 9.3. PROC LCA allowed for the specification of a grouping variable, which was used to measure whether the qualitative meanings of the latent classes differ across levels6 of group membership (Lanza et al., 2007). . In the current study, the grouping variable was a dichotomous measure of whether or not the youth has been charged with a sexual offence.

Results

Identification of Behavioral Pathways

The first step conducted for the LCA involved identifying the number of latent classes which best fit the data on the eleven behavioral indicators (n = 145). First, a baseline model was fitted to the full sample of juvenile offenders. AIC values indicated a three class solution best fit the data, whereas BIC values indicated a two class solution (See Table 2). Bootstrapping confirmed that the three class solution significantly improved model fit over a two class solution. Moreover, in the three class solution, G² values were less than the model’s degrees of freedom, which is an indication of good model fit (Laska, Pasch, Lust, Story, Ehlinger, 2009). Further, with an entropy value of 0.83, the model indicated good classification accuracy based on Lanza and colleagues’ (2007) ranking of entropy values. In other words, the LCA suggested that the behaviors of the full sample of juvenile offenders were best represented by the presence of three behavioral pathways. In the next step, the meanings of each latent class were interpreted.

--Insert Table 2 about Here--

Interpreting the meanings of the latent classes required an examination of item-response probabilities for each of the latent classes (or behavioral pathways) found. Item-response probabilities indicated the probability that an individual within each latent class engaged in a specific behavior. Based on the pattern of item-response probabilities in each of the three latent classes found, the different patterns of antisocial behavior were named Low Antisocial (50% of the sample), Primarily Overt (hereinafter Overt) (27% of the sample) and Primarily Covert (hereinafter Covert) (23% of the sample) (Figure 1). Offenders in the Low Antisocial group had low item response probabilities for each type of antisocial behavior (most item responses < .20) for each type of antisocial behavior included in the analyses. The highest item response probability found for this group was disturbing the classroom, albeit the item response was relatively low (<.30).

Offenders in the Overt latent class had the highest probability of having engaged in aggressive or violent behavior such as fist fights (.98), getting angry and hitting someone (.71), and hitting someone because of being teased (.60). Overt offenders were in the group with the highest probabilities of having committed various forms of authority conflict behavior, particularly disturbing the classroom (.80). The behavior Overt offenders were least likely to have engaged in were from the covert domain. Here, the probabilities were all lower than 0.5. For offenders in the Covert group, covert forms of behavior were most common, and included theft from a store (.98) and theft from other people (.92). Covert offenders also had a high probability of having been in a fist fight (.81), disturbing the classroom (.76) and refusing to follow house rules (.65). All three groups had low probabilities of using force to dominate others and stealing a car, which were considered the most serious forms of overt and covert antisocial behavior. Overt offenders had the highest probabilities of using force to dominate others (.30) and stealing a car .11). It could not be determined from the baseline (a) whether JSOs fit just one of these behavioral patterns, indicating that within-group heterogeneity of behavior did not exist for JSOs, and (b) whether the behavioral patterns differed for JSOs when compared to JNSOs. We examined these two questions in the next section.

--Insert Figure 1 about Here--

Differences between JSOs and JNSOs

In order to describe the association between behavioral pathways and juvenile offender type, we first compared the proportion of JSO and JNSO in each of the three behavioral pathways found (Figure 2). Comparisons were made using t-tests; none of the tests were statistically significant. The Low Antisocial group was the most prevalent behavioral pathway and represented about 50% of the sample for both JSOs and JNSOs. The other half of the sample of JSOs and JNSOs was almost evenly split between the Overt and the Covert group. Hence, the prevalence of JSOs and JSNOs was relatively similar across the three latent classes found, which suggested much similarity in the developmental antecedents between the two groups. When the baseline model was examined further for each of the latent classes, no significant differences were found in the average classification accuracy of JSOs and JNSOs (Figure 2). However, it was possible that the baseline model had constrained differences in the behavioral patterns of JSOs and JNSOs, and so offender type was included as a grouping variable so that patterns of behavior could be examined separately for JSOs and JNSOs.

--Insert Figure 2 about Here--

Offender Type as a Grouping Variable

Offender type was used a grouping variable so that we could examine whether item-response probabilities (i.e., behavioral patterns) differed between JSOs and JNSOs. LCA was run using a measurement invariance test7 and we then examined whether the early antisocial behavior patterns of JSOs are qualitatively different from JNSOs. The measurement invariance test used a chi-square analysis that compared two models: (1) A model that assumed near identical item-response probabilities for JSOs and JNSOs (the measurement invariant model), and (2) a freely estimated model that allowed the item-response probabilities within a latent class to be measured separately for JSOs and JNSOs. If the comparison between the two models yielded no significant differences in model fit, we could conclude that the latent classes found are the same for JSOs and JNSOs. Despite the small ratio of JSOs to behavioral items (51/11), the result of this test still indicated significant differences in the item-response probabilities of JSOs compared to JNSOs (χ² [33] = 55, p < .001), which indicated that JSOs and JNSOs are characterized by different behavioral pathways. In addition, the PROC LCA outpost procedure provided average posterior probabilities for each latent class for JSOs and JNSOs, which indicated that the model averaged excellent classification accuracy (0.96) for both JSOs and JNSOs.

