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Childhood Victimization and Poly-Victimization of Online Sexual Offenders: A Developmental Psychopathology Perspective

Published onMay 10, 2022
Childhood Victimization and Poly-Victimization of Online Sexual Offenders: A Developmental Psychopathology Perspective
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Abstract

Background: Research on childhood victimization of individuals involved in online sexual offending during adulthood is scarce. Studies focusing on adverse childhood of individuals involved in offline child abuse suggested that childhood trauma was associated with an increased probability of sexual offending during adulthood.

Objective: The purpose of this study is to explore the role that childhood victimization may have in the development of risk factors that increase the likelihood of being involved in online sexual offending

Participants: This comparative study analyzed the characteristics of 127 individuals involved in online sexual offending who did not experience childhood victimization and 77 individuals involved in online sexual offending who experienced childhood victimization.

Methods: Bivariate and regression analyses were conducted to identify variables associated with the presence of victimization and polyvictimization during childhood. Next, structural equation modeling analysis was used to identify the direct and indirect relationships between childhood (poly)victimization and the development of risk factors.

Results: Results showed that individuals who experienced childhood victimization presented different risk factors and cognitions compared to those who did not. Depending on the type of victimization experienced, criminogenic cognitions, antisocial behaviors, and sexual interests for children were more likely to be developed.

Conclusions: For individuals involved in online sexual offending during adulthood, childhood abuse is directly associated with the development of offense-supportive cognitions, substance abuse, and youth engagement in sexual offending, while sexual interests for children and sense of loneliness are indirect consequences of childhood trauma.

Introduction

Developmental victimology is the area of study related to childhood victimization and its consequences over the life course of individuals (Finkelhor, 2007). The concept of childhood victimization contributing to criminal involvement during adulthood is now well-documented in criminology (Weeks & Widom, 1998). This phenomenon, known as “victim to victimizer” (see Ryan, 1989), is one of the few accepted notions in criminology (Miley et al., 2020). Several empirical studies have established a causality link between childhood trauma and a higher risk of offending behavior during adolescence and adulthood (Broidy et al., 2006; Jennings et al., 2010). Comparisons between the general population and incarcerated individuals have shown that a significant proportion of sexual offenders experienced victimization during childhood (between 20% to 70%, see Levenson & Socia, 2016; Weeks & Widom, 1998). Other studies have shown that certain risk factors associated with offline sexual offending are associated with childhood victimization (e.g., pedophilic sexual interests, substance abuse, antisocial behaviors, see Blank et al., 2018; Craissati et al., 2002; Freund et al., 1990; Miley et al., 2020; Nunes et al., 2013; Widom et al., 2006).

Although there are a plethora of studies examining individuals involved in offline sexual offending, studies investigating online sexual crimes are scarce (Alanko et al., 2017; Babchishin et al., 2011; Webb et al., 2007). Studies have found that both individuals involved in online and offline sexual offending against children reported higher rates of childhood victimization and polyvictimization than the general population (Babchishin et al., 2015; Babchishin et al., 2011). Nevertheless, previous research also highlighted that these two types of sexual offenders presented several differences (Babchishin et al., 2015; Babchishin et al., 2011) and that consequently it was not appropriate to apply the knowledge about individuals involved in offline crimes on those who act on the Internet. Based on this finding, it is of utmost importance to develop specific knowledge to further unpack the causal mechanisms that connect childhood victimization with the development of risk factors associated with the commission of online sex crimes. Given the lack of knowledge on the topic, this study is relevant in terms of improving our understanding of online sexual offending and to allow clinicians to implement victim assistance. This could also lead to more accurate intervention strategies when considering specificities induced by childhood victimization.

Developmental Psychopathology Theoretical Framework

The theory of developmental psychopathology proposes a conceptual framework to explain the association between negative experiences during the early stages of human development and the emergence of subsequent disorders. This theoretical framework has been applied in criminology as an explanatory model for the links between childhood abuse and subsequent disorders that may lead to an increased likelihood of engaging in criminal activity (Cicchetti & Banny, 2014; Levenson & Socia, 2016). This theoretical approach suggests that positive and negative experiences affect the dynamic interactions between affective and cognitive processing that shape the behavioral adaptation patterns of individuals (Rutter & Sroufe, 2000). The development of individuals is perceived here as a succession of stages, including competences acquired on the basis of negative and positive experiences. Each stage of development includes a set of competences that will irremediably condition the acquisition of competences in the next stage of development. When the normal acquisition of competences is disrupted by the occurrence of negative experiences, the developmental process will be affected, resulting in maladaptive behaviors in individuals (Cicchetti & Banny, 2014; Rutter & Sroufe, 2000).

In light of this perspective, studies have identified childhood abuse and maltreatment to be significant factors increasing the likelihood of adaptive functioning of individuals over their lifetime (Cicchetti & Banny, 2014). These negative childhood experiences increased the risk of developing psychopathological disorders. Specifically, these traumatic events exacerbated the development of maladaptive cognitive patterns, relational disorders, antisocial behaviors, emotional dysregulation, and sexual disorders, all of which are risk factors that increased the likelihood of engaging in crime (Cicchetti & Banny, 2014).

It is important to note that this theoretical framework is based on probabilistic patterns and that not all children who have been victimized will develop the above-mentioned predicaments. In efforts to address the trauma-disorders overlap issues, Cicchetti and Banny (2014) incorporated the concepts of multifinality (i.e., the same pathway leading to several outcomes) and equifinality (i.e., several pathways leading to the same outcome). The inclusion of these concepts in psychopathological developmental theory implies that external factors (e.g., adapted victim assistance) can address maladaptive learning patterns. Similarly, childhood trauma is not the only factor related to the development of criminal problems.

