Assessment of treatment change for sexual offenders against children: comparing different methodologies based on psychometric self-report
Degree GrantorUniversity of Canterbury
Degree NameMaster of Science
Communities seek success when it comes to preventing the sexual abuse of children. Thus, how best to measure treatment gains for incarcerated offenders and how those gains are linked to reductions in recidivism are important topics for research. This study examines the relationship between psychometric changes and recidivism in a sample of 495 sex offenders who completed treatment in the prison-based Kia Marama treatment programme in Rolleston prison, New Zealand. The specific goals of this study were threefold. Firstly; to characterise offender progress overall on the administered psychometric battery in terms of five different methods of calculating change. Two methods of calculating clinically significant change were employed. Firstly, change was calculated using the Jacobson and Truax (1991) method of establishing a cut off score based on normative data for each measure. Secondly change was defined as clinically significant when the post treatment score fell 1SD away from the pre-treatment mean in the direction of functionality, a methodology used by Wakeling, Beech, and Freemantle (2013). Two methods of calculating reliable change were then employed. Firstly the Jacobson, Follette, Revenstorf, et al. (1984) calculation adopted by Wakeling et al. (2013) was applied, followed by the more stringent formula proposed by Christensen and Mendoza (1986) which takes account of the standard error of difference. Finally, residual change scores were calculated, replicating the change methodology adopted by Beggs and Grace (2011). The second goal of this study was to compare the five different methodologies above for assessing change based on participants’ scores on the administered psychometric battery. The third and final goal was to determine which of the five identified methods of measuring change demonstrated the strongest correlation with recidivism. Measures of clinically significant change were found to be significantly correlated with recidivism. However, this was not necessarily true when change was defined as both reliable and clinically significant. Results indicated that the Wakeling et al. (2013) method of calculating clinically significant change outperformed all of the others in regards to predicting recidivism. Overall, the present results support the use of self-report psychometrics in measuring treatment change and predicting recidivism.