Abstract
Most child sex offending is unreported and undetected. Despite this, most research relies on the characteristics of those frequently detected and arrested. This study aims to address this disparity by examining a group of men convicted of child sexual abuse (CSA) offences with multiple victims and who evaded detection for long periods of time (n = 170). This sample was compared to a group of men caught quickly for CSA offences against multiple victims (n = 170). The two groups were compared on demographic, lifestyle, sexual deviancy, and criminogenic measures. Individuals with long detection lags had more child victims, including more pre-pubescent and male victims and commenced their sexual offending at a comparatively earlier age. Additionally, individuals with long detection lags were more likely to be non- Indigenous and to show specialization in their sexual offending. These findings have implications for identifying and managing high harm child sexual offenders who evade detection for long periods.
Background
Child sexual abuse (CSA) often remains unreported and undetected (Australian Bureau of Statistics, 2017; Mills et al., 2015). Despite low rates of disclosure, much of what we know about the characteristics of CSA perpetrators comes from samples of convicted offenders and particularly those identified as recidivists (Hanson et al., 2010; Hanson & Morton-Bourgon, 2005). Research on convicted offenders is understandably prevalent given the challenges of reliably accessing information from undetected perpetrators of CSA but is likely unable to account for the broader population of those who commit CSA but who are less likely to be detected.
Theoretical Frameworks and Evading Detection
Developmental and life course (DLC) criminological research seeks to explain the differential distribution of criminality in the population and examines the dynamic variables that explain onset, escalation, persistence, and desistance, across one’s criminal career. Several DLC theories have helped shape criminal justice responses and particularly policy on juvenile offending and detention. These theories are not specific to crime types (such as sexual offending) but have tended to focus on the small group of people (5%–6%) who commit a disproportionate volume of crime (Moffitt, 2018). This framework translates usefully to our understanding of men convicted for sexual crimes, and in particular, those who sexually abuse multiple children and who also engage in other criminal behavior (Harris et al., 2009).
It is necessary to distinguish between persistence (repeated offending for a long duration) and recidivism (offending that continues after being sanctioned). When measures of persistence for CSA are focussed on victim counts and duration, as opposed to number of detected (known) crime events, the findings differ (Sullivan et al., 2011; Wortley & Smallbone, 2014). Small samples of men convicted of CSA have been identified as persistent in their offending but lack criminal versatility (Wortley & Smallbone, 2014), and appear to maintain pro-social lifestyles, including professional employment (Sullivan et al., 2011). The current study expands on this research by comparing the characteristics of men who are known to have evaded detection for CSA for long periods, and have demonstrated persistence with their high victim counts, with a group of men who have similarly high counts of CSA victims but were caught sooner for their crimes.
Prior literature on detection avoidance has focused on examination of the strategies individuals enact to avoid offence detection, typically framed using the rational choice perspective (Beauregard & Bouchard, 2010). Within this framework, people make decisions not only about the suitable target (the child), and opportunity (through lack of guardianship), but also make conscious decisions in actions to evade and minimize the risk of detection (Pedneault & Beauregard, 2014). Given this focus, much of the research on the strategies adopted by the CSA perpetrators to avoid detection have focused on their behaviors and cognitive decision making prior, during, and after the commission of a sexual offence (Bourke et al., 2012; Lussier & Mathesius, 2012; Vernham & Nee, 2016). Comparatively less is known about the characteristics (rather than the offence specific behaviors) of those men who persist in CSA and who evade detection for long periods, which could be directly relevant to investigative processes.
CSA detection is largely reliant on disclosure from victims or witnesses, and so inhibitors to disclosure contribute to perpetrators evading detection for these crimes. Barriers to people disclosing CSA are many and include (but are not limited to): the strength of relationship between offender and victim, feelings of guilt and shame, distrust in relevant authorities and fear of being ostracized by family, friends, and the wider community (Lanning & Dietz, 2014). There are also offence specific behaviors associated with the perpetrator of CSA which can influence likelihood of victim non-disclosure. These include grooming behaviors (Winters et al., 2020, 2022), social competence, and cognitive problem-solving abilities used in the course of their offending to gain compliance from and manipulate victims (Bourke et al., 2012; Vernham & Nee, 2016).