Childhood (Poly-)Victimization and Sexual Offending

Childhood victimization has been found to be associated with an increased in probability of sexual offending during adulthood. Previous studies have reported that childhood victimization rates were significantly higher among incarcerated individuals than the general population (Dierkhising et al., 2013; Levenson et al., 2014). This finding led to the hypothesis suggesting that individuals who have had traumatic experiences in their childhood were more likely to be involved in sexual offending, particularly sexual abuse against children (Abbiati et al., 2014; Davis et al., 2012; Drury et al., 2019; Krahé & Berger, 2017; Lee et al., 2002; Miley et al., 2020; Whitaker et al., 2008).

The different types of abuse that have been studied were often divided into three categories: sexual, physical, and psychological victimization (e.g., Abbiati et al., 2014; Cicchetti & Banny, 2014). Although these forms of victimization have been found to be associated with future sexual offending, sexual victimization has been identified to be the most significant childhood trauma in predicting engagement in future sexual delinquency as well as the development of sexual disorders (Burton, 2003; DeLisi et al., 2017; DeLisi et al., 2014; Drury et al., 2019; Jespersen et al., 2009; Lewis et al., 2007; Papalia et al., 2020). It is important to note that depending on the type of data used (i.e., cross-sectional vs. longitudinal data), the results may vary. The cross-sectional data showed a specific association for childhood sexual victimization (e.g., Jespersen et al., 2009; Miley et al., 2020) while the longitudinal data did not suggest a specific association to sexual victimization (e.g., Widom et al., 2006). Moreover, some studies (Howell et al., 2017; Widom & Massey, 2015) found that physical abuse and neglect were better predictors than sexual victimization. While the existence of discrepancies in results should obviously be considered, they may be due to differences in the distribution of types of victimization in the samples used (Widom & Massey, 2015).

Finkelhor and colleagues (Finkelhor et al., 2007, 2009; Finkelhor et al., 2011) examined the role of polyvictimization (i.e., refers to the experience of multiple types of victimization, see Finkelhor et al., 2007) and found that the accumulation of different types of victimization had a major negative impact on individuals’ social and psychological development. Recent studies have corroborated this finding by establishing an explicit link between polyvictimization and engagement in sexual offending. These studies found that polyvictimization during childhood was a risk factor for engaging in severe sexual offending later in life (Casey et al., 2009; King et al., 2019; Leach et al., 2016; Thibodeau et al., 2017).

Several studies have identified relationships between the development of risk factors associated with sexual offending and childhood victimization. For instance, individuals involved in offline sexual offending who experienced childhood victimization were more likely to be diagnosed with pedophilia and to have sexual interests in children (Craissati et al., 2002; Freund & Kuban, 1994; Freund et al., 1990; Lee et al., 2002; Nunes et al., 2013). Relational disorders, as well as alcohol/drug abuse, have also been frequently observed among sexual offenders who experienced childhood victimization (Cicchetti & Banny, 2014; Johnson & Knight, 2000; Marini et al., 2014; Sable et al., 2006; Widom et al., 2006). Furthermore, studies have identified relationships between childhood victimization and cognitions supportive of sexual offending (Blank et al., 2018; Craissati et al., 2002; Kenny et al., 2001; Marziano et al., 2006). In a recent study involving incarcerated individuals, Blank et al. (2018) found that individuals who experienced childhood sexual victimization were more likely to have emotional congruence with children.

Childhood Victimization and Individuals Involved in Online Sexual Offending

Two empirical studies and one meta-analysis have examined childhood victimization of individuals involved in online sexual crimes. In these studies, online sexual offenders were compared to groups of individuals involved in offline sexual offending against children or to the general population. Webb et al. (2007) compared 90 men who used online child sexual exploitation material (CSEM) with men who engaged in contact sexual offenses against children. The results showed that both groups had a relatively high prevalence rate of childhood victimization. However, the findings indicated that individuals involved in online sexual crimes were less likely to be physically victimized (Webb et al., 2007). In the meta-analysis published by Babchishin et al. (2011), results showed lower rates of physical childhood victimization among online offenders compared to offline offenders. Further, the authors found that offenders involved in online crimes experienced more sexual and physical victimization during childhood compared to the general population. In a comparative study between groups of individuals involved in child abuses, CSEM, and a combination of both offenses (i.e., mixed), results showed that the mixed group reported the highest prevalence of childhood sexual victimization (59%), followed by those involved in offline child sexual assault (20%), and finally those involved in CSEM (11%) (Alanko et al., 2017)

Aim of the Study

There is current evidence showing that childhood victimization contributes to the development of risk factors associated with offline sexual offending. However, to date, no studies have examined the relationship for individuals involved in online sexual offending against children. We believe that in order to improve the understanding of online sexual offending and to provide tailored responses for professionals and clinicians, it is important to explore the role that childhood victimization may have in the development of risk factors that may affect the likelihood of being involved in online sexual offending. Understanding the different mechanisms underlying these risk factors could lead to a better understanding of individuals involved in this type of offending, improve the management of children experiencing abuse, and prevent children from developing these risk factors. Based on the literature review, three exploratory hypotheses were formulated for this study:

H1. Childhood victimization increases the likelihood of development of criminogenic cognitions and behaviors associated with online sexual offending against children.

H2. Childhood polyvictimization increases the likelihood of development of criminogenic cognitions and behaviors associated with online sexual offending against children.

H3. Childhood victimization increases directly and indirectly the likelihood of development of criminogenic cognitions and behaviors associated online sexual offending against children.

