The purpose of this paper is to collate the available research into the characteristics of child abuse material (CAM) offenders to inform future assessment and treatment options. This systematic review collates the contribution and directionality of variables from existing research assessing an offenders’ use of CAM.
Background and definitions of terminology are reviewed, and a summary of sexual reoffending rates provided. Articles were then identified for inclusion through a systematic review using online searches, EBSCOHost and other databases. Articles were also identified from reference lists. After exclusions, the final sample (n=17) were reviewed for identified variables and their directional contribution to risk.
Internet only (IO) offenders present with a range of similarities and differences. The demographic, psychological and offence-specific risk variables identified suggest IO offenders differ from other types of sexual offenders. Using the collated variables, IO offender profiles are suggested.
Limitations have been identified in the availability of research in this area, the variety of terminology and the definitions in common usage. Additionally, there are challenges in ascertaining the truthfulness of self-reported data.
Development of IO offender-specific risk assessment tools would contribute to advances in targeted supervision and treatment. In turn, this contributes to community safety by protecting children from online sexual victimisation.
Based on identified gaps, this review contributes to ongoing research by signalling future pathways for IO offender-specific risk assessment.
Garrington, C., Rickwood, D., Chamberlain, P. and P. Boer, D. (2018), "A systematic review of risk variables for child abuse material offenders", The Journal of Forensic Practice, Vol. 20 No. 2, pp. 91-101. https://doi.org/10.1108/JFP-05-2017-0013Download as .RIS
Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited
Opportunities for seeking child abuse material (CAM) have increased, with the internet allowing greater levels of accessibility and anonymity. Policing the internet for the sexual abuse of children has become a major international concern. Removal of practical barriers may have resulted in people accessing CAM who may not have previously done so (Faust et al., 2014). Krone (2004) acknowledges the impact of the internet on such behaviours and notes it is not possible to know how the internet may have contributed to the previously existing demand.
There are a variety of terms relating to child sexual abuse (CSA) material. These include child sexual exploitation material, child abuse images and CSA imagery. These terms replace the previous and outdated term of child pornography (CP). This systematic review focuses on offenders who source and download child abuse images or videos online, or internet only (IO) offenders. Other types of sexual offenders include those who produce child abuse images or solicit sexual contact with children offline, or contact offenders (CO), and mixed offenders who commit both online and offline child sexual offences.
Despite the assertions of some sentencing judges and offenders convicted of CAM downloads and/or possession, it is not a victimless crime (Rogers, 2008). The effects on the victims of CAM production are widely detailed in Rogers (2008) and von Weiler et al. (2010). Effects can include physical and psychological abuse. Additionally, Rogers (2008) notes and von Weiler et al. (2010) agrees that these feelings can be exacerbated by the fact that CSA images uploaded or shared online can never be fully deleted. The ongoing exposure adds humiliation, shame and powerlessness to the victim’s experience that can last forever. The tracking, arrest, prosecution and treatment of CAM users are all imperative for community protection and general deterrence.
Individuals who access CAM online may or may not meet the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders Version 5 (DSM-5)’s classification and diagnostic criteria for paedophilia (American Psychiatric Association, 2013). DSM-5 records the prevalence of paedophilic disorder to be unknown, however overwhelmingly diagnosed in males. It is less important to differentiate between paedophiles and men who access CAM without a primary sexual attraction to children as the result of their actions is the same: they contribute to the trade of sexual images of children and the resulting harm to the victims.
There are challenges in defining “recidivism”. Technically, any offence, including a driving or theft offence is considered a reoffence. The question of sexual recidivism and predictive factors was addressed by Eke et al. (2011). They note undetected reoffending is unable to be captured by the standard methods of data collection. As a follow up to their 2005 study, Eke et al. (2011) found predictors of contact sexual recidivism to include any prior criminal convictions, with approximately half the sample having prior convictions for CAM offences.