Antisocial Pathways and Developmental Covariates

The behavioral antecedent latent classes were examined again to confirm that the item-response probability differences that were identified between JSOs and JNSOs could not be attributed to some other individual characteristic. This step was necessary considering that JSOs and JNSOs included in the sample differed on individual factors, particularly offence history (see Table 1). Multinomial logistic regression was used to identify whether certain factors predicted membership in one of the three latent class identified by the baseline model (n = 145). In each analysis, for the computation of odds ratios, the Low Antisocial group was used as the reference category to which the Covert and Overt groups were compared to (see Table 3). First, offender type (JSO/JNSO) was included as a covariate and revealed no significant differences (p < .05), meaning that the odds of being in a particular latent class did not differ between JSOs and JNSOs8. Second, age and ethnicity were examined, controlling for offender type, and revealed a non-significant (p < .05) finding. Being of a certain age or ethnicity had no bearing on membership in a particular latent class, and this was evident for both JSOs and JNSOs.

Three domains of developmental covariates were also examined: (1) offending history, (2) individual-oriented factors, and (3) family factors (Table 3). Within offending history, age of onset of offending (i.e. age at first charge), total number of charges, and whether the individual was defined as a ‘chronic’ offender were all significantly (p < .05) related to the early antisocial (Overt and Covert) behavioral patterns. When offending history was controlled for, offender type (JSO/JNSO) was no longer significant, which suggested that the different latent classes found were more reflective of criminal history than being a JSO or JNSO. Specifically, individuals with a greater number of charges, an earlier age of onset of offending, and being identified as a chronic offender were more likely to be associated with the Covert group and the Overt group compared to the Low Antisocial Group.

Within the individual-oriented risk factor domain, physical abuse, sexual abuse, sexual behavior at school, and self-reported behavioral disorder (i.e. ADHD, oppositional defiant disorder, conduct disorder) were all significantly (p < .05) related to the early antisocial behavioral pattern latent classes. When adjusting for individual-oriented risk factors, offender type was no longer significant, which suggested that the different latent classes found were more reflective of individual-oriented risk factors than being a JSO or JNSO. Specifically, individuals who had been physically abused, sexually abused, in trouble at school for sexual behavior, and who self-reported having a behavioral disorder were more likely to be associated with the Covert group and the Overt group compared to the Low Antisocial Group.

For the family history domain of risk factors, all factors were significantly (p < .05) related to the early antisocial behavioral patterns based on latent class. Adjusting for these family-based factors indicated that offender type was not significant, which suggested that the different latent classes were more reflective of family-oriented factors than being a JSO or JNSO. Family factors, including abuse, substance use, criminal record, and mental illness were more prevalent in the Covert and the Overt groups compared to the Low Antisocial Group.

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Discussion

We examined whether the antisocial behavioral patterns of JSOs were heterogeneous and whether the behavioral patterns of JSOs differed from JNSOs. In doing so, three conceptual issues in the sex offender literature were addressed. First, contrasting with previous studies (e.g., Seto and Lalumière, 2010), to better understand antecedents to sexual offending, only behaviors that occurred prior to the onset of the subject’s sexual offence were considered. Second, to address the long-standing issue of JSO within-group heterogeneity (Barbaree et al., 1993; Johnson & Knight, 2000; Hunter et al., 2003; Freeman, et al., 2005; Seto & Lalumière, 2010; Smith et al., 1987; van Wijk et al., 2005b; Worling, 2001) and JNSO within-group heterogeneity (Loeber & Stouthamer-Loeber, 1998 heterogeneity of antisocial behavior among both JSOs and JNSOs was examined. Said differently, because it was expected that offenders in general would differ in the nature and frequency of behavioral antecedents, LCA was used in order to determine if there were mutually exclusive categories of behavioral antecedents. Third, to address issues associated with reliance on unidimensional measures of antisocial behavior (e.g., one general measure of all forms of antisocial behavior), LCA was used to examine behavioral patterns based on authority conflict, covert, and overt antisocial behavior used with a general sample of juvenile offenders. The results of the LCA indicated that the behavioral patterns of JSOs do not differ from JSOs even when traditional correlates of sexual offending such as abuse are accounted for.

