Vincent Samuel R, Bate George, Leedom Liane J, Miller Steven A, Kossson David S
Department of Psychology, Rosalind Franklin University of Medicine and Science, 3333 N Green Bay Rd, North Chicago, IL 60064.
Department of Psychology, University of Bridgeport, 126 Park Ave, Bridgeport, CT 06604.
Pers Individ Dif. 2025 Nov;246. doi: 10.1016/j.paid.2025.113312. Epub 2025 Jun 9.
Network analyses offer a viable alternative approach to understanding the nature of mental disorders. The current study was conducted to advance our understanding of the network underlying of Psychopathy Checklist-Revised (PCL-R)-assessed traits in 1698 incarcerated adult males. First, in order to test the robustness of past findings, a generalized Potts network was constructed to identify the most central item in a unidimensional psychopathy network. Consistent with some previous studies, analyses demonstrated Callous/Lack of Empathy was the most central psychopathy trait. To investigate a multidimensional network solution of psychopathy, we utilized exploratory graph analysis to organize the PCL-R items into separate clusters. The analysis yielded a four-cluster solution that closely resembled the commonly observed four-factor solution of psychopathy. Analyses demonstrated that Callous/Lack of Empathy also had the highest bridge centrality, suggesting these features are critical to linking the different clusters in the network together. These findings provide additional evidence of the importance of unempathic and callous behavior to both unidimensional and multidimensional network accounts of psychopathy.
网络分析为理解精神障碍的本质提供了一种可行的替代方法。本研究旨在增进我们对1698名成年男性在押人员中,经《精神病态核查表修订版》(PCL-R)评估的特质背后的网络的理解。首先,为了检验以往研究结果的稳健性,构建了一个广义Potts网络,以识别一维精神病态网络中最核心的项目。与之前的一些研究一致,分析表明冷酷/缺乏同理心是最核心的精神病态特质。为了研究精神病态的多维网络解决方案,我们利用探索性图分析将PCL-R项目组织成不同的集群。分析得出了一个四集群解决方案,与常见的精神病态四因素解决方案非常相似。分析表明,冷酷/缺乏同理心也具有最高的桥梁中心性,这表明这些特征对于将网络中的不同集群联系在一起至关重要。这些发现为缺乏同理心和冷酷行为在精神病态的一维和多维网络解释中的重要性提供了更多证据。