There are also general offending patterns and lifestyle factors associated with an increased likelihood of offence evasion and victim non-disclosure. Men who specialize in sexual offending and lack criminal versatility are more likely to have longer periods of evading detection for CSA (Lussier et al., 2011), and more likely to be in professional employment (Sullivan et al., 2011). Although these factors provide some insight into underlying characteristics associated with evading detection, there is a significant knowledge gap on the potentially identifiable features of men who engage in CSA and evade detection for long periods of time, which hinders investigative capacities to detect perpetrators early and limit harm. This exploratory study attends to this gap by creating two distinct groups: Men with multiple victims and a long lag to detection, and men with multiple victims and only short detection lags. Although the risk of committing a post-conviction sexual offence (reoffending) is a different concept altogether to evading detection, men with multiple victims and long detection lags, share the features of duration, and chronicity with recidivist men. This study cannot account for those men who evade detection altogether, but it does highlight the characteristics of those men who evaded detection for the longest period prior to their detection. Therefore, it has important implications for practice.
Characteristics Associated With Perpetration of CSA
Studies on perpetrators of child sexual abuse have highlighted that increased risk of persistent CSA, (usually typified by official recorded recidivism) is associated with demographic factors (e.g., age, gender, and ethnicity; Babchishin et al., 2016), antisocial orientation (Babchishin et al., 2016; Hanson & Morton-Bourgon, 2005; Katsiyannis et al., 2018), and sexual deviancy (Babchishin et al., 2016; Hanson et al., 2010; Ogloff et al., 2012; Seto, 2019). Much of the research on those who are persistent in their CSA offending focuses on these three broad constructs.
Demographic and Lifestyle Factors
Male perpetrators of CSA are much more prevalent than females (Hanson & Morton-Bourgon, 2005; Seto, 2019). Youthfulness has also long been associated with an increased risk of criminal offending, including sexual recidivism (Hanson et al., 2010). Younger sexual offenders are generally associated with higher engagement in risk taking activities and antisocial behavior, and also have more time to offend due to their early onset (Babchishin et al., 2016).
Ethnicity is associated with recidivism risk for CSA. In the Australian context, Indigenous Peoples are over-represented in the criminal justice system both as victims and perpetrators of crime, including for sexual offences (Adams et al., 2020; Allard et al., 2016). This over-representation is associated with a range of factors including socio-economic disadvantage, inter-generational trauma of colonization, and systemic racism which has resulted in mental health disorders, substance abuse, and lower educational attainment and insecure housing (Adams et al., 2020; Allard et al., 2016). Although Indigenous Peoples are over-represented in recidivism studies, they are less likely to evade detection for long periods due to systemic issues (e.g., levels of policing).
Finally, the nature of intimate partner relationships is associated with CSA. This is important in two ways. First, adult intimate partner relationships situationally may bring the perpetrator into direct unsupervised contact with children (Wortley & Smallbone, 2006). Second, the absence, or frequent changing of intimate partner relationships might be indicative of intimacy deficits the person may feel in adult partner relationships (Wielinga et al., 2019). The person may have an emotional congruence with children (Finkelhor, 1984) and this can create a sense of loneliness and aid in developing cognitive distortions such as abuse supportive attitudes (Ó Ciardha & Ward, 2013). It is likely that those who have long detection lags and multiple victims can form long term relationships with age-appropriate partners (Lanning & Dietz, 2014), but that these relationships may leave them unfulfilled due to their emotional congruence with and sexual attraction to children. The presence of long-term relationships amongst those people who evade detection is yet to be examined in research and is addressed in this study.
Antisocial Orientation
Antisocial orientation (ASO) has been strongly correlated with a range of criminal behavior, including sexual abuse (Hanson & Morton-Bourgon, 2005; Katsiyannis et al., 2018). ASO is not always overt (typified through violent or aggressive behaviors), but can be covert (deceitful, lying, or fraudulent behavior) or reckless (risky activities including in sexual activity; McCuish et al., 2015). Those people who have multiple victims but evade detection may have more covert forms of ASO than overt antisocial criminality allowing them to evade capture.
Studies have identified that although child sexual offenders (CSOs) tend to have less criminal versatility than adult rapists or violent offenders, their criminal records are commonly found to be more versatile than specialized (Harris et al., 2009; Wortley & Smallbone, 2014). There are CSOs however, who present with offence specialization. Men with multiple CSA victims who specialize in their sexual offending have been shown not only to have a higher likelihood of victim non-disclosure (Lussier et al., 2011), but also abuse more children over longer periods of time (Wortley & Smallbone, 2014). This study builds on this research by examining the degree to which sex offence specialization differentiates CSOs with long and short detection lags for their CSA offending.