With regard to assessing the risk of sexual reoffending of offenders convicted of IO offences, there is limited availability of applicable research studies. At this time, estimates range from around 7 per cent for further IO offences (see Eke et al., 2011), to 32 per cent for any type of offence Eke et al. (2011). Self-report data reflect 95 per cent of CAM offenders admitting ongoing use and 59 per cent admitting frequent use (Riegel, 2004).
The aim of this systematic review is to source and summarise the available literature reviews on CAM offenders. From these reviews, a summary of the identified variables related to recidivism for internet-based CAM offending behaviours will be discussed. Finally, the possibilities for future risk assessment, including limitations, will be explored.
Searches were undertaken using the following EBSCOHost online databases: Medline, PsychARTICLES, Psychology and Behavioural Sciences Collection, PsychINFO and ProQuest. Additional searches were conducted using the University of York’s Prospero International prospective register of systematic reviews, Campbell Collaboration’s Campbell Systematic Reviews, and Google Scholar for articles published to 7 June 2016. Articles were also identified through reference lists of articles returned by the above searches.
Articles containing information relevant to online CAM offences, offenders and their characteristics were included. Articles about online offenders who source and download CAM images (IO offenders) were included. Articles about CO who produce such images or contact children online to solicit sexual contact were excluded. CO offenders were excluded from this study due to the focus on online CAM offenders. Articles included:
were available in an English translation; and
addressed risk and/or protective factors for online CAM users.
Search terms and associated acronyms used in searches were CSA (CSA), Child Sexual Exploitation Material (CSEM), CP (CP), CAM, online CP, Child Pornographic Exploitation and CP Offender. Words used with search terms included web, internet, online pornography (including porn*), molestation (including molest*) and children (including child*). The phrase “child pornography” was not used as a search term in Google Scholar without clarifying words to reduce the risk of returning illegal material. However, the term “child pornography” with quotation marks and without clarifying terms was used in restricted academic databases. Please see Figure 1 for total search results, and Table I for a final list of studies included in the systematic review.
The search terms used indicate a range of terminologies in common usage. This paper will use “IO offender” to describe online only CAM offenders, unless otherwise specified. It is noted all papers reviewed considered males only.
Results and discussion
Information from the articles included (n=17) has been divided into categories of variables. These categories are summarised in Table II, noting the contribution each variable makes to the direction of an IO offender’s risk of reoffending. In order to ascertain variables and their contribution to predicting further IO offending, this review has had to draw upon previous studies’ comparisons between IO and CO offenders. This assists to build a generalised description of an IO offender. Table II also compares identified risk variables between these populations.
Babchishin et al. (2011) conducted a meta-analysis comparing demographic and psychological differences between IO and CO sexual offenders. Of 27 studies totalling 4,844 adults included in the meta-analysis, Babchishin et al. (2011) established online offenders were younger, not in a relationship and unemployed when compared to the general population. They postulated IO offenders have higher rates of self-control and emotional avoidance, and show less impulsivity than CO offenders.
Henshaw et al. (2015) conducted a comprehensive critical review of worldwide literature comparing IO offenders to CO offenders. Their findings concluded that the demographic characteristics indicative of IO offenders are younger, higher functioning in education and employment, and lower functioning in the relationship domain. An IO offender was found to be Caucasian, less likely to have a past history of sexual abuse, physical abuse or substance use problems (also see Faust et al., 2014). Additionally, IO offenders were less likely to have a recorded criminal history of either general or sexual offending (Henshaw et al., 2015).
Clevenger et al. (2014) compared demographic and background factors of offenders arrested for IO offences in the USA. They further differentiated between CAM possessors and CAM producers/distributors. Of significance, they found IO offenders were twice as likely to be arrested over the age of 40 when compared to arrests under the age of 30 years, and twice as likely as producers/distributors to have been previously violent. IO offenders were found to be more likely to have been employed full time and married and/or separated (when compared to single/never married arrestees) (Clevenger et al., 2014). Further, arrestees for CAM possession in this study who were employed full time and married and/or separated had less than half the risk of further arrest for CAM possession when compared to CAM producers/distributors.