Methodology

Sample

The sample in this study consisted of 199 men involved in online sexual offenses that occurred in Canada between 2001 and 2020. Specifically, these men were involved in the use of online CSEM and/or child luring (i.e., online sexual solicitation of minors). A coding manual was created to adequately collect and compile the information. To ensure conceptual and content validity (Nunnally & Bernstein, 1994), the conceptualization and operationalization of the variables were reviewed both by the authors and external experts in the field of forensic psychology. In order to compile data from police files and offender interviews for the database, research assistants were trained to use the coding manual. Considering the length of many of the interviews available for coding (i.e., 4–5 hours on average), a subsample (n = 9 cases) was coded by two research assistants for inter-judge reliability. The overall agreement on the coding of the variables measured in the cases reached 84%. The information contained in the database included offender characteristics (i.e., sociodemographic, criminal history, childhood and adolescent victimization, sexual component, relational component, emotional component, antisocial component, cognitive component), crime characteristics (i.e., crime process), and victimological aspects (i.e., victim and victimization characteristics).

This database has been used in recent studies relating to CSEM and/or child luring (Chopin et al., 2022; Paquette & Fortin, 2021a, 2021b).

Measures

Response Variable. The response variables used in this research were related to childhood victimization and polyvictimization. A history of childhood victimization referred to any physical, sexual, or psychological violence experienced during childhood (i.e., less than 12 years old) committed by a family member (e.g., parent, step-parent, sibling), peer (e.g., schoolmate), acquaintance (e.g., teacher, neighbor), or stranger. Specifically, the presence of physical victimization was defined as a deliberate use of force against an individual without his consent, which may have caused physical pain or injury. The presence of sexual victimization referred to any sexual touching, activity, or intercourse. Finally, the presence of psychological victimization referred to the use of words or actions to control, frighten, isolate, or take away someone’s dignity, including threatening, belittling, name calling, or insulting; constantly yelling at or criticizing someone; preventing them from seeing family or friends; destroying property, hurting pets, or threatening to do so; and intimidating or humiliating.

Several response variables were used in this study (see Table 1). Three dichotomous variables (0 = absence, 1 = presence) described the presence of childhood sexual victimization, childhood physical victimization, and childhood psychological victimization. Two additional variables were computed based on these three dichotomous variables. The first was a dichotomous variable which measured whether at least one form of childhood victimization was experienced by individuals included in the research sample, with 0 indicating the absence of childhood victimization experience, and 1 indicating the presence of at least one type of childhood victimization (i.e., sexual, physical, or psychological). The second was a continuous variable which measured the number of different types of childhood victimizations experienced by each individual (x̄ = 0.55, SD = 0.84, range = 0–3).

Explanatory Variables. A set of explanatory variables was used to control the relationship between childhood victimization and socio-demographic characteristics which include: 1) offender had a legal occupation (i.e., employment or was studying) and 2) offender was single (i.e., at the time of the offense). The sample used in this research included both individuals involved in online child luring offenses and/or CSEM. In order to determine whether child sexual victimization may affect the type of offending, we included two variables: 3) offender was involved in CSEM use and 4) offender was involved in child luring.

Previous studies have found that childhood victimization increased the risk of an individual’s criminal career (Levenson & Socia, 2016; Miley et al., 2020). In order to test this assumption, we included the following dichotomous variable: 5) offender was convicted of sex crimes during adolescence (i.e., before 18 years old).

Previous studies have found that childhood victimization may be associated with deviant sexual interests, relational difficulties, and antisocial behaviors (Levenson & Socia, 2016; Levenson et al., 2014; Nunes et al., 2013). Such risk factors have also been identified among individuals involved in online sexual offending against children (Babchishin et al., 2015; Howitt & Sheldon, 2007). We used four dichotomous variables to test these aspects: 6) exhibited pedo/hebephilic sexual interests (i.e., based on previous diagnoses of pedophilia or hebephilia or admission of specific sexual interest in children or adolescents), 7) substance abuse (i.e., drug or alcohol use reported by the offender as abusive, related to the commission of criminal offenses, or leading to therapeutic support group membership), 8) relational difficulties (i.e., offender reported having difficulties with intimate relationships), and 9) sense of loneliness (i.e., offender reported experiencing a feeling of loneliness, being surrounded by few or no significant people, avoiding social situations, or feeling rejected by others).

Offense-supportive cognitions have also been examined in childhood victimization studies (Blank et al., 2018; Craissati et al., 2002; Kenny et al., 2001; Marziano et al., 2006). Specifically, men who engaged in online sexual offending against children exhibited cognitions supportive of their online behaviors (Paquette & Cortoni, 2020). To examine these cognitions, seven dichotomous variables were added: 10) the world is dangerous (i.e., cognitions suggesting that the offline world is a hostile place where people exploit others), 11) the world is uncontrollable (i.e., cognitions suggestive of the idea that offenders are unable to control themselves offline), 12) the sexualization of children (i.e., cognitions suggesting that children are sexual beings able to provide sexual consent and that sexual activities are beneficial to them), 13) children are life partners (i.e., cognitions supporting the idea that children are friends, lovers, and/or partners), 14) entitlement (i.e., cognitions supportive of the illusion that some have the right to use child sexual exploitation material or engage in sexual communication with adolescents with impunity), 15) the virtual is not real (i.e., cognitions supporting the idea that the internet does not represent reality and that its content cannot be known or real), and 16) internet is uncontrollable (i.e., cognitions suggestive of the idea that offenders are unable to control themselves on and offline).

Analytical Strategy

The objective of this study was to examine the relationships between childhood victimization and the development of different risk factors present in a sample of men involved in online sexual offending against children during adulthood. First, a bivariate comparison (i.e., chi-squared) between the set of explanatory variables (i.e., risk factors) and the presence of childhood victimization was conducted. Second, a series of logistic regression analyses and a multiple linear regression analysis were performed. The logistic regression models were used to determine the relationship between the presence of physical (Model 1), sexual (Model 2), psychological (Model 3), and any childhood victimization (Model 4), and explanatory factors. Multiple linear regression analysis was used to determine whether the number of different childhood victimizations (i.e., polyvictimization) was associated with dependent variables at the multivariate level.