Sexual Deviance
Sexual deviance (e.g., pedophilic interest) coupled with ASO has repeatedly been identified as predictive of sexual recidivism (Hanson & Morton-Bourgon, 2005; Katsiyannis et al., 2018). The presence of male child victims amongst persistent recidivist offenders has been identified in a broad range of studies, including those involving meta-analysis (Babchishin et al., 2016; Hanson & Morton-Bourgon, 2005; Seto et al., 2017). Male child victims have also been identified as less likely to disclose CSA (Alaggia et al., 2019; Hébert et al., 2009). It could follow that those with long detection lags, but multiple victims will have high proportions of male and pre-pubescent victims, but this is yet to be tested empirically. Seto et al. (2017) identified a high number of victims, and particularly those who were male and pre-pubescent were important indicators of pedophilia on the Revised Screening Scale for Pedophilic Interests (SSPI-2). There remain important gaps in our knowledge of the prevalence of sexual deviance, and particularly pedophilia amongst those who perpetrate CSA on multiple victims but evade detection for the longest time.
Current Study
This exploratory study aims to compare the characteristics of individuals convicted of child sexual offences against multiple victims with short and long detection lags. Previous studies have used recidivism to differentiate groups as an identifier of persistence (Hanson & Morton-Bourgon, 2005; Katsiyannis et al., 2018), whereas this study examines groups in a novel way by comparing groups with multiple victims (over time) but differentiating them by how long they evaded detection. Characteristics were coded from police holdings data managed by a state-wide police service, including demographic and personal characteristics, indicators of sexual deviancy, and general criminality. When compared to those caught more quickly for similar crimes against multiple victims, the following hypotheses were developed:
That those who evade detection for the longest time would: (1) have an earlier known onset for their sexual offending; (2) be non-Indigenous; (3) be in long term relationships; (4) have criminal records with more evidence of offence specialization (in sexual offending); and (5) have more pre-pubescent and male child victims.
Method
Data Source and Participants
Data were retrieved from the Queensland Police Service database. An initial sample of 2,435 men convicted for a contact child sexual offence on at least one extrafamilial victim (between 2007 and 2020) were extracted. Information on the victim offender relationship were not readily available prior to 2007. Contact sexual offences include any criminal offence of a sexual nature in which the offender was in physical proximity to the child (under 18 years) and in which there is at least one victim named in the offence. This would include an exposure offence if they targeted specific victims. All charged criminal offences (including sexual) were then sourced for the participants in this group from 1990 (earliest date from which offending information is available) to 2020 from the same database, and conviction data retrieved across the participant’s life span.
Two subgroups were then selected from the initial sample using two criteria. The first criterion ensured the sample participants were sufficiently persistent in their sexual offending and required that they had at least two child victims. This criterion substantially reduced the sample (n = 1,059). The second criterion was designed to ensure we were capturing only those men with the “longest detection lag.” This sample consisted of the outliers in the group with the longest detection lag for any of their recorded sexual offending (n = 295). The detection lag was calculated to determine the period of time that was known to have elapsed between offence and detection. This variable was computed by deducting the earliest known commission date of offence (the “start date”), usually reported by the victim or witness, from the detection date (when the sexual offence was reported to police). The outliers were determined using the inter-quartile range (IQR) method (Tukey, 1977). In this method, the detection lags were set in ascending order, with the lower quartile Q1 being the observation of the 25th percentile, the second quartile Q2 the observation at the 50th percentile, and the third quartile Q3 the observation at the 75th percentile. The value between Q3 and Q1 is referred to as the inter quartile range (IQR) and represents the parameters from which outliers can be determined. If an observation falls below Q1 − 1.5 × IQR or above Q3 + 1.5 × IQR, it is considered as an outlier (Andreou & Karathanassi, 2014). A comparison group (n = 319) with relatively shorter detection lags across all of their sexual offending was then extracted. A short detection lag was defined as falling below the second quartile Q2 (below the mean value across the sample) of the distribution.