Also in the USA, Faust et al. (2014) considered recorded data on 638 males released from US prisons between 2002 and 2005. In total, 428 were convicted of IO offences only, and the remaining 210 convicted of contact sexual offences against children. With regard for IO offenders, Faust et al. (2014) found they were more likely to be Caucasian (coded as “White”), have lower levels of recorded criminal histories, less substance abuse history and were older when first arrested. Additionally, IO offenders had higher recorded years of education than CO offenders, and higher levels of pre-incarceration employment.
Faust et al. (2014) also established IO offenders were less likely than CO offenders to be arrested for a subsequent sexual or non-sexual violent offence/s.
In 2012, Long, Alison and McManus conducted research on the largest UK sample at the time of 120 IO and mixed offenders. Findings relating to demographic factors demonstrated no statistical differences between the two groups on age or relationship status at time of detection. However, they found IO offenders were more likely to be living alone, less likely to have previous criminal convictions and had less access to children.
In a similar and more recent study, McManus et al. (2015) examined a further sample of UK convicted child sex offenders, again differentiating between IO and mixed offenders. In contrast to their 2012 study above, this study found IO offenders were more likely than CO/mixed offenders to be living with their parents and not in a relationship. They concluded this may indicate social deficits in the IO offender population (McManus et al., 2015).
Ray et al. (2013) surveyed an anonymous sample of voluntary internet adult pornography users. Of the total sample, 21 per cent were self-identified as IO offenders. The only significant demographic difference was that IO offenders were less likely to report being in an intimate relationship than general adult pornography users. However, Ray et al. (2013) suggest other differences may not be statistically apparent as the demographics of adult pornography users may be similar in both the legal and illegal users of pornography groups. A comparative study of a further anonymous sample of online pornography users by Seigfried-Spellar (2014) found a smaller proportion (5.86 per cent) self-reported as IO offenders. Seigfried-Spellar (2014) also found IO offenders were more likely to report being Caucasian, single and with greater than 15 years of education.
Whilst Clevenger et al. (2014) used IO offenders’ alcohol and/or other drug use as an indicator of higher levels of self-control, this variable could also be included under the social variables category. Magaletta et al. (2014) concur that alcohol and/or other drug use is lower in IO offenders than in CO offenders. However, it is suggested further research is required to clarify the placement of this variable.
There are significant limitations in using offenders’ recorded criminal histories in isolation. Bourke and Hernandez (2009) identified 155 offenders convicted of CAM possession or transmission offences in an American prison. Of these, prior to treatment, 26 per cent recorded a history of contact child sexual offences. However, after self-reported disclosures during treatment, this number rose to 85 per cent. Bourke and Hernandez (2009) suggested that this raises doubts as to the veracity of the IO offender category, as the majority of their sample were also self-reported contact child sexual offenders.
Seto et al. (2011) concur with Bourke and Hernandez’s (2009) study. Through a meta-analysis of 24 studies, their data indicated that 12 per cent of offenders convicted of IO offences had a recorded prior contact child sexual offence. However, 55 per cent self-reported prior contact offence/s not detected by authorities. Although these numbers are lower than those reported by Bourke and Hernandez (2009), they strongly support discrepancies between recorded and self-reported contact offences by IO offenders.
Of interest to the question of recorded vs self-reported crimes, Neutze et al. (2011) conducted a related study in Germany. Significantly, Germany does not have mandatory reporting laws for child abuse. Thus, such offenders can self-report without immediate fear of criminal sanctions. In their 2011 study, Neutze et al. established 75 per cent of the 155 male sample diagnosed with paedophilic disorders (as per DSM-IV-TR (American Psychiatric Association, 2000) criteria) self-reported previously undetected offences. Neutze et al. (2011) also corroborated other studies, finding IO offenders with offences committed in the previous six-month period were more likely to be employed than CO offenders.
