AbstractsPsychology

Examination of the use of self-report psychometrics within sexual offender treatment and in prediction of reoffending

by Helen Catherine Wakeling




Institution: University of Birmingham
Department: School of Psychology
Year: 2015
Keywords: BF Psychology; HN Social history and conditions. Social problems. Social reform
Record ID: 1390685
Full text PDF: http://etheses.bham.ac.uk/5599/


Abstract

This thesis aims to examine the utility of self-report psychometrics within delivery of sexual offender treatment. The focus is particularly on the ability of self-report psychometrics to discriminate between recidivists and non-recidivists and to predict recidivism outcome. Its findings are especially relevant to the National Offender Management Service (NOMS) who deliver sexual offender treatment across custodial and community settings in England and Wales. Chapter 1 provides an overview of the literature on self-report psychometrics and their use within sexual offender treatment and risk assessment. Chapter 2 provides exploratory analyses into the relationship between a large battery of pre and post self-report psychometrics and recidivism outcome on a large sample of sexual offenders. Chapter 3 examines the predictive power of a selection of psychometric variables and static variables using prognostic modelling techniques. Chapter 4 examines treatment change as measured psychometrically using clinically significant change methodology and its relationship to recidivism outcome. Chapter 5 provides a summary of the previous chapters’ findings and recommends further analyses and investigation. Chapter 6 attempts to generate a new shortened psychometric battery with good validity. Chapter 7 concludes the thesis with an overview, synthesis and discussion of the findings, limitations, practical implications and future research directions. The thesis found psychometrics to have limited discriminant and predictive validity, and in general static factors were better predictors of recidivism than psychometrics.