Groups were matched on age using case control matching. This process yielded two groups of 170 participants each (See supplementary figure for further details). There were clear differences between the groups for the length of their longest detection lag. Those men determined to have long detection lags ranged from 1,779 to 18,879 with a mean average longest lag to detection of 5,374.74 days (SD = 3,427.74). In comparison, the longest detection lags for the short detection lag group ranged in length from 0 days to 100 days, with a mean average of 20.69 days (SD = 28.69). An independent samples t-test confirmed that the groups were statistically significantly different t(169.02) = 20.37, p < .001, two-tailed). This was expected, given the way the groups were constructed, but it is included here to provide evidence of group separation on detection lag. It took more than 4 years for those men with long detection lags to be reported for their CSA after it occurred, compared to less than a month elapsing between offence and detection for the comparison group. In compliance with the University’s ethics committee and the research unit of the Police Service, data was redacted and deidentified prior to analysis.
Measures
Age
Age was operationalized in two different ways: age at data extraction (November 2020); and age at known sexual offence onset. Age is consistently correlated with risk of recidivism (Babchishin et al., 2016; Hanson & Morton-Bourgon, 2005) and youth (under 25 years) appears as a risk factor for persistence and recidivism in many actuarial tools.
Indigenous status
Subjects who self-identified as Indigenous were recorded as such (regardless of any other ethnicities recorded within the police holdings). In this article, we respectfully refer to Aboriginal and Torres Strait Islander Peoples as Indigenous Australians.
Intimate partner relationships
This variable was measured at the time of data extraction and consistently appears in comparative research of men who commit CSA offences (Babchishin et al., 2016). The response options in the data holdings included: married, engaged, de-facto (common law), separated, divorced, widowed, single, and unknown. These were later condensed into a dichotomous variable: “ever in a long-term relationship (married, engaged, de-facto, divorced, or separated)”; and “single.” This approach enabled adequate distribution across categories, but nearly half of the cases were missing for this item (n = 158; leaving 84 in the long detection and 98 in the comparison group).
Victim characteristics
The “unique victims” measure counted the individual child victims of contact sexual abuse for each offender between 1990 and 2020. Victim gender and age was also collected. Victim age was ultimately dichotomized into under 13 years (pre-pubescent) and 13 and over (pubescent).
Pedophilia
Pedophilia was indicated if the person was recorded with multiple victims of contact CSA (which was pre-requisite selection criteria), and recorded with pre-pubescent victims and male victims, consistent with the Revised Screening Scale for Pedophilic Interests (SSPI; Seto et al., 2017). Victim age was operationalized as a dichotomous variable, with victims defined as pre-pubescent (under 13 years), or pubescent (aged 13–17 years). Although pedophilia is not defined by age category in the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5), prior research has used under 13 years as a measure for pre-puberty in case file analysis (Guha et al., 2020; Hanson et al., 2010; Ogloff et al., 2012). Gender was also operationalized as a dichotomous variable with all victims within the dataset identifying as either male, or female. The count of victims was operationalized as a continuous variable.
Sexual offence specialization and summary of non-sexual convictions
Offence specialization and criminal versatility was measured by calculating the percentage of one’s sexual offending as a percentage of their total official criminal record. This percentile average was then compared between groups. In this regard, there was no cut-off for specialization threshold but a comparison of the calculated percentage of specialization.
Based on pre-determined categorizations provided in the police data, non-sexual offences were classified as follows:
Violent and harmful offences
The sum count of offences involving interpersonal (nonsexual) harm such as homicide, torture, assaults, kidnapping, and strangulation in a domestic and family violence (DFV) context. Other interpersonal harmful offences included stalking, arson, and weapon offences (not including weapons licensing).
Covert and reckless antisocial indicators
Offences indicative of antisocial or impulsive characteristics included illicit drug offences, breaches of community-based orders, breaches of DFV orders, and criminal reoffending (criminal offending after prior conviction).
Other criminal offences
This is a summary count of all criminal offences not included in the above categories.
Juvenile criminal offending
This is a dichotomous measure of whether the participant had any official criminal record prior to the age of 18. Juvenile offending is often closely associated with antisocial orientation or impulsivity and is a measure included in validated tools such as the Psychopathy Checklist Revised (PCL-R; Hare et al., 2000).