Eke et al. (2011) followed a Canadian sample of 541 males convicted of IO offences over a period of 4.1 years. They established an overall recidivism rate of 32 per cent, including 7 per cent charged with a new IO offence and 8 per cent charged with a further contact sexual offence (either historical or post index offence). Of the 64 per cent of the original sample who were convicted of online offences, Eke et al. (2011) reported significant predictors of re-offending included younger age, prior criminal history, especially violent criminal history (including contact sexual offences). Unfortunately, the undifferentiated use of mixed offenders in their reporting makes these findings indicative rather than predictive.
Babchishin et al. (2011) identified psychological variables indicating IO and CO offenders report higher rates of childhood sexual and/or physical abuse than the general population. No significant difference was found between IO and CO offenders with regard to childhood sexual and/or physical abuse.
Beech et al. (2008) conducted a criminological review of the processes by which people use the internet for CAM. They identified three key processes: dissemination of CAM, communication with other CAM offenders and maintenance/networking between CAM users. Beech et al. (2008) suggest that the self-report of undetected contact offences against children by IO offenders can be of use, but noted limitations in the inability to verify data. Limitations include possible over- and under-estimating of past offences as claimed by offenders. Of especial significance to risk assessment, they noted several studies independently found increasing rates of IO offenders admitting to previously undisclosed contact offences (see Hernandez, 2006 in Beech et al., 2008).
In summary, demographic variables identified consistently suggest factors that may be of value in further research into IO offenders. These include age, ethnic background, educational level, employment status, relationship status and living status. Further, alcohol and other drug use, victim of past physical or sexual abuse and general and/or criminal history (recorded and self-reported). From the studies included in this review, indicators are an IO offender is more likely to be younger, Caucasian, educated for over ten years, employed and single. Further indicators are they are less likely to use alcohol and/or other drugs, and increasingly likely to have a more extensive criminal history than detected. Finally, an IO offender appears to be less likely to have been a victim of physical and/or sexual abuse. This portrays a possible image of an IO offender who is able to lead an outwardly functional adult life of education and employment, an absence of a significant partner and no discernible alcohol and/or other drug issues.
With regard to offending pathways, Aslan et al. (2014) identified offence process themes through qualitative thematic coding analysis of interviews with eight male offenders in England convicted of both IO and CO child sexual offences. The methodology of theme predictability is not statistically tested, resulting in suggestive commonalities limited by the small sample size. Aslan et al. (2014) recognised the variety in childhood experiences of offenders who commit sexual offences against children. These included a spectrum from prosocial and supportive upbringings to childhood abuse (emotional, physical and/or sexual) and attachment difficulties. However, they noted these factors may not be predictive of the commission of sexual offences against children. Escalating variables towards committing sexual offences against children coded by Aslan et al. (2014) included the quality of adult relationships, personality problems and alcohol and/or other drug use.
With regard to personality factors, Magaletta et al. (2014) compared a sample of 35 convicted IO offenders to a sample of 26 CO offenders using the Personality Assessment Inventory in the USA. Their findings indicate IO offenders have higher comparative interpersonal deficits and depression than CO offenders. IO offenders recorded lower scores on aggression and dominance factors than CO offenders and a normative sample. Other findings for IO offenders included difficulties in interpersonal functioning and mood regulation, lower levels of alcohol and drug use and lower levels of anti-sociality and criminality than CO offenders. This study concluded the significant personality factors and treatment targets of IO offenders are unassertiveness, under socialisation and poor emotional regulation (Magaletta et al., 2014).
Babchishin et al. (2011) found IO offenders scored lower on impression management scales than CO offenders. Similarly, Seigfried-Spellar (2014) indicated differences between types of IO offenders (see Krone, 2004 for definitions), include higher levels of extraversion, conscientiousness and impulsivity seeking than CO offenders. They also noted exchangers and communicators of CAM scored higher on extraversion scales than viewing only CAM offenders. Suggested variables for further research into IO offenders include higher social/interpersonal deficits, access to the internet and children, lower impression management and alcohol and/or other drug use.
