The Effects of Psychopathy Facets on Treatment Involvement

Anna Vasaturo; Sonja Krstic; Raymond A Knight

doi:10.1177/0306624X241270593

The current study explored the relations between patient characteristics and psychopathic traits in predicting treatment involvement. We rated treatment involvement using detailed archival clinical files of 218 individuals committed to the Massachusetts Treatment Center (MTC). Psychopathy Checklist-Revised (PCL-R) scores had been rated from a previous study on the same sample. Overall, PCL-R Facets 2 and 4 significantly predicted decreases in treatment involvement, suggesting the characteristics associated with these facets have the most disruptive effects on treatment involvement. Exploratory analyses were also conducted assessing the relations between the PCL-R facets and the individual treatment involvement components. Whereas Facet 2 significantly predicted lower levels in all three individual treatment involvement components, Facet 4 only significantly predicted lower levels in two, highlighting the differentiating effects of these facets. Identifying the components that have either positive or negative effects on treatment involvement can allow clinicians to tailor treatments to optimize treatment involvement and outcome.The current study explored the relations between patient characteristics and psychopathic traits in predicting treatment involvement. We rated treatment involvement using detailed archival clinical files of 218 individuals committed to the Massachusetts Treatment Center (MTC). Psychopathy Checklist-Revised (PCL-R) scores had been rated from a previous study on the same sample. Overall, PCL-R Facets 2 and 4 significantly predicted decreases in treatment involvement, suggesting the characteristics associated with these facets have the most disruptive effects on treatment involvement. Exploratory analyses were also conducted assessing the relations between the PCL-R facets and the individual treatment involvement components. Whereas Facet 2 significantly predicted lower levels in all three individual treatment involvement components, Facet 4 only significantly predicted lower levels in two, highlighting the differentiating effects of these facets. Identifying the components that have either positive or negative effects on treatment involvement can allow clinicians to tailor treatments to optimize treatment involvement and outcome.