Analytical strategy
A series of bivariate analyses examined group differences on demographic, offence-related, and sexual deviance characteristics. Chi-square tests were used to examine differences between long and short detection lag individuals on category variables. Independent samples t-test were conducted to compare the groups on continuous measures. Kolmogorov-Smirnov and Shapiro-Wilk tests demonstrated that the continuous variables of victim count, degree of offence specialization, and criminal offence types were not normally distributed, with Mann-Whitney U-Tests conducted as an alternative to the independent samples t-test. For multivariate analysis, a logistic regression model was performed to assess the combined impact of several factors on the likelihood that participants would have long (sample) or short (comparison) detection lags.
Results
Demographic and Personal Characteristics
All participants had a mean age of 50.19 (SD = 12.67) years at the time the data were extracted. At the commission date of their first sexual offence, the comparison group were on average 9 years older (M = 36.74, SD = 14.93) than the long detection lag group (M = 25.71, SD = 10.30; t(300.14) = 7.93, p < .001, two-tailed). A chi-square test for independence indicated the comparison group had a significantly higher representation of Indigenous men than the sample group (n = 60 and 21 respectively), χ2(1, n = 339) = 24.98, p < .001; Cramer’s V = 0.271. Relationship status did not distinguish the groups. Although, as mentioned above, this result should be interpreted cautiously due to the number of missing cases for this item.
Sexual Deviancy
The long detection lag group reported higher median numbers of child victims, pre-pubescent victims, pubescent victims, and male victims compared to those with short detection lags (see Table 1). Of the significant findings, higher median numbers of pre-pubescent victims for the long detection group (compared to short detection group) had the largest effect size (r = .37) in the moderate to large range. The number of female victims did not significantly differentiate the groups.
Sexual Deviance by Detection Lag.
p < .001.
General Criminality
Across all criminality measures, long detection lag individuals had lower rates of criminal offending and a higher degree of specialization in sexual offending (see Table 2). The largest between groups effect size (r = .37) was observed for sex offence specialization in which the long detection lag offenders (M = 62.16% specialized; SD = 33.54) were significantly more specialized than the short detection group (M = 36.20 specialized; SD = 32.64). The long detection lag group had less harmful offences (M = 1.11; SD = 2.77) than the short detection lag group (M = 2.99; SD = 5.47), less covert and overt antisocial offending (LDL: M = 9.28, SD = 14.50: SDL: M = 21.44, SD = 25.48), and fewer other types of criminal offending (LDL: M = 5.58, SD = 12.63: SDL: M = 17.49, SD = 31.01). The effect sizes in this category on the Mann Whitney U tests were in the moderate to high range. A chi-square test indicated that participants with short detection lags had higher rates of juvenile criminal offending than those with long detection lags, χ2(1, n = 340) = 4.83, p = .03; Cramer’s V = 0.119, albeit with a low to moderate effect size.
Rates of Criminality Indicators by Detection Lag.
p < .001.
Other variables of interest
Logistic regression was performed to assess the combined effect of the variables on distinguishing between individuals with long and short detection lags. Relationship status was not included in the final model due to the high number of missing cases. Multicollinearity was assessed using a threshold of values above .50 in the variance proportions in two or more categories and/or a Variance Inflation Factor (VIF) of more than 4, and/or a tolerance level below .2. These statistics identified multicollinearity affecting several of the variables. When the variables of victim count, pubescent victims, female victims, covert and reckless antisocial offences, harmful offences and other criminal offences were excluded from the model, no issues with multicollinearity were identified. The final model contained five independent variables (Indigenous status, onset age for sexual offending, number of pre-pubescent victims, any male victims and sexual offence specialization). The full model containing all predictors was statistically significant, χ2(5, n = 339) = 178.35, p < .001, indicating that in combination the variables were able to significantly distinguish between the groups. The model explained between 40.9% (Cox & Snell R2) and 54.5% (Nagelkerke R2) of the variance in group membership for detection lag and correctly classified 78.2% of cases (AUC = 0.881).
As shown in Table 3, four of the five independent variables made a statistically significant contribution to the model (age, Indigenous status, pre-pubescent victims, and sex offence specialization). The strongest predictor of evading detection was identifying as non-Indigenous and having pre-pubescent victims. The odds of being in the long detection lag group was 65.7% lower for Indigenous Australians. Further, the long detection lag group were 1.58 times as likely to have pre-pubescent victims than the comparison group.
