Online child sexual exploitation (OCSE) continues to rise and evolve with advances in technology. Consequently, it is essential for police involved in the investigation and management of OCSE to effectively prioritise responses and allocate resources to those who pose the greatest ongoing threat to children. Understanding typical recidivism rates across different OCSE sub-types and identifying reliable risk assessment methods to identify OCSE cases at greatest risk of sexual reoffending is crucial to this process.

While research indicates low recidivism rates among individuals involved in accessing and distributing child sexual abuse material (CSAM), little is known about the reoffending patterns among people who use online and digital technology to groom children or produce CSAM. There are various strategies available, but it is unclear which strategy is best to predict reoffending among each OCSE sub-type.