Babchishin et al. (2014) conducted a further meta-analysis of the differing characteristics of IO and CO offenders from 30 studies from the USA, Canada and the UK. Differentiating between IO, CO and mixed offender populations, Babchishin et al. (2014) detailed marked differences in offending profiles. CO offenders were found to be more likely than IO offenders or mixed offenders to have lower antisocial assessments. Further, IO offenders were found to be the most paedophilic, as identified by expressed sexual interest.
On the variable of self-control, Clevenger et al. (2014) reported CAM possessors demonstrated higher levels of self-control (as indicated by less prior arrests, less reported alcohol and/or other drug issues). They concluded CAM possessors have more restraint and have more stable lifestyles than CAM producers/distributors. Acknowledging a limited data pool, Clevenger et al. (2014) caution against drawing conclusions from the above findings, and clearly avoid using the terms “risk” or “protective” with regard to the identified factors.
In a critical review, Henshaw et al. (2015) identified the psychological variables of IO offenders as exhibiting fewer offence supporting beliefs, higher interpersonal and affective deficits and higher fantasy and sexual deviancy. However, they also note the current infancy of IO offender research, the differences and lack of clarity in definitions used by different authors, and the subsequent challenges in generalising data.
Overall, the current research indicates psychological variables relating to IO offenders include self-control levels, emotional avoidance and social and interpersonal deficits. Further inclusions are impression management, impulse control and anti-sociality. Based on the consistent research findings, an IO offender would have high levels of self-control, emotional avoidance and social and interpersonal deficits, but lower levels of impression management, impulse seeking and anti-sociality. Therefore, an IO offender with the above characteristics may demonstrate a controlled image, less social abilities and possible avoidance of social interactions and would not attempt to impress others. However, without significant anti-sociality, this IO offender would also avoid impulse seeking activities.
Perhaps logical considering the internet-based nature of CAM offences, Babchishin et al. (2014) established IO offenders were found to have greater access to the internet than CO offenders. Through statistical analysis of a complex data set, McManus et al. (2015) identified mixed offenders as being more likely to have access to children than IO offenders. Also strongly supportive of these variables, Seigfried-Spellar (2014) concurred IO offenders are more likely to have access to the internet but noted lower access to children.
Aslan et al. (2014) identified commonalities and possibly predictive variables for offenders with an IO index offence and a past conviction for CO offences. These included sexually deviant interests, lack of self-control, opportunity to commit offence/s, the role of the internet (including availability, ease of access and anonymity) and cognitive distortions (justifications, denial, blame, minimisation). Consistent with these findings, Babchishin et al. (2011) also identified variables that indicate IO offenders have greater victim empathy and greater sexual deviancy than CO offenders.
Babchishin et al. (2014) found although IO offenders are more likely to have sexually deviant interests than CO offenders, their psychological barriers to contact child sexual offending were also higher. It was suggested higher victim empathy may reduce the risk of contact child sexual offending in IO offenders.
Henshaw et al. (2015), Aslan et al. (2014) and Neutze et al. (2011) found indications that IO offenders have lower offence supportive beliefs than CO offenders. Interpretations are that this could be that this could be a protective factor to crossing over to contact sexual offending. Further protective factors include fewer cognitive distortions, lower emotional identification with children and higher victim empathy than contact sexual offenders (Babchishin et al., 2011). One significant limitation of this study was the inclusion of both IO and CO offenders.
Revisiting Long et al.’s (2012) UK study, they suggested their analysis of the types of CAM images and videos found in the possession of IO offenders may give significant clues as to areas of dynamic risk. Long et al. (2012) suggested the content could indicate “anchor points”, or an offender’s clear preference of image content and possibly victim selection. Questions raised include whether IO offenders who possess lower, more voyeuristic images of children compared with higher, sexual contact images would be less likely to cross over to contact sexual offences against children. Long et al. (2012) conclude more research into this area could provide valuable insight into dynamic reoffending factors.
