A comparison of a self-report measure of psychopathy with the psychopathy checklist-revised in a UK sample of offenders

Abstract

Psychopathy is an extremely important construct in both forensic psychology and psychiatry. Recently, there have been attempts to produce self-report questionnaires of psychopathic traits. We examined the relationship between such a self-report measure of psychopathy [(Psychopathic Personality Inventory – Revised (PPI-R), Lilienfeld, S.O., & Widows, M.R. (2005). Psychopathic Personality Inventory – Revised. Lutz, FL: Psychological Assessment Resources, Inc.] and an assessment of psychopathy by a third party using the Psychopathy Checklist – Revised (PCL-R; R.D. Hare, 2003. Hare Psychopathy Checklist-Revised (PCL-R) 2nd Edition. Toronto: ON: Multi-Health Systems.). A strong relationship (r = .54) was found between the two measures of psychopathy in a sample of male offenders. However, the factors underpinning the PPI-R and the factors underpinning the PCL-R did not show any obvious correspondence. It is suggested that the PCL-R and the PPI-R measure different conceptualisations of psychopathy and that one cannot be used as a substitute for the other.

Keywords:

• psychopathy
• offending behaviour
• PCL-R

Acknowledgement

We would like to thank an anonymous reviewer for suggesting possible reasons (e.g. semantic aphasia) for our results.

Notes

1. For short-hand, we will refer to these instruments as the PCL under the assumption that they are measuring the same concepts at both total and factor scores (Guy & Douglas, 2006).

2. Unfortunately, the individual scores from the two raters were not available to us to perform an analysis of inter-rater reliability.

3. In the present sample, the correlation between Factor 1 and Factor 2 was r = .49 (p < .001).

4. Malterer et al. (2010) also present data from an undergraduate sample, but this is not considered here as we only had an offender sample.

5. Data on the associations between the facet scores of the PCL-R (and PCL:SV) and the PPI were kindly supplied to us by Malterer et al. (2010). The results do not seem to form a consistent pattern, either across the studies within Malterer et al. (2010) or with the present data. Namely, Malterer et al. (2010) did not find that Facet 4 was most associated with PPI-I. However, we note that they did not present this data in the original paper due to low levels of reliability. Clearly, our finding of an association between Facet 4 and PPI-I may be a Type 1 error, and further study is needed before this result should be accepted.