Multivariate Predictors of Likelihood of Group Membership by Detection Lag (n = 339).
p < .01. ***p < .001.
Discussion
This study identified people who were known to have committed CSA against multiple victims and evaded detection for the longest time and compared them on a range of characteristics to a comparison group of people who abused multiple children but were caught comparatively quickly for their crimes. Significant differences were found between the groups. Those who evaded detection were younger at the onset of sexual offending, non-Indigenous, had more child victims (particularly pre-pubescent male victims), and were more likely to specialize in sexual offending. In contrast, the short detection lag participants were observed to have the characteristics consistent with high recidivist offenders found in a broad range of studies (Babchishin et al., 2016; Hanson & Morton-Bourgon, 2005; Katsiyannis et al., 2018).
This exploratory study identified a group of men who not only adopt behaviors in their offending to evade detection but have inherent characteristics which appear to have aided that evasion. When persistence is considered by the number of victims rather than the frequency in which a person is caught for CSA, a different profile emerges from extant high recidivism studies. These men are not life-course persistent offenders in their general criminality but tend to specialize in CSA (hypothesis 4), with onset typically in adulthood rather than adolescence (as far as official records indicate). It is not only that they make rational choices about their offending behaviors, but the lack of general criminality indicates some degree of self-regulation and lesser impulsive traits than men who only have short detection lags for CSA, although further research is required to determine this. The findings and their implications are expanded on below.
Supporting the first hypothesis, demographic differences were identified between the groups. Long detection lag participants were, on average 9 years younger than the short detection group at the start of their sexual offending. This is consistent with research indicating that those motivated by pedophilic interest are likely to have an earlier onset than those committing CSA as part of broader criminogenic lifestyle (Blagden et al., 2017). It is likely that the motivations behind perpetration of CSA are multifaceted and cannot be reduced to taxometric categorizations (Seto, 2019). In addition, situational factors may be an important precipitating factor in the onset of CSA. It may be that lifestyle factors including relationships, parenthood, and employment, make child access more available to the men in both groups, but further research would be required to determine the circumstances behind the variance in situational factors between these groups.
In support of hypothesis 2, fewer Indigenous men than non-Indigenous men managed to evade detection for long periods. Research has identified an overrepresentation of Indigenous people in the Australian criminal justice system (Allard et al., 2016; Gathercole et al., 2016). Causal factors for this include the effects of colonization, intergenerational trauma, and systemic racism (Allard et al., 2016; Menzies, 2019). Consequently, Indigenous people have been identified as disproportionally exposed to systemic vulnerabilities including poverty, poor educational attainment, unemployment and higher rates of substance abuse, all associated with higher likelihoods of sexual offending (Adams et al., 2020). We regret that the earlier detection rates for Indigenous men may also be representative of inherent bias in the criminal justice system (Cunneen & Tauri, 2019).
Hypothesis 3 was not supported as the groups did not differ by relationship status. There could be several explanations for this finding. First, as discussed earlier, this result may be due in part to missing data where lifestyle factors are not as readily available, or as accurately recorded as criminal offending information. Second, it is likely that intimacy deficits existed in both groups. As this study examined only those with multiple victims, it is possible that a reasonable proportion of men in both groups have pedophilic tendencies and had difficulties forming relationships with age-appropriate partners (Wielinga et al., 2019). Further research using relationship information from alternative sources is recommended.
The short detection lag group were not only found to be more criminally versatile, but also more frequently engage in harmful non-sexual offences, such as violent offending, as well as other more covert or reckless antisocial offences than long detection lag individuals. This is likely to be a significant factor in victims making earlier disclosures of CSA, particularly if the perpetrator is prone to violence (or threats). Juvenile criminal offending was also observed to be more common amongst those with shorter detection lags. It is likely that the absence of the high rates of criminality is a contributory factor in them evading detection for long periods, but further research is required before attributing causation to their tendency to evade detection.
Overall, the men who evaded detection were found to have more pedophilic interest, as measured by more child victims, and particularly more pre-pubescent male victims (in support of hypothesis 5). No significant difference was indicated for female victims. The pre-pubescent victim count remained significant in the logistic regression model. These findings, highlight pedophilia as a salient characteristic for the men with long detection lags, as shown in prior studies (Seto, 2019; Wortley & Smallbone, 2014).