In summary, identified risk variables relevant to offence-specific indicators of IO offenders include sexual deviance, offence supporting beliefs and victim empathy. Accounting for the online nature of IO offences, it is no surprise that these offenders also have higher levels of internet access. Additionally, an IO offender appears less likely to have direct access to children, but higher levels of sexual deviance. Perhaps of treatment significance, an IO offender is likely to present with lower levels of offence supporting beliefs and higher levels of victim empathy.
Drawing together demographic, psychological and offence-specific variables, it is apparent there is no singular identifying variable or variables for identifying IO offenders. Consistent with current research, it remains challenging to identify an IO offender without indisputable evidence of their activities. Current findings offer evidence towards a range of variables. This requires identification of a combination of demographic, psychological and offence-specific predictors. The IO offender depicted by the above variables could continue to merge into legal society, with few to no indicators of their duplicitous life until after detection, arrest and conviction.
Limitations and future directions
The contribution IO offender assessment could make to community protection appears critical to preventing the sexual exploitation of children. There was a limited field of studies available for this review, resulting in a variety of perspectives on contributing variables. With differences in terminology and definitions, challenges in using self-reports and the sensitive nature of this topic, it is unsurprising there many theories and suggestions with limited quantified data. Houtepen et al. (2014) detailed similar difficulties in their literature review with discrepancies between legal and academic definitions of terminology. Further, their conclusions are similar in suggesting further research is required in the areas of IO offenders’ negative childhood experiences as well as sexual and cognitive distortion development.
As initially noted, there remain ongoing challenges in assessing the risk of sexual reoffending of offenders convicted of solely downloading pre-existing CAM images. With a variety of risk variables detailed, it is obvious the complexity of risk assessment requires further consideration and development. With some consistencies highlighted, there remain other less easily observable variables. This research signals future pathways for the risk assessment of IO offenders.
This systematic review has commenced collating similarities and differences between IO and CO offenders. As yet, it is not possible to yet suggest whether existing risk assessment tools for predicting sexual reoffending may also be applicable to IO offenders. The characteristics identified may or may not be contributing factors to IO recidivism. Indications are the development of a new risk assessment tool would be useful for community protection through sentencing guidelines, and for the treatment of IO offenders. If there are differing types of sexual offenders, there remains little point in attempting to assess and treat all in the same manner. The development of specialised assessment tools for CAM offenders would contribute to forming a foundation for treatment options. These could include individualised, targeted treatment and supervision plans to successfully treat those who contribute to the sexual victimisation of children.
Implications for practice
Research indicates that there are variables common to IO offenders which would assist with providing clarity to the risk factors for reoffending. With the collation of risk factors, treating practitioners could:
identify IO offending behaviours;
tailor IO offender treatment to target individualised risk factors;
focus on individual treatment needs; and
protect children from further victimisation.
Targeted treatment addressing IO offenders’ demographic, psychological and offence-specific variables will contribute to the community protection of children online.