The regression method is often used for two main analyses: prediction and causal (Allison, 1999). In a prediction study, the goal is to develop a formula for making predictions about the response variable based on the observed values of the explanatory variables. For causal analysis, the explanatory variables are assumed to be causes of the response variable. Causal analysis was used in this study, in which childhood victimization variables represented the cause of explanatory variables. The regression models were estimated with explanatory variables that were significant at the bivariate level (p ≤ 0.05). As suggested by several references in statistics (Hosmer & Lemeshow, 2013; Tabachnick & Fidell, 2019), performing multivariate analyses is not recommended when bivariate analyses indicate that there is no relationship between two variables. If a significant relationship is observed at the multivariate level despite the absence of a significant relationship at the bivariate level, it is likely due to interaction effects with other variables. Finally, an exploratory structural equation model (SEM) was used to determine the direct and indirect associations between childhood victimization and the variables of interest. This exploratory model aimed to test the application of the developmental psychopathology theory to individuals involved in online sexual crimes. Specifically, the goal was to determine whether the childhood victimization was associated with the development of offense-supportive cognitions which would have shaped illegal behaviors. Standardized path coefficients (β) for both the direct and indirect effects were estimated using 2000 bootstrap samples. Goodness of fit was assessed with the maximum likelihood chi-squared statistic, the Tucker Lewis index (TLI), the goodness of fit index (GFI), the adjusted goodness of fit index (AGFI), the comparative fit index (CFI), the root mean square error of approximation (RMSEA), the root mean square residual (RMSR), and the relative fit index (RFI) (Bentler, 1990; Hu & Bentler, 1999).

For the multiple linear regression and SEM analyses, a continuous variable representing the number of childhood victimizations was used. As this variable was skewed (skewness = 1.43), a log-normal transformation was performed resulting in a variable that was normally distributed (skewedness = 0.90, kurtosis = -.51). A test for multicollinearity was conducted for the variables included in the multivariate analyses, and the results showed that the variance inflation factor did not exceed the 2.00 threshold, and the tolerance was above 0.50.

Ethics

This study received ethical approval from the Arts and Sciences Research Ethics Board of the University of Montreal.

Results

Bivariate Analyses

Table 2 presents the bivariate analyses. Results showed that individuals who experienced childhood victimization were more likely to have been previously convicted of sexual offending during their adolescence (χ2 = 12.30, φc= 0.25, p < .001), to exhibit sexual interest in children (χ2 = 9.34, φc= 0.23, p = .002), to have a substance abuse problem (χ2 = 13.91, φc= 0.26, p < .001), and to report a sense of loneliness (χ2 = 4.16, φc= 0.15, p = .041). The results also showed a relationship between childhood victimization and cognitions that support online sexual offending. Individuals with a history of childhood victimization were more likely to consider children to be life partners (χ2 = 12.55, φc= 0.25, p < .001) and to believe that the world is dangerous (χ2 = 8.49, φc= 0.21, p = .004), although they were less likely to perceive the virtual world as not real (χ2 = 5.28, φc= 0.16, p = .022).

[Insert Table 2 here]

Multivariate Analyses

Table 3 describes the findings of the logistic regression models. Model 1 represents the factors associated with childhood physical victimization and presents an area under the curve (AUC) of 0.80. The results showed that individuals who sustained physical childhood victimization were more likely to have criminal convictions for sexual crimes during adolescence (β = 2.08, p < .001) and to have cognitions supporting the idea that the world is dangerous (β = 1.85, p < .001).

Model 2 shows the factors associated with childhood sexual victimization, with an AUC of 0.78. Individuals who sustained sexual childhood victimization were more likely to have criminal convictions for sexual crimes during adolescence (β = 0.49, p = .046), to exhibit sexual interests in children (β = 1.01, p = .013), and to have substance abuse problems (β = 0.79, p = .042). These individuals were more likely to have cognitions supporting the idea that children are life partners (β = 1.04, p = .042), although they were less likely to have cognitions supporting the idea that the virtual world is not real.

Model 3 indicates the factors associated with childhood psychological victimization, with an AUC of 0.77. The results showed that individuals who sustained childhood psychological victimization were more likely to have cognitions supporting the idea that the world is dangerous (β = 1.36, p = .008) and that children are life partners (β = 1.31, p = .014).

Model 4 represents the factors associated with any childhood victimization, with an AUC of 0.79. Individuals who sustained any childhood victimization were more likely to have criminal convictions for sexual crimes during adolescence (β = 1.24, p = .048), to have substance abuse problem (β = 1.02, p = .002), and to have cognitions supporting the idea that children are life partners (β = 1.36, p = .015). These persons were less likely to have cognitions suggesting that the virtual world is not real (β = -0.91, p = .013).

[Insert Table 3 here]

Table 4 presents the results of the multiple linear regression analyses. The findings showed that individuals who sustained polyvictimization were more likely to have criminal convictions for sexual crimes during adolescence (β = 0.52, p = .004), to have substance abuse problems (β = 0.21, p = .011), and to have cognition supporting the idea that the world is dangerous (β = 0.30, p = .016) and that children are life partners (β = 0.41, p = .002). However, polyvictimized persons were less likely to have cognitions supporting the idea that the virtual world is not real (β = -0.20, p = .015).

