Examining the sexual offending patterns of registered sexual offenders

Problem

Online child sex offending is a high-volume crime, and the scale of the issue can strain the capacity for effective management and prevention with the resources currently being used. The rapid development of the internet and the proliferation of online child abuse are deeply concerning issues that pose significant challenges for society, police and child protection agencies across the globe (Wolak, Finkelhor and Mitchell, 2009). The internet has made it easier for individuals to access, share explicit material, groom and target children (Kemshall and McCartan, 2014).

Despite the growing empirical literature in the field of online child sexual abuse, research from an investigative perspective is needed to explore:

• recidivism rates of indecent images of children offending populations
• the risk factors that are unique to indecent images of children offenders
• escalation pathways from online to offline and vice versa

This will inform the development of tertiary intervention measures particularly specialised risk assessment tools and management strategies.

Current figures and management model

There are currently over 5,000 registered sexual offenders (RSOs) within Greater Manchester. Around 3,000 require community management by the Sex Offender Management Unit (SOMU).

The register grows by approximately 10% annually. If this upward trajectory continues, the register could list over 8,000 people by 2027. In addition, there are many more who are subject to sexual risk orders or have been identified as posing a potential risk but have not been convicted of a sexual offence. Consequently, there are significant demands on the SOMU staff and police resources.

The current model for managing sexual offenders uses the same approach regardless of the type of sexual offence committed. However, due to the heterogeneity (variety) of sexual offending, this strategy is increasingly considered to be inefficient with little evidence that it is effective in reducing the risk of reoffending for all offenders. For example, it is likely that the risk of recidivism presented by non-contact online offenders – that is, those charged with producing, possessing, making or distributing indecent images of children – is different from contact offenders.

It is estimated that most offenders currently on the Greater Manchester Police (GMP) register pose some form of online offending risk (approximately 70%). Therefore, having a detailed understanding of this group and their risk of recidivism could lead to a more effective risk management approach.

Aims

1. Categorise offenders into typologies (non-contact online/online and contact).
2. Examine pre- and post-index offence offending patterns of the non-contact online offender cohort.
3. Provide an initial analytical profile of the current non-contact online offender to understand the range of crime incidents recorded.
4. Investigate the feasibility of linking this information to other data sources that can inform risk management and help target resources more effectively.

It is estimated that there are 7,800 crimes relating to the possession, production and possession of indecent images of children recorded for the GMP region between 1 January 2013 and 31 December 2022. 

In a recent meta-analysis examining predictive validity of a risk assessment tool in males convicted of sexual offending (Brankley, Babchishin and Hanson, 2021), the median sample size from 12 studies was n=179 (range 42 – 4,291). Based on this research, we aim to randomly select a sample of at least 179 cases.

Crimes involving producing, possessing, making, or distributing indecent images of children recorded over a 10-year period with be analysed, regardless of the outcome for the offender. Secondary data on previous offending history will be extracted from the Police National Computer (PNC). 

Variables

• Socio-demographic and behavioural characteristics of offender (and victim if known).
• Offence typology (non-contact online / online and contact).
• Offences recorded on the PNC (previous convictions / cautions for sexual offending) pre- and post-offence.
• Any civil orders issued (such as sexual harm prevention orders).
• Any risk assessments undertaken (such as ARMS, RISK MATRIX 2000, OPS).
• If the offender was subject to registered sex offender management.

Analysis

Coding the cohort will establish the prevalence and nature of the offences committed by non-contact online offenders.

Basic descriptive analysis of the cohort using frequencies, percentages, means and standard deviations will be undertaken. Performing inferential analysis such as multi-nominal logistic regression analysis will enable us to identify the variables that predict outcomes occurring – for example, if the risk of recidivism is greater in online and contact offenders compared to online only offenders.

Regression analysis will also be used to estimate what influences (the predictors) online only / online and contact offending using independent variables. For example, socio-demographic and behavioural characteristics, risk assessment data, recidivism data and other available information.

200 cases.

Database analysis.