Final articles included in systematic review
|Aslan et al. (2014)||Entering the world of sex offenders: an exploration of offending behaviour patterns of those with both internet and contact sex offences against children||Journal of Forensic Practice, Vol. 16 No. 2, pp. 110-26|
|Babchishin et al. (2011)||The characteristics of online sex offenders: a meta-analysis||Sexual Abuse: A Journal of Research and Treatment, Vol. 23 No. 1, pp. 92-123|
|Babchishin et al. (2014)||Online child pornography offenders are different: a meta-analysis of the characteristics of online and offline sex offenders against children||Archives of Sexual Behavior, Vol. 44 No. 1, pp. 45-66|
|Beech et al. (2008)||The internet and child sexual offending: a criminological review||Aggression and Violent Behavior, Vol. 13 No. 3, pp. 216-28|
|Bourke and Hernandez (2009)||The “Butner Study” Redux: a report of the incidence of hands-on child victimization by child pornography offenders||Journal of Family Violence, Vol. 24 No. 3, pp. 183-91|
|Clevenger et al. (2014)||A matter of low self-control? Exploring differences between child pornography possessors and child pornography producers/distributers using self-control theory||Sexual Abuse: A Journal of Research and Treatment, Vol. 1, pp. 1-17|
|Eke et al. (2011)||Examining the criminal history and future offending of child pornography offenders: an extended prospective follow-up study||Law and Human Behavior, Vol. 35 No. 6, pp. 466-78|
|Faust et al. (2014)||Child pornography possessors and child contact sex offenders: a multilevel comparison of demographic characteristics and rates of recidivism||Sexual Abuse: A Journal of Research and Treatment, Vol. 27 No. 5, pp. 460-78|
|Houtepen et al. (2014)||From child pornography offending to child sexual abuse: a review of child pornography offender characteristics and risks for cross-over||Aggression and Violent Behavior, Vol. 19 No. 5, pp. 466-73|
|Henshaw et al. (2015)||Looking beyond the screen: a critical review of the literature on the online child pornography offender||Sexual Abuse: A Journal of Research and Treatment, Vol. 1, pp. 1-30|
|Long et al. (2012)||Child pornography and likelihood of contact abuse: a comparison between contact child sexual offenders and noncontact offenders||Sexual Abuse: A Journal of Research and Treatment, Vol. 25 No. 4, pp. 370-95|
|Magaletta et al. (2014)||Exploring clinical and personality characteristics of adult male internet only child pornography offenders||International Journal of Offender Therapy and Comparative Criminology, Vol. 58 No. 2, pp. 137-53|
|McManus et al. (2015)||Factors associated with contact child sexual abuse in a sample of indecent image offenders||Journal of Sexual Aggression, Vol. 21 No. 3, pp. 368-84|
|Neutze et al. (2011)||Predictors of child pornography offences and child sexual abuse in a community sample of pedophiles and hebephiles||Sexual Abuse: A Journal of Research and Treatment, Vol. 23 No. 2, pp. 212-42|
|Ray et al. (2013)||Correlates and moderators of child pornography consumption in a community sample||Sexual Abuse: A Journal of Research and Treatment, Vol. 26 No. 6, pp. 523-45|
|Seigfried-Spellar (2014)||Distinguishing the viewers, downloaders, and exchangers of internet child pornography by individual differences: preliminary findings||Digital Investigation, Vol. 11 No. 4, pp. 252-60|
|Seto et al. (2011)||Contact sexual offending by men with online sexual offences||Sexual Abuse: A Journal of Research and Treatment, Vol. 23 No. 1, pp. 124-45|
Identified risk variables for reoffending for IO compared to CO offenders
American Psychiatric Association (2000), Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (text revision), American Psychiatric Association, Washington, DC.
American Psychiatric Association (2013), Diagnostic and Statistical Manual of Mental Disorders, 5th ed., American Psychiatric Association, Washington, DC.
Aslan, D., Edelmann, R., Bray, D. and Worrell, M. (2014), “Entering the world of sex offenders: an exploration of offending behaviour patterns of those with both internet and contact sex offences against children”, Journal of Forensic Practice, Vol. 16 No. 2, pp. 110-26.
Babchishin, K., Hanson, R. and Van Zuylen, H. (2014), “Online child pornography offenders are different: a meta-analysis of the characteristics of online and offline sex offenders against children”, Archives of Sexual Behavior, Vol. 44 No. 1, pp. 45-66, available at: http://dx.doi.org/10.1007/s10508-014-0270-x
Babchishin, K., Karl Hanson, R. and Hermann, C. (2011), “The characteristics of online sex offenders: a meta-analysis”, Sexual Abuse: A Journal of Research and Treatment, Vol. 23 No. 1, pp. 92-123, available at: http://dx.doi.org/10.1177/1079063210370708
Beech, A., Elliott, I., Birgden, A. and Findlater, D. (2008), “The internet and child sexual offending: a criminological review”, Aggression and Violent Behavior, Vol. 13 No. 3, pp. 216-28, available at: http://dx.doi.org/10.1016/j.avb.2008.03.007
Bourke, M.L. and Hernandez, A.E. (2009), “The ‘Butner Study’ Redux: a report of the incidence of hands-on child victimization by child pornography offenders”, Journal of Family Violence, Vol. 24 No. 3, pp. 183-91.