[Insert Table 4 here]

Table 5 shows the estimates with 95% confidence interval (CIs) for the SEM, and Figure 1 shows the SEM. The goodness of fit statistics showed a satisfactory model with a χ2 (19) of 156.57 (p <0.001), TLI of 0.936, GFI of 0.968, AGFI of 0.939, CFI of 0.931, RMSEA of 0.044, RMSR of 0.015, and RFI of 0.809. The findings suggested a direct relationship between childhood victimization and cognitions supporting the idea that the world is dangerous (β = 0.32, p < .001), that children are life partners (β = 0.31, p < .001), and that the online world is not reality (β = -0.16, p = .010). The relationship between childhood victimization and sexual interest in children (indirect effect: β = -0.16, p = .011) could be explained by the mediating effect of cognitions supporting the idea that the world is dangerous (β = 0.22, p = .001) and that children are life partners (β = 0.17, p = .012). Similarly, a direct relationship was observed between childhood victimization and the presence of previous convictions for sexual crimes during adolescence (β = 0.28, p < .001), while an indirect relationship also exists (indirect effect: β = 0.03, p = .017) potentially explained by the presence of sexual interest in children (β = 0.14, p = .041). The findings indicated that a direct relationship exists between childhood victimization and having a substance abuse problem (β = 0.22, p = .002). Further, an indirect relationship was observed between childhood victimization and the sense of loneliness (β = 0.12, p = .001). Finally, a direct relationship was found for cognitions supporting the idea that the world is dangerous (β = 0.03, p = .017) and that children are life partners (β = 0.02, p = .030) with the existence of convictions for sexual crimes during adolescence.

[Insert Table 5 here]

[Insert Figure 1 here]

Discussion

The objective of this study was to explore the role of childhood victimization on the development of risk factors associated with online sexual offending against children. Using a sample of men who used CSEM or engaged in child luring in Canada, we explored the association between childhood victimization and online sexual offending risk factors. In this sample, we observe that approximately one third of the individuals experienced childhood victimization. The results indicate that the overlap between the different types of childhood victimization is limited as the majority of individuals reported only one form of victimization, which is congruent with previous studies focusing on individuals involved in offline sexual crimes (e.g., Abbiati et al., 2014). We hypothesized that childhood victimization increases the risk of development of risk factors associated with online sexual offending against children, that childhood polyvictimization is associated with specific risk factors of online sexual offending against children, and that childhood victimization is associated directly and indirectly with risk factors of online sexual offending against children. All the exploratory hypotheses we formulated were supported by the results.

The results indicate an association between childhood victimization and risk factors for online sexual offending against children. This finding is congruent with previous studies focused on offline sexual offending (Abbiati et al., 2014; Davis et al., 2012; Krahé & Berger, 2017; Lee et al., 2002; Whitaker et al., 2008). Our findings highlight the relationship between childhood victimization and the presence of risk factors and criminogenic cognitions. These results are also in line with previous studies that found that childhood victimization is associated with a higher likelihood of developing pedophilic sexual interests (Freund & Kuban, 1994; Freund et al., 1990; Nunes et al., 2013), antisocial behaviors (Cicchetti & Banny, 2014; Johnson & Knight, 2000; Marini et al., 2014), relational problems (Cicchetti & Banny, 2014; Johnson & Knight, 2000; Marini et al., 2014), and cognitions supporting sexual aggression (Blank et al., 2018; Craissati et al., 2002; Kenny et al., 2001; Marziano et al., 2006). Furthermore, the results are in agreement with the developmental psychopathological framework, which suggests that negative experiences during childhood victimization may affect the dynamic interactions between affective and cognitive processing which in turn, shapes the behavioral adaptation patterns of individuals (Rutter & Sroufe, 2000).

Results also show that different types of childhood victimization affect adult cognitions and behaviors differently. Specifically, sexual victimization was more likely to be associated with risk factors of online sexual offending against children than physical and psychological victimizations. This result is congruent with previous studies, suggesting that childhood sexual abuse remains the most significant trauma in predicting future engagement in sexual offending (Jespersen et al., 2009; Leach et al., 2016). Additionally, psychological victimization tends to be associated with a higher likelihood to criminogenic cognitions, while physical victimization is more likely to be associated with the development of antisocial beliefs and behaviors. Such findings are in line with studies suggesting that the development of related risk factors is specific to different types of childhood victimization (e.g., McGloin et al., 2011; Miley et al., 2020)

In terms of types of abuse, polyvictimized victims were more likely to be associated with more risk factors than those who experienced one type of abuse. This finding echoes the results of other studies showing that the combination of several forms of trauma was associated with the development of several problematic disorders and behaviors during adolescence (Leach et al., 2016). Interestingly, we observed that the model computed for childhood polyvictimization presents more significant factors than the model for general childhood victimization. This finding suggests that polyvictimization increases the likelihood of developing risk factors associated with online sexual offending. This is congruent with studies that identified stronger relationships between polyvictimization and the development of risk factors (Casey et al., 2009; King et al., 2019; Leach et al., 2016). According to the concept of cumulative effect (see Thibodeau et al., 2017), we could assume that polyvictimization during childhood contributed to the development of a greater number of risk factors in individuals involved in online sex crimes.

Childhood Victimization and Online Sexual Offending Risk Factors: Toward an Integrated Model

In order to better understand the relationship between childhood victimization and the development of online sexual offending risk factors, an exploratory SEM was used. We examined the relationships between the variable related to childhood victimization and the different risk factors and criminogenic cognitions. The results showed that childhood victimization has both direct and indirect relationships with the different components of the model.

