Investigation and Comparison of Networks of Psychopathic Traits in Psychiatric Inpatients and University Students

• Published in: Psychiatria Danubina Vol. 34; no. Suppl 8; p. 207
• Main Authors: Sunakawa, Takuyoshi, Briganti, Giovanni
• Format: Journal Article
• Language: English
• Published: 01.09.2022
• ISSN: 0353-5053

The Levenson Self-Report Psychopathy Scale (LSRPS) is a psychometric tool composed of 26 items to assess psychopathic traits. This study aims to perform a network analysis of this scale in a large sample composed of 100 hospitalized psychiatric patients and 256 French-speaking Belgian university students in medicine and to compare the network structure. We estimated a regularized partial correlation network for the 26 items of the questionnaire. Node predictability is used to assess the connectivity of items. The network comparison test (NCT) and statistical inference on sum scores are conducted to compare networks from the inpatients and the university students. The networks composed of LSRPS are mostly connected positively, but some negative interconnections were observed in both inpatients and university students, and node connectivity varies. Although the scores from inpatients are substantially higher than those of university students, network analysis didn't show any statistical difference in the overall connectedness. Network analysis is a valuable tool for exploring psychopathic traits and offers new insight into how they interact. In the network estimation, we concluded that the two domains of psychopathy are interrelated. This interconnectivity was observed in both subject groups. We hypothesize that such interconnectivity was present because environmental and genetic factors are intricately intertwined in the appearance of primary and secondary psychopathy. Meanwhile, although inpatients may have higher scores of psychopathic traits, those traits' connectedness isn't different from that of the general population. This finding aligns well with the theory of hysteresis in network analysis, which states that the connections among components of mental disorders do not disappear or reappear over time, but their importance may vary. Further studies may replicate our findings using different sample groups.The Levenson Self-Report Psychopathy Scale (LSRPS) is a psychometric tool composed of 26 items to assess psychopathic traits. This study aims to perform a network analysis of this scale in a large sample composed of 100 hospitalized psychiatric patients and 256 French-speaking Belgian university students in medicine and to compare the network structure. We estimated a regularized partial correlation network for the 26 items of the questionnaire. Node predictability is used to assess the connectivity of items. The network comparison test (NCT) and statistical inference on sum scores are conducted to compare networks from the inpatients and the university students. The networks composed of LSRPS are mostly connected positively, but some negative interconnections were observed in both inpatients and university students, and node connectivity varies. Although the scores from inpatients are substantially higher than those of university students, network analysis didn't show any statistical difference in the overall connectedness. Network analysis is a valuable tool for exploring psychopathic traits and offers new insight into how they interact. In the network estimation, we concluded that the two domains of psychopathy are interrelated. This interconnectivity was observed in both subject groups. We hypothesize that such interconnectivity was present because environmental and genetic factors are intricately intertwined in the appearance of primary and secondary psychopathy. Meanwhile, although inpatients may have higher scores of psychopathic traits, those traits' connectedness isn't different from that of the general population. This finding aligns well with the theory of hysteresis in network analysis, which states that the connections among components of mental disorders do not disappear or reappear over time, but their importance may vary. Further studies may replicate our findings using different sample groups.