Implications for Practice
The findings from this study indicate differences for those who evade detection for the longest time for CSA, when compared to those who are caught comparatively quickly. The sexual offending for those who evade detection is not part of a general pattern of antisocial behavior. The earlier age at onset of sexual offending, targeting of more (and younger aged) children, higher propensity for male victims and less criminal versatility all indicates a long-term motivation to not only abuse, but correspond with evasion of detection for their crimes. These findings have important implications for law enforcement and practitioners in both detecting offences, prioritizing offender management strategies, crime prevention and treatment. Each one is described below.
First, those who evade detection for the longest time, have significantly more pre-pubescent victims than those who were detected more quickly. Young children may not be able to verbalize the abuse sufficiently to disclose, may be less likely to be understood and believed, and may be more susceptible to the offender “coaching” the child through grooming techniques (Lanning & Dietz, 2014; Winters et al., 2020, 2022). Professional training and public information focused on ways to effectively communicate with young children around inappropriate touching or identifying grooming techniques should be encouraged (Rudolph & Zimmer-Gembeck, 2018). For police, training such as this should be considered more broadly to include general duty officers in addition to those working in child protection, as increased awareness will assist in identifying concerning behaviors at an earlier stage.
Second, although much of the literature on victimization focuses on women, and girls, due to their higher rates of victimization overall, this study further highlights boys as being frequently targeted for sexual abuse. Boys often either do not disclose that abuse or disclosures are not taken as seriously. The finding that men committing persistent CSA but evading detection for long periods are targeting boys reinforces earlier studies on the gender disparity in disclosure (Alaggia et al., 2019; Hébert et al., 2009). The reasons for this are likely multifaceted, but center on perceptions of masculinity, both at the societal and individual level. Reflective of those broader perceptions, police and child protection agencies may be less inclined to associate sexual abuse with boys, and so not be as vigilant at identifying the indicators of it (Scholes et al., 2014). When coupled with the decreased likelihood of boys disclosing abuse than girls, this poses a substantial challenge for police in detecting these crimes earlier. Further research and gender responsive training in speaking to younger children around these issues would be of benefit here.
Finally, the findings from this study highlight that although those who evade detection for long periods do present with sexual deviancy, they often lack more generic criminogenic indicators. This is contrary to the broader body of research on CSA identifying antisocial orientation and sexual deviancy to be the primary predictors of sexual recidivism (Babchishin et al., 2016; Hanson & Morton-Bourgon, 2005; Katsiyannis et al., 2018). Whilst the sample of interest represent a small proportion of those who commit CSA, they are important to consider because they cause significant harm through such high victim counts. There also remains the possibility that those identified by the frequency in which they are caught represents an inherent bias in the criminal justice system and is not representative of the broader population of those who perpetrate abuse but not caught for their crimes. Lussier et al., (2011) highlighted this point in their study of the factors associated with “successes” of CSOs. These “successes” were demonstrated in the CSO’s ability to offend against multiple victims, on multiple occasions over long periods without detection. Sex offence specialization was identified as an important factor in longer delays to detection. Efforts to detect men with high victim counts sooner requires challenging some acquired knowledge on those who perpetrate sexual abuse. For example, “risk” factors such as criminal versatility (Babchishin et al., 2016; Hanson & Morton-Bourgon, 2005), and “protective” factors such as employment, stable relationships, and an apparent ability to self-regulate may actually facilitate detection evasion rather than act as a barrier to abuse. Further research is clearly required on these variables before such conclusions can be drawn.
Whilst relevant agencies should continue to utilize actuarial risk tools in identifying those with a high likelihood of sexual and violent recidivism, this study provides evidence that there remain subsets of persistent offenders who do not fit well into these risk models. Although this study does not examine the likelihood of official recidivism amongst those men with long detection lags, it does consider their number of victims (chronicity) and duration of offending (persistence) prior to arrest. Therefore, it is important to identify how they compare on characteristics with those who are caught more frequently for their crimes. Incorporating the characteristics of those with multiple victims but who evaded detection for long periods should, therefore, be considered in risk management and prevention strategies. Additionally, with those who evade detection for long periods likely to have a higher likelihood of pedophilic interest and demonstrate longevity in their offending, it is likely that they will have developed entrenched cognitive distortions, such conditions might pose additional challenges in a treatment context (Barroso et al., 2019). As their criminal histories seem to contain a greater proportion of sexual offences (and lack criminal versatility), they also develop expertise in persistent offending and evasion (Bourke et al., 2012). This may serve as a motivation to reoffend, which could also be addressed in a treatment setting.