First, a direct relationship with criminogenic cognitions was observed. This result is in line with several previous studies that have identified a link between childhood abuse and the development of offense-supportive cognitions (Blank et al., 2018; Craissati et al., 2002; Kenny et al., 2001; Marziano et al., 2006). Specifically, we found a direct link between childhood victimization and cognitions supporting the idea that children are life partners. These cognitions mediate the relationship between childhood victimization and sexual interests for children. Given that such cognitions characterize men who self-identify as being in romantic relationships with children (Paquette & McPhail, 2020) which correlates with pedophilic interests (McPhail et al., 2014), our results suggest that some individuals who experienced victimization during childhood will be more likely to trust and feel confident around children later in adulthood– who are perceived to be safer and trustworthy compared to adults (Paquette and Cortoni, 2022) – and will eventually sexualize children, when sexual interests are consolidated.

Similarly, cognitions supporting the idea that the world is a hostile place in which people exploit others are also associated with childhood victimization. Just as cognitions reflective of the idea that children are life partners, our results show that endorsing the idea that the world is dangerous mediates the relationship between childhood victimization and sexual interests for children during adulthood. These cognitions characterize men who perceive children as safer because they believe adults are dangerous and will be betrayed by them. (Marziano et al., 2006). To explain this relationship, we hypothesized that being victimized as a child leads to a bias in the perception of adult–child relationships, resulting in victims’ loss of trust in adults. Again, lack of trust in adults and perceiving children to be trustworthy may lead some men to develop sexual interests for children later in adulthood. Although the identification of a relationship between pedophilic interests and childhood victimization is not a novel finding (Freund & Kuban, 1994; Nunes et al., 2013), the observation of the indirect link between the two factors is interesting and novel. This indirect link suggests that childhood victimization is not what explains the development of pedophilic sexual interests, but rather the development of distorted cognitions resulting from the victimization experienced in childhood.

We also find that cognitions supporting the idea of a dangerous world partially contribute to the development a sense of loneliness. In line with findings from Bates and Metcalf’s (2007) study, our results show that such cognitions characterized individuals who tend to avoid social contact with other adults.

We observe that cognition supporting the idea that the virtual world is not real is negatively associated with childhood victimization was observed. According to Paquette and Cortoni (2020), this cognition refers to the idea that the internet is not the reality and that its contents cannot be known or are perceived as unreal. The negative relationship observed in the current study suggests that individuals who have been victimized during childhood do not believe that what happens online is only virtual. It could thus be hypothesized that having been abused as a child makes individuals aware that child sexual exploitation images and videos, as well as child luring do involve real victims, even in a virtual context.

Consistent with previous findings, the current study’s results show a direct relationship between childhood victimization and substance abuse (Marini et al., 2014; Widom et al., 2006). We hypothesized that individuals who have experienced childhood victimization developed maladaptive coping strategies to manage their negative emotions. Substance abuse is often used as an adaptative regulation strategy to manage anxiety, stress, and unhappiness through self-medicating (Widom et al., 2006). However, this association should be further examined since studies have shown that there are a number of socio-economic (i.e., individual and contextual) factors that could arise from the context of childhood victimization which could indirectly explain substance use during adolescence and adulthood (Widom et al., 2006).

Our results showed both a direct and indirect relationships between childhood victimization and the commission of sexual crimes during adolescence. This relationship was also present among offline sexual offenders in past studies (Blumstein et al., 1988; Dierkhising et al., 2013; Drury et al., 2019; Jennings & Meade, 2017; Miley et al., 2020). Although not surprising, it is interesting to note that the involvement in delinquency during adolescence was the only risk factor that showed direct and indirect relationships with childhood victimization. On the one hand, we could assume that the direct relationship may be explained by the social learning of abusive behaviors (e.g., modeling by parents in the home) (Bandura, 1973; Jennings & Meade, 2017). On the other hand, the indirect association may be the consequence of the criminogenic cognitions and specific sexual interests discussed previously.

Conclusion

The purpose of this study was to explore the role of childhood victimization on the development of risk factors and criminogenic cognitions associated with online sexual offending against children. Using different levels of analysis, results showed that individuals who experienced childhood victimization presented different risk factors and cognitions than those who did not. Depending on the type of victimization experienced, different criminogenic cognitions, antisocial behaviors, and pedophilic sexual interests for children are more likely to manifest in adulthood. In addition, results show that polyvictimization accentuated the development of these risk factors in line with the concept of cumulative effect. Finally, we found that the relationship between childhood victimization and the risk factors are complex. Childhood abuse is directly associated with the development of offense-supportive cognitions, substance abuse, and youth engagement in sexual offending, while sexual interests for children and sense of loneliness are indirect consequences of childhood trauma.

This study has both theoretical and practical implications. From a theoretical perspective, this research is the first to describe the implication of childhood victimization among a sample of individuals involved in online sexual crimes against children in adulthood. Although individuals involved in online and offline sexual offenses are often considered separate, our results suggest that the mechanisms and implications of childhood victimization on the development of risk factors are very similar. Moreover, this study supports the relevance of the developmental psychopathology theoretical framework for individuals involved in online sexual crimes. The current study’s analyses provide concrete evidence supporting the notion that trauma affects the construction of individuals’ cognitive schema, which then shapes their behavioral adaptation patterns through the development of individual and antisocial disorders.

In terms of practical implications, this research may be useful for both victim assistance and offender management programs. According to Cicchetti and Banny (2014), the relationship between childhood victimization and the development of risk factors is probabilistic, instead of deterministic (see the concepts of multifinality and equifinality). Therefore, it is important to increase the identification of children who have sustained different types of traumas and to offer them appropriate psychological assistance to reframe their affective and cognitive processing that may have been adversely affected by those negative experiences. In particular, our results suggest that beliefs about trusting adults and about sexualizing children should be predominantly targeted. Finally, results suggest that the involvement of some individuals in delinquency can be partly explained by childhood trauma. Therefore, it may be appropriate to focus treatment programs on the role of adverse childhood events. This practice, known as trauma-informed care, recognizes the role of childhood trauma and its impact on future life events. The goal is not to focus all therapy on childhood adverse events but to integrate it with relapse prevention or cognitive behavioral therapy programs (Levenson et al., 2014). Our results may allow clinicians to better target the factors likely associated with their clients’ childhood traumas in order to treat them accordingly and increase the chances of reducing recidivism.

