The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Psychopathic Personality: Bridging the Gap Between Scientific Evidence and Public Policy
Abstract
Few psychological concepts evoke simultaneously as much fascination and misunderstanding as psychopathic personality, or psychopathy. Typically, individuals with psychopathy are misconceived as fundamentally different from the rest of humanity and as inalterably dangerous. Popular portrayals of are diverse and conflicting, ranging from uncommonly impulsive and violent criminal offenders to corporate figures who callously and skillfully manuever their way to the highest rungs of the social ladder. Despite this diversity of perspectives, a single well- validated measure of psychopathy, the Psychopathy Checklist-Revised (PCL-R; Hare, 1991; 2003), has come to dominate clinical and legal practice over recent years. The items of the PCL-R cover two basic content domains--an interpersonal-affective domain that encompasses core traits such as callousness and manipulativeness and an antisocial domain that entails disinhibition and chronic antisocial behavior. In most Western countries, the PCL-R and its derivatives are routinely applied to inform legal decisions about criminal offenders that hinge upon issues of dangerousness and treatability. In fact, clinicians in many cases choose the PCL-R over other, purpose-built risk-assessment tools to inform their opinions about what sentence offenders should receive, whether they should be indefinitely incarcerated as a dangerous offender or sexually violent predator, or whether they should be transferred from juvenile to adult court. The PCL-R has played an extraordinarily generative role in research and practice over the past three decades--so much so, that concerns have been raised that the measure has become equated in many minds with the psychopathy construct itself (Skeem & Cooke 2010a). Equating a measure with a construct may impede scientific progress because it disregards the basic principle that measures always imperfectly operationalize constructs and that our understanding of a construct is ever-evolving (Cronbach & Meehl, 1955). In virtually any domain, the construct-validation process is an incremental one that entails shifts in conceptualization and measurement at successive points in the process of clarifying the nature and boundaries of a hypothetical entity. Despite the predominance of the PCL-R measurement model in recent years, vigorous scientific debates have continued regarding what psychopathy is and what it is not. Should adaptive, positive-adjustment features (on one hand) and criminal and antisocial behaviors (on the other) be considered essential features of the construct? Are anxious and emotionally reactive people that are identified as psychopaths by the PCL-R and other measures truly psychopathic? More fundamentally, is psychopathy a unitary entity (i.e., a global syndrome with a discrete underlying cause), or is it rather a configuration of several distinguishable, but intersecting trait dimensions? Although these and other controversies remain unresolved, theory and research on the PCL-R and alternative measures have begun to clarify the scope and boundaries of the psychopathy construct. In the current comprehensive review, we provide an integrative descriptive framework--the triarchic model--to help the reader make sense of differing conceptualizations. The essence of this model is that alternative perspectives on psychopathy emphasize, to varying degrees, three distinct observable (phenotypic) characteristics: boldness (or fearless dominance), meanness, and disinhibition. The triarchic framework is helpful for clarifying and reconciling seemingly disparate historical conceptions, modern operationalizations, and contemporary research programs on psychopathy. Our review addresses what psychopathy is, whether variants or subtypes exist (i.e., primary and secondary, unsuccessful and successful), the sorts of causal influences that contribute to psychopathy, how early in development psychopathy can validly be identified, and how psychopathy relates to future criminal behavior and treatment outcomes. Despite controversies and nuances inherent in each of these topics, the current state of scientific knowledge bears clear implications for public policy. Policy domains range from whether psychopathic individuals should be held responsible for their criminal actions to whether employers should screen job candidates for tendencies toward psychopathy. In many cases, the findings we review converge to challenge common assumptions that underpin modern applications of psychopathy measures and to call for cautions in their use. For example, contemporary measures of psychopathy, including the PCL-R, appear to evidence no special powers in predicting violence or other crime. Instead, they are about as predictive as purpose-built violence-risk-assessment tools, perhaps because they assess many of the same risk factors as those broader-band tools. Specifically, the PCL-R and other psychopathy measures derive most of their predictive utility from their Factor
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Construct validity in psychological tests.