The study findings indicated the presence of multiple antisocial behavioral pathways in a sample of JSOs that mirrored those of JNSOs. This finding was not congruent with the general conclusion of Seto and Lalumière’s (2010) findings that JSO are less antisocial than JNSOs. An explanation for the different findings may be because the Seto and Lalumière (2010) study included both incarcerated/residential samples and community-based samples whereas the current study included only incarcerated offenders. In effect, our study compared JSOs and JNSOs from the same population (incarcerated offenders) whereas Seto and Lalumière (2010) compared JSOs from different populations (i.e., clinical samples and incarcerated samples) to JNSOs primarily from incarcerated samples. Studies in Seto and Lalumière’s (2010) meta-analysis did not include JNSOs from community samples, which might explain why characteristics such as antisocial behavior were more prominent amongst JNSOs than JSOs. The findings from the current study also contrasted with Becker’s (1999) and Butler and Seto’s (2002) research that identified the presence of a single antisocial pathway among JSOs and is consistent with Lussier et al.’s (2012) multiple antisocial trajectories associated with juvenile sexual offending. Lussier et al. (2012) study, however, did not examine overt and covert manifestations. It is important to re-emphasize that findings from the current study may contrast with other studies because of the specificity of the sample (Canadian male incarcerated offenders).

Based on the results from the current study it was inferred that offenders can be distinguished based on their pattern of covert or overt behavior and that these different behavioral patterns could be distinguished by different risk factors. Loeber et al. (1993) noted that individuals who engaged in multiple forms of antisocial behavior were the most frequent offenders. Similarly, in the current study, Covert and Overt groups were more frequent offenders and their offending began earlier relative to the Low Antisocial group. The nature of the Overt and Covert groups’ criminal behavior suggests that their offending represented a continuation and escalation from early antisocial behavior. Within the family domain, both Overt and Covert individuals were more likely than the Low Antisocial group to have family members who: had a criminal record, had been abused, abused drugs or alcohol, and had a mental illness. These results were similar to Gorman-Smith and Loeber’s (2005) study on family normlessness in aggressive youth where the authors examined specific family-based factors such as abuse and criminal offending. Based on the current study, similar family issues exist for both JSOs and JNSOs. In the individual-oriented domain, the Covert and Overt groups were more likely to have experienced physical and sexual abuse, exhibit sexual behavior problems, and report having been diagnosed with a behavioral disorder. Youth with comorbid symptoms of ADHD and conduct disorder are those most likely to engage in sex crimes and persist with their antisocial behavior in adulthood (Lussier, Blokland, Mathesius, Pardini & Loeber, in press; Loeber, Keenan, & Zhang, 1997). The different behavioral patterns and their associated offender characteristics from the three domains of covariates are possibly related to the modus operandi of an individual’s sexual offence.

Latent Class Type and Sexual Offence Characteristics

Elliott (1994) argued that drug use, robberies and assaults preceded more serious criminal offences (i.e., rape). Part of the explanation for this escalating pattern is that individuals who display a pattern of engaging in a specific type of behavior will subsequently be exposed to expanded opportunities for serious antisocial and criminal behavior (Loeber & Hay, 1994). For example, an individual who earns a reputation for schoolyard fights may be befriended by similar minded individuals who actively seek situations that call for aggressive behavior. In other words, the antisocial potential, whether covert or overt, will likely manifest itself differently in different social contexts, including sexual contexts. Thus, based on results from the current study, the observed behavioral patterns of JSOs may be reflective of their sexual offence. Hayh

For both Overt and Covert antisocial pathway groups, their sexual offences can be considered as one stage or point in a continuing and escalating pattern of antisocial behavior (e.g., Elliott, 1994; Butler & Seto, 2002). In the Overt group, for example, JSOs appeared to engage in sexual offending that as part of an escalating pattern of aggressive and violent behavior. In effect, the recurrent pattern of aggressive antisocial and criminal behavior more likely exposed the Overt group to different opportunities for sexual offending. For example, overt offenders had previously demonstrated that they would use violence when met with resistance (e.g., Overt JSOs were likely to hit someone who had teased them). Furthermore, the Overt group had the highest probability of having dominated someone using physical force to get what they wanted. Although their sexual offence appears distinctive, it represents a more common characteristic of a longstanding (i.e., before age twelve) pattern of antisocial aggressive and domineering behavior.

The common types of behavior engaged in by Covert JSOs required deception and detection avoidance for success. For example, an offender who is caught for theft will be forced to return the stolen goods; therefore, an offender will typically only benefit by avoiding apprehension. Sexual offending for this group reflects a well concealed and deceitful pattern of antisocial behavior. This pattern possibly includes identifying vulnerable victims less likely to report their victimization (e.g., children, a mentally disabled child, children under their authority/supervision while babysitting, or others who are less likely to be aware that the offender’s sexual actions are wrong). Another potential target for the Covert group could be individuals who are severely intoxicated, and, thus unable either to defend themselves or accurately recall the offence. For Covert JSOs, using traditional victim characteristics such as gender to account for JSO within-group differences (e.g., Ford & Linney, 1995; Seto & Lalumière, 2010) may not be as useful as accounting for situational characteristics such as whether the victim was intoxicated or in an isolated area. In other words, Covert JSOs may be opportunistic in their sexual offending, targeting victims based on the likelihood of avoiding detection.