Limitations
It is necessary to consider the study’s limitations. First, data were collected exclusively from police holdings, limiting the scope of some lifestyle variables, such as interpersonal relationships and mental health. Second, this is essentially a study of outliers. This exploratory study included the creation of two outlier groups for analysis, with the sample of interest consisting of outliers amongst a broad sample of men convicted of CSA offences. This method created inherent bias in the selection, but it was ultimately deemed appropriate to maximize possible differences, given the exploratory nature of the research. This selection of outliers was intentional, and we note the unavoidable flaw in the limited generalizability of our findings to other offending populations. Our contribution is valuable, however, given the paucity of empirical research on these particular men. Third, the operationalization of the “longest detection lag” variable does not preclude those with long detection lags also having sexual offences with shorter detection lags. The purpose was to compare those men who have evaded detection for significantly long periods for sexual abuse with those men who did not evade detection for sexual offending for long periods at all, and so this method was justifiable given the exploratory nature of the study. Fourth, due to limitations in identifying the offender/victim relationship, we were unable to locate a connection between delays in detection and offending inside or outside the family prior to 2007. This limits our conclusions because the circumstances for evading detection are substantially different for abuse perpetrated within the family rather than outside of the family. Fifth, the amount of time in which the participant was incarcerated may inadvertently create a disclosure bias, in that their other victims may be more inclined to disclose historical abuse if their perpetrator has been taken into custody. Although this incarceration time somewhat biases the “detection lag,” there is limited evidence to suggest that incarceration impacts CSA disclosure. This may, however, be a useful measure for additional research in this area. Finally, this study does not include possible investigative or organizational failures which can play a part in the variance in disclosure and detection of these offences. Further to this, luck may also play a part in whether someone evades detection for these crimes, as well as intangible factors associated with detection of CSA.
Conclusions
This study examined two groups of men convicted of CSA offences with multiple victims and sought to differentiate them by long and short detection lags, and a range of offence and victim characteristics. Men with long detection lags were less likely to be Indigenous, and commenced their sexual offending at a younger age, whilst demonstrating more indicators of sexual deviancy through high counts of child victims, more pre-pubescent victims, and more male victims. Conversely, they exhibited far less general criminality and antisocial indicators when compared to individuals with short detection lags. This study shows that the difference between those caught quickly and those able to offend for long periods is not blind luck. There are systematic differences, and this represents a first step in understanding a specific group and has important implications for investigation, detection of CSA, and management of men convicted of these crimes. This study demonstrates that whilst those who evade detection for long periods represent a relatively small group of outliers amongst populations of men convicted of CSA, they cause considerable harms through persistent victimization and worthy of further examination.
Supplemental Material
sj-docx-1-ijo-10.1177_0306624X221106320 – Supplemental material for Evading Detection: Characteristics of Individuals With Extrafamilial Child Sexual Offences and Long Detection Lags
Supplemental material, sj-docx-1-ijo-10.1177_0306624X221106320 for Evading Detection: Characteristics of Individuals With Extrafamilial Child Sexual Offences and Long Detection Lags by Samuel J. Nicol, James Ogilvie, Danielle A. Harris, Mark R. Kebbell and Tony B. Christie in International Journal of Offender Therapy and Comparative Criminology
Supplemental Material
sj-docx-2-ijo-10.1177_0306624X221106320 – Supplemental material for Evading Detection: Characteristics of Individuals With Extrafamilial Child Sexual Offences and Long Detection Lags
Supplemental material, sj-docx-2-ijo-10.1177_0306624X221106320 for Evading Detection: Characteristics of Individuals With Extrafamilial Child Sexual Offences and Long Detection Lags by Samuel J. Nicol, James Ogilvie, Danielle A. Harris, Mark R. Kebbell and Tony B. Christie in International Journal of Offender Therapy and Comparative Criminology
Footnotes
Acknowledgements
The authors wish to acknowledge the support and assistance from the Queensland Police Service in undertaking this research. The views expressed in this publication are not necessarily those of the Queensland Police Service and any errors of omission or commission are the responsibility of the authors.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
Supplemental Material
Supplemental material for this article is available online.
References
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