There are several limitations to the current study. First, the information used in this research came from official data. Thus, the results can only be generalized to individuals who were known to the judicial system. Second, this study is the first to focus on online sexual offenders, and we do not have any point of comparison with which to contextualize our results. The only comparisons that were possible were with studies of individuals involved in offline sexual crimes. Third, SEM method was conducted with a limited sample size (N = 199). While the use of SEM is appropriate with limited sample sizes (see Wolf et al., 2013), we believe that the results should be understood in terms of trends rather than the exact values of the standardized path coefficients. Fourth, the cognition variables used in this study were taken from the discourse of individuals in police custody, which may include post-hoc justifications intended to reduce the negative impacts associated with their crimes rather than reflecting the actual beliefs of online sexual offenders. Fifth, despite our findings being in line with previous studies, we are unable to disentangle the possibility that some risk factors are more likely to be associated with other life events other than childhood victimization. Sixth, in tandem with the majority of studies in the field, we assume that cognitions, disorders, and antisocial behaviors are a consequence of childhood victimization, but it is still possible that these could have developed before, or independently of the traumatic events. Seventh, it was not possible to conduct bivariate analyses for each type of victimization. Although this analytical process is common and allows for better comparability of specific multivariate models, we cannot rule out that bivariate analyses conducted for each type of victimization could affect the selection of some variables to be included in the multivariate models. Finally, in this study, we combined individuals involved in two types of online sex crimes (i.e., CSEM and child luring). Differences as well as similarities were found when comparing CSEM and child luring offenders (see Seto et al., 2012). Both were, however, considered in the same group given the overlap in terms of their offences. Such overlap was found in previous research using independent samples conducted in police (Paquette & Cortoni, 2022) as well as clinical and correctional settings (e.g., Paquette & Cortoni, 2021). It should be noted that many men who engaged in online sexual solicitation of minors are also charged with child pornography-related offences, since they obtained sexual images of their victims or captured images on their webcam session with them. Thus, very few of these men were only charged with child luring. Inversely, men who download child pornography over P2P software also, sometimes, concurrently engage in online sexual communication with minors. Although no differences in childhood victimization were found in the bivariate analyses, we cannot exclude that the construction of specific models for each type of online crime may eventually present some differences. These results should be considered as a first step and therefore, deserve more in-depth investigation.

Future studies will need to further investigate the role of childhood victimization among online sex offenders. First, research should replicate this study with a different sample to test the validity of the findings presented in this study. Second, it would be interesting to include some additional variables to increase the scope of the results and determine whether specific types of childhood victimization may explain the implications in online vs. offline sexual offending.

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Tables and Figures

Table 1. Descriptive analysis of childhood victimization among the sample of online sexual offenders (N=199)


N

% of total samples

% of childhood victimization

Childhood victimization (dichotomous)

72

36.18

100.00

Type of childhood victimization




Sexual childhood victimization

45

22.61

62.50

Physical childhood victimization

34

17.09

47.22

Psychological childhood victimization

30

15.08

41.67

Combination of childhood victimization




Only sexual childhood victimization

23

11.56

31.94

Only physical childhood victimization

10

5.03

13.89

Only psychological childhood victimization

10

5.03

13.89

Sexual and physical childhood victimizations

9

4.52

12.50

Sexual and psychological childhood victimizations

5

2.51

6.94

Physical and psychological childhood victimizations

7

3.52

9.72

Sexual, physical and psychological childhood victimizations

8

4.02

11.11

Different types of childhood victimization (continuous)




Mean

0.55

SD

0.84

Skewness

1.43

Kurtosis

1.12

Minimum

0.00

Maximum

3.00


Table 2. Bivariate analysis of factors associated with childhood victimization (N=199)


No childhood victimization

Childhood victimization

χ²

φc


n=

%

n=

%



Individual had a legal occupation

84

66.14

46

63.89

0.10

0.02

Individual was single

70

55.12

48

66.67

2.54

0.11

Individual used CSEM

96

75.59

59

81.94

1.08

0.07

Individual engaged in child luring

64

50.39

32

44.44

0.65

0.06

Individual was convicted of sex crimes during his adolescence

2

1.57

10

13.89

12.30***

0.25

Individual exhibited sexual interests in children

43

33.86

41

56.94

10.04**

0.23

Individual has a substance abuse problem

48

37.80

47

65.28

13.91***

0.26

Individual presented relational difficulties

27

21.26

23

31.94

2.79

0.12

Individual reported a sense of loneliness

35

27.56

30

41.67

4.16*

0.15

Cognition: Dangerous world

11

8.66

17

23.61

8.49**

0.21

Cognition: World is uncontrollable

37

29.13

25

34.72

0.67

0.06

Cognition: Sexual offending does not cause harm

34

26.77

24

33.33

0.96

0.07

Cognition: Children are life partners

7

5.51

16

22.22

12.55***

0.25

Cognition: Entitlement

10

7.87

10

13.89

1.84

0.10

Cognition: Virtual is not real

60

47.24

22

30.56

5.28*

0.16

Cognition: Online world is uncontrollable

48

37.80

25

34.72

0.19

0.03

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

φc = Cramer’s V


Table 3. Logistic regressions of factors associated with childhood victimization (N=199)


Model 1a

Model 2b

Model 3c

Model 4d


β

S.E.

