Prediction of reoffending risk in men convicted of sexual offences: development and validation of novel and scalable risk assessment tools (OxRIS)

• Published in: Journal of criminal justice 2022-09, Vol.82, p.101935-101935, Article 101935
• Main Authors: Yu, Rongqin, Molero, Yasmina, Långström, Niklas, Fanshawe, Thomas, Yukhnenko, Denis, Lichtenstein, Paul, Larsson, Henrik, Fazel, Seena
• Format: Article
• Language: English
• Subjects: Big data; Calibration; Clinical algorithms; Crime; Criminal justice; Criminal justice system; Decision making; Discrimination; Evaluation; Forensic psychiatry; Internet; Medical screening; Men; Mental health; Mental health services; Offenses; Prediction model; Prediction models; Recidivism; Risk assessment; Sex crimes; Sex offenders; Sexual development; Sexual offending; Tests
• ISSN: 0047-2352; 1873-6203
• DOI: 10.1016/j.jcrimjus.2022.101935

Current risk assessment tools have a limited evidence base with few validations, poor reporting of outcomes, and rarely include modifiable factors. We examined a national cohort of men convicted of sexual crimes in Sweden. We developed prediction models for three outcomes: violent (including sexual), any, and sexual reoffending. We used Cox proportional hazard regression to develop multivariable prediction models and validated these in an external sample. We reported discrimination and calibration statistics at prespecified cut-offs. We identified 16,231 men convicted of sexual offences, of whom 14.8% violently reoffended during a mean follow up of 38 months, 31.4% for any crime (34 months), and 3.6% for sexual crimes (42 months). Models for violent and any reoffending showed good discrimination and calibration. At 1, 3, and 5 years, the area under the curve (AUC) was 0.75–0.76 for violent reoffending and 0.74–0.75 for any reoffending. The prediction model for sexual reoffending showed modest discrimination (AUC = 0.67) and good calibration. We have generated three simple and web-based risk calculators, which are freely available. Scalable evidence-based risk assessment tools for sexual offenders in the criminal justice system and forensic mental health could assist decision-making and treatment allocation by identifying those at higher risk, and screening out low risk persons. •Prediction models for violent and any reoffending in sex offenders were developed.•The new tools demonstrated good calibration, particularly at lower risk levels.•Discrimination was good for violent and any reoffending.•These models were translated into freely available online risk calculators.