The development of juvenile sexual offending though cannot be explained entirely by “antisocial” covert and overt JSO types (e.g., Becker, 1998; Butler & Seto, 2002; Elliott, 1994; Lussier et al., 2012). Half of JSOs in this sample did not engage in early antisocial behavior (the Low Antisocial group). This result is congruent with descriptive studies (e.g., Frances & Hudson, 1993; Seto & Lalumiere, 2006) and is reminiscent of the non-recidivist group described by Becker (1999). The Low Antisocial group is consistent with Lussier et al.’s (2012) finding that most JSOs are characterized by a delinquency pattern that is occasional and limited to the period of adolescence.

Clinical Implications

Arguably, the offenders in the current study are the types of offenders that are most in need of intervention and treatment due to their serious and extensive offence histories (see Table 1). Although JSOs are unlikely to sexually recidivate (Caldwell, 2002; McCann & Lussier, 2008), it is still important for incarcerated male JSOs to receive treatment/intervention. JSOs in the current sample were characterized by several risk factors that placed them at a risk for future general offending. It was especially evident for JSOs in the Covert and Overt latent classes that these individuals were characterized a prior pattern of antisocial behavior that has been present at an early age and was related to future chronic and violent offending. Correction of these behavioral problems likely requires treatment/intervention that targets the multitude of underlying risk factors that has increased the likelihood of these offenders being involved in future offending. Many of the risk factors present in these offenders were related to their belonging to a disruptive and chaotic family environment. Therefore, as Letourneau et al. (2009) suggested, treatment of JSOs should involve members of their family since the family environment may be counterproductive to treatment if not dealt in conjunction with other individual-oriented risk factors that have impacted the offender’s lifestyle. In effect, dealing with the early antisocial behavioral patterns of JSOs by addressing individual and family-based risk factors may be an effective method of preventing both sex offending and general offending.

Limitations and Future Research

This was the first study related to latent class profiles of behavioral antecedents of JSOs, and results should be interpreted as such. Of importance, the study included a sample of JNSOs for comparison purposes. The current study was based on a sample of incarcerated young offenders in Canada with a high proportion of Aboriginal offenders (28.3%). Although this meant that results should not be generalized to community-based samples, it also meant that the differences that were detected could not be attributable to the sampling of offenders from different populations. For example, differences between community and custody populations would be expected because custody populations have a more serious group of offenders. The current study was also based on retrospective longitudinal data rather than prospective longitudinal data. As such retrospective longitudinal data may suffer from memory biases, although strategies were taken to minimize such biases (using a versatility scale rather than measuring frequency of the behavior). However, the exploratory nature of the study warranted the use of such data before prospective longitudinal data becomes available. Also, the method selected allowed for more direct comparison with prior studies on the topic.

Separating JSOs based on victim selection has been commonly used to address within-group heterogeneity (e.g., Hunter et al., 2004; Richardson et al., 1997; Smith et al., 1987; Worling, 2001). However, within the context of research on behavioral pathways of JSOs, studies have not separated JSOs based on victim selection nor type of offender, such as in Butler and Seto’s (2002) sex-only and sex-plus groups. The current study did not make these distinctions because of the small sample size. It would be particularly valuable to do this with longitudinal data so that the escalation, persistence, and desistence of antisocial behavior pathways could be examined. For example, Lussier et al. (2012) found that JSOs tend to follow five non-sexual offending and two sexual offending trajectories. It would be worthwhile to examine whether early antisocial behavior pathways are correlated with later offending trajectories. To date, Loeber and Hay’s (1994) authority conflict, covert, and overt behavioral types have not been examined within the context of JSOs. As such, the current study should be considered exploratory. The small sample size also meant that there was the possibility that the results were sample specific. However, other exploratory studies using latent class analysis have been conducted with a similarly sample ratio of subjects to variables (e.g., Deslauriers-Varin & Beauregard, 2010). Finally, the research ethics board prohibited question that included measures of sexually deviant behavior. It would be valuable for future research to examine how atypical sexual behaviors fit within the context of Loeber and Hay’s (1994) model.

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Figure 1. Prevalence of each behavioral indicator examined in the latent class analyses

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Figure 2. Three-class solution of behavioral patterns of juvenile offenders (n=145)

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Figure 3. Average assignment probabilities based on the posterior probability of the baseline model

Appendix