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The factor structure of static actuarial items: its relation to prediction
Howard E Barbaree1, Calvin M Langton, Edward J Peacock
1University of Toronto, Toronto, Ontario, Canada. howard_barbaree@camh.net
Sexual Abuse : a Journal of Research and Treatment
|August 29, 2006
Summary
This study analyzed sex offender risk assessment tools, identifying key factors like Antisocial Behavior and Child Sexual Abuse. These factors predict violent and sexual recidivism, respectively, aiding in risk management.
Area of Science:
- Forensic Psychology
- Criminology
- Risk Assessment
Background:
- Actuarial instruments are crucial for assessing sex offender recidivism risk.
- Existing tools like RASORR, Static-99, VRAG, SORAG, and MnSOST-R are widely used.
- Understanding the underlying components of these tools can refine risk prediction.
Purpose of the Study:
- To identify latent components within common actuarial risk assessment instruments for adult sex offenders.
- To examine the relationships between these components and specific recidivism types (violent vs. sexual).
Main Methods:
- Principal components analysis was applied to data from four actuarial instruments.
- The analysis utilized a dataset of 311 adult sex offenders, including child molesters and rapists.
- Statistical correlations were calculated between identified components and specific risk assessment tools.
Main Results:
- Six interpretable components emerged: Antisocial Behavior, Child Sexual Abuse, Persistence, Detached Predatory Behavior, Young and Single, and Male Victim(s).
- The Rapid Assessment of Sex Offender Risk for Recidivism (RASORR) correlated with Persistence.
- The Violence Risk Appraisal Guide (VRAG) and Sex Offender Risk Appraisal Guide (SORAG) correlated with Antisocial Behavior.
Conclusions:
- Antisocial Behavior emerged as a significant predictor of violent recidivism.
- Persistence and Child Sexual Abuse were significant predictors of sexual recidivism.
- These findings can inform more nuanced sex offender risk assessments and interventions.
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