Exp(β)

β

S.E.

Exp(β)

β

S.E.

Exp(β)

β

S.E.

Exp(β)

Individual was convicted of sex crimes during his adolescence

2.08

0.57

8.02***

0.49

0.55

1.63*

0.19

0.64

1.21

1.24

0.56

3.46**

Individual exhibited sexual interests in children

-0.51

0.49

0.60

1.01

0.40

2.76*

0.35

0.47

1.42

0.46

0.35

1.59

Individual has a substance abuse problem

0.41

0.45

1.50

0.79

0.39

2.20*

0.60

0.45

1.82

1.02

0.34

2.76**

Individual reported a sense of loneliness

0.42

0.45

1.53

0.35

0.39

1.42

0.34

0.45

1.40

0.50

0.36

1.64

Cognition: Dangerous world

1.85

0.53

6.33***

-0.22

0.51

0.80

1.36

0.50

3.88**

0.54

0.48

1.71

Cognition: Children are life partners

0.71

0.60

2.03

1.04

0.54

2.82*

1.31

0.53

3.71*

1.36

0.56

3.88*

Cognition: Virtual is not real

-0.90

0.48

0.41

-0.90

0.40

0.41*

-0.20

0.45

0.82

-0.91

0.36

0.40

Constant

-2.27

0.43

0.10***

-2.14

0.39

0.12***

-2.84

0.49

0.06***

-1.49

0.32

0.23***

χ²

38.58***

30.27***

26.38***

45.89***

-2 log likelihood

143.40

182.49

142.18

214.88

Hosmer and Lemeshow test

8.43

7.08

11.18

6.82

AUC

0.80

0.78

0.77

0.79

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

a Any physical childhood victimization

b Any sexual childhood victimization

c Any psychological childhood victimization

d Any childhood victimization


Table 4. Multiple regression of factors associated with childhood polyvictimization (N=199)


β

S.E.

95% [CI]

Constant

0.39***

0.07

0.25

0.54

Sex crimes during his adolescence

0.52**

0.18

0.17

0.87

Sexual interest in children

0.12

0.09

-0.06

0.29

Substance abuse problem

0.21*

0.08

0.05

0.37

Sense of loneliness

0.11

0.09

-0.07

0.28

Cognition: Dangerous world

0.30*

0.13

0.06

0.55

Cognition: Children are life partners

0.41**

0.13

0.15

0.67

Cognition: Virtual is not real

-0.20*

0.08

-0.37

-0.04

R2

0.30




SE of Estimates

0.58




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


Table 5. Regression weights of the exploratory structural equation model

Paths

β

S.E.

95 % [C.I]

Pvalue

Direct effects








Cognition: Dangerous world

<---

Childhood victimization

0.32

0.03

0.16

0.50

<0.001

Cognition: Children are life partners

<---

Childhood victimization

0.31

0.03

0.13

0.47

<0.001

Sexual interests for children

<---

Cognition: Dangerous world

0.22

0.10

0.06

0.35

0.001

Sexual interests for children

<---

Cognition: Children are life partners

0.17

0.11

0.03

0.30

0.012

Substance abuse problem

<---

Childhood victimization

0.22

0.04

0.07

0.36

0.002

Cognition: Virtual is not real

<---

Childhood victimization

-0.16

0.04

-0.28

-0.02

0.025

Sex crimes during his adolescence

<---

Childhood victimization

0.28

0.02

0.08

0.44

<0.001

Sense of loneliness

<---

Cognition: Dangerous world

0.18

0.09

0.03

0.32

0.010

Sex crimes during his adolescence

<---

Sexual interests for children

0.14

0.03

0.01

0.25

0.041

Sense of loneliness

<---

Childhood victimization

0.06

0.04

-0.02

0.15

0.123

Sexual interests for children

<---

Childhood victimization

0.09

0.04

-0.01

0.17

0.058

Sexual interests for children

<---

Cognition: Virtual is not real

-0.04

0.07

-0.17

0.10

0.630

Substance abuse problem

<---

Cognition: Virtual is not real

0.08

0.07

-0.06

0.22

0.288

Substance abuse problem

<---

Cognition: Dangerous world

0.04

0.11

-0.11

0.19

0.571

Substance abuse problem

<---

Cognition: Children are life partners

-0.02

0.12

-0.18

0.14

0.827

Indirect effects








Sense of loneliness

<---

Childhood victimization

0.12

0.02

0.06

0.21

0.001

Sexual interests for children

<---

Childhood victimization

0.06

0.02

0.03

0.13

0.011

Sex crimes during his adolescence

<---

Cognition: Dangerous world

0.03

0.02

0.00

0.08

0.017

Sex crimes during his adolescence

<---

Cognition: Children are life partners

0.02

0.02

0.00

0.06

0.030

Sex crimes during his adolescence

<---

Cognition: Virtual is not real

-0.01

0.11

-0.02

0.01

0.664

χ²=156.57, df=19, p<.001








Tucker Lewis Index (TLI)

0.94







Goodness of Index (GFI)

0.97







Adjusted Goodness of Index (AGFI)

0.94







Comparative Fit Index (CFI)

0.93







Root Mean Square Error of Approximation (RMSA)

0.04







Root Mean Square Residual (RMR)

0.02







Relative Fit Index (RFI)

0.81







Note: β, standardized path coefficient; SE, standard error; CI, confidence interval.

Figure 1. Exploratory structural equation model for childhood victimization of individuals involved in online sex offending during adulthood (N=199).

Notes. *** p<0.001, ** p<0.01, * p<0.05

Parameter estimates are standardized.

Insignificant paths are not represented

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