Clevenger, S., Navarro, J. and Jasinski, J. (2014), “A matter of low self-control? Exploring differences between child pornography possessors and child pornography producers/distributers using self-control theory”, Sexual Abuse: A Journal of Research and Treatment, Vol. 28 No. 6, pp. 555-71, available at: http://dx.doi.org/10.1177/1079063214557173
Eke, A.W., Seto, M.C. and Williams, J. (2011), “Examining the criminal history and future offending of child pornography offenders: an extended prospective follow-up study”, Law and Human Behavior, Vol. 35 No. 6, pp. 466-78, doi: 10.1007/s10979-010-9252-2.
Faust, E., Bickart, W., Renaud, C. and Camp, S. (2014), “Child pornography possessors and child contact sex offenders: a multilevel comparison of demographic characteristics and rates of recidivism”, Sexual Abuse: A Journal of Research and Treatment, Vol. 27 No. 5, pp. 460-78, available at: http://dx.doi.org/10.1177/1079063214521469
Henshaw, M., Ogloff, J. and Clough, J. (2015), “Looking beyond the screen: a critical review of the literature on the online child pornography offender”, Sexual Abuse: A Journal of Research and Treatment, Vol. 29 No. 5, pp. 416-45, available at: http://dx.doi.org/10.1177/1079063215603690
Hernandez, A.E. (2006), “Sexual exploitation of children over the internet: the face of a child predator and other issues”, paper presented before the Subcommittee on Oversight and Investigations Committee on Energy and Commerce at the United States House of Representatives, United States Department of Justice, Washington, DC.
Houtepen, J., Sijtsema, J. and Bogaerts, S. (2014), “From child pornography offending to child sexual abuse: a review of child pornography offender characteristics and risks for cross-over”, Aggression and Violent Behavior, Vol. 19 No. 5, pp. 466-73, available at: http://dx.doi.org/10.1016/j.avb.2014.07.011
Krone, T. (2004), “A typology of online child pornography offending”, Trends and Issues in Crime and Criminal Justice, No. 279, pp. 1-6.
Long, M.L., Alison, L.A. and McManus, M.A. (2012), “Child pornography and likelihood of contact abuse: a comparison between contact child sexual offenders and noncontact offenders”, Sexual Abuse: A Journal of Research and Treatment, Vol. 25 No. 4, pp. 370-95.
McManus, M.A., Long, M.L., Alison, L. and Almond, L. (2015), “Factors associated with contact child sexual abuse in a sample of indecent image offenders”, Journal of Sexual Aggression, Vol. 21 No. 3, pp. 368-84, available at: www.rimas.qc.ca/wp-content/uploads/2013/10/McManus-1.pdf
Magaletta, P.R., Faust, E., Bickart, W. and McLearen, A.M. (2014), “Exploring clinical and personality characteristics of adult male internet-only child pornography offenders”, International Journal of Offender Therapy and Comparative Criminology, Vol. 58 No. 2, pp. 137-53.
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About the authors
Catherine Garrington is a Student of Psychology at the Faculty of Health, University of Canberra, Canberra, Australia.
Dr Debra Rickwood is a Professor of Psychology at the Faculty of Health, University of Canberra, Canberra, Australia.
Dr Peter Chamberlain was based at the Faculty of Health, University of Canberra, Canberra, Australia.
Dr Douglas Boer is a Professor of Clinical Psychology at the Department of Psychology, University of Canberra, Canberra, Australia.