Cronbach, L. J., & Meehl, P. E. (1955) · Psychological Bulletin · doi:10.1037/h0040957 · Cited by 11,195
Adolescence-limited and life-course-persistent antisocial behavior: a developmental taxonomy
Moffitt, T. E. (1993) · Psychological Review · doi:10.1037/0033-295x.100.4.674 · Cited by 9,987
Hutchinson, G. E. (1957) · Cold Spring Harbor Symposia on Quantitative Biology · doi:10.1101/sqb.1957.022.01.039 · Cited by 6,228
Gray, J. A. (1982) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00013066 · Cited by 4,477 · cited 1×
“He saw each variant as reflecting an extreme temperament, with either impaired fear sensitivity or impaired reward sensitivity (see J. A. Gray, 1982).”
On the practice of dichotomization of quantitative variables.
MacCallum, R. C., Zhang, S., Preacher, K. J., & Rucker, D. D. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.1.19 · Cited by 3,538
Anderson, C. A., Shibuya, A., Ihori, N., Swing, E. L., Bushman, B. J., Sakamoto, A., Rothstein, H. R., & Saleem, M. (2010) · Psychological Bulletin · doi:10.1037/a0018251 · Cited by 2,048
Classification for Effective Rehabilitation: Rediscovering Psychology
ANDREWS, D. A., BONTA, J., & HOGE, R. D. (1990) · Criminal Justice and Behavior · doi:10.1177/0093854890017001004 · Cited by 1,895
The Structure of Common Mental Disorders
Krueger, R. F. (1999) · Archives of General Psychiatry · doi:10.1001/archpsyc.56.10.921 · Cited by 1,881
Adolescent Brain Development: A Period of Vulnerabilities and Opportunities. Keynote Address
DAHL, R. E. (2004) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1308.001 · Cited by 1,667
Krueger, R. F., Hicks, B. M., Patrick, C. J., Carlson, S. R., Iacono, W. G., & McGue, M. (2002) · Journal of Abnormal Psychology · doi:10.1037/0021-843x.111.3.411 · Cited by 1,378
Self-citation
Cited by
Bloom, P. (2017) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2016.11.004 · Cited by 420
Patrick, C. J., & Drislane, L. E. (2015) · Journal of Personality · doi:10.1111/jopy.12119 · Cited by 365
Self-citationAre forensic experts biased by the side that retained them?
Murrie, D. C., Boccaccini, M. T., Guarnera, L. A., & Rufino, K. A. (2013) · Psychological Science · doi:10.1177/0956797613481812 · Cited by 286
Boduszek, D., Debowska, A., Dhingra, K., & DeLisi, M. (2016) · Journal of Criminal Justice · doi:10.1016/j.jcrimjus.2016.02.004 · Cited by 84
Vieira, J. B., Tavares, T. P., Marsh, A. A., & Mitchell, D. G. V. (2017) · Human Brain Mapping · doi:10.1002/hbm.23467 · Cited by 43
Metadata
- Authors
- Skeem, J. L., Polaschek, D. L. L., Patrick, C. J., & Lilienfeld, S. O.
- Venue
- Psychological Science in the Public Interest
- Publisher
- SAGE Publications
- Published
- 2011-12
- Volume
- 12
- Issue
- 3
- Pages
- 95-162
- ISSN
- 1529-1006 (ISSN-L)
- 2160-0031
- OpenAlex
- W2156566037
- Cited by
- 582
- References
- 28
- FWCI
- 34.70
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Psychopathic Personality: Bridging the Gap Between Scientific Evidence and Public Policy. https://app.cochat.ai/papers/10.1177/1529100611426706
- The paper
- Skeem, J. L., Polaschek, D. L. L., Patrick, C. J., & Lilienfeld, S. O. (2011). Psychopathic Personality: Bridging the Gap Between Scientific Evidence and Public Policy. Psychological Science in the Public Interest. https://doi.org/10.1177/1529100611426706
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.