Network analysis of psychopathy in forensic patients
The question of which features represent the most central components of psychopathy remains unresolved and is the subject of considerable debate. Network analysis, which is a relatively new way to conceptualize mental disorders that emphasizes complex causal systems, provides a means to graphically...
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Contributors: | ; |
Format: | Electronic Article |
Language: | English |
Published: |
2018
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In: |
Journal of abnormal psychology
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Online Access: |
Volltext (Verlag) Volltext (doi) |
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Check availability: | HBZ Gateway |
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100 | 1 | |a Preszler, Jonathan |e VerfasserIn |4 aut | |
245 | 1 | 0 | |a Network analysis of psychopathy in forensic patients |c Jonathan Preszler, David K. Marcus, John F. Edens [und ein weiterer] |
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520 | |a The question of which features represent the most central components of psychopathy remains unresolved and is the subject of considerable debate. Network analysis, which is a relatively new way to conceptualize mental disorders that emphasizes complex causal systems, provides a means to graphically and quantitatively describe the centrality of the various symptoms of a disorder. We applied association and adaptive LASSO networks on two samples of forensic patients. The first sample included forensic inpatients (N = 277) who were administered the Psychopathy Checklist—Revised (Hare, 2003), and the second sample included patients who previously had been civilly committed (N = 1136), who were administered the Psychopathy Checklist: Screening Version (Hart, Cox, & Hare, 1995). The models indicated the items on the affective facet are highly central across both samples and methods, and the item 'lack of remorse' was especially central to the networks. Conversely, interpersonal, lifestyle, and antisocial facets generally resulted in low centrality in the models of both samples. Thus, the models lend support to the importance of affective deficits as the primary feature of psychopathy when psychopathy is assessed using the Hare Psychopathy Checklist measures. | ||
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