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Castro D, Cardoso J, Araujo AS, Rodrigues AR, Ferreira F, Ferreira-Santos F, Ferreira TB. Topological properties of psychopathological networks of healthy and disordered individuals across mental disorders. J Affect Disord 2024; 366:226-233. [PMID: 39216639 DOI: 10.1016/j.jad.2024.08.168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 08/04/2024] [Accepted: 08/23/2024] [Indexed: 09/04/2024]
Abstract
The identification of psychopathological markers has been the focus of several scientific fields. The results were inconsistent due to lack of a clear nosology. Network analysis, focusing on the interactions between symptoms, provided important insights into the nosology of mental disorders. These interactions originate several topological properties that could constitute markers of psychopathology. One of these properties is network connectivity, which has been explored in recent years. However, the results have been inconsistent, and the topological properties of psychopathological networks remain largely unexplored and unknown. We compared several topological properties (i.e., connectivity, average path length, assortativity, average degree, modularity, global clustering) of psychopathological networks of healthy and disordered participants across depression (N = 2830), generalized anxiety (N = 13,463), social anxiety (N = 12,814), and obsessive-compulsive disorder (N = 16,426). Networks were estimated using Bayesian Gaussian Graphical Models. The Janson-Shannon measure of divergence was used to identify differences between the network properties. Network connectivity distinguished healthy and disordered participants' networks in all disorders. However, in depression and generalized anxiety, network connectivity was higher in healthy participants. The presence and number of motifs also distinguished the networks of healthy and disordered participants. Other topological properties (i.e., modularity, clustering, average path length and average degree) seem to be disorder-specific. The psychopathological significance of network connectivity must be clarified. Some topological properties of psychopathological networks are promising markers of psychopathology and may contribute to clarifying the nosology of mental disorders.
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Affiliation(s)
- Daniel Castro
- University of Maia, Maia, Portugal; Center for Psychology at University of Porto, Porto, Portugal.
| | - Joana Cardoso
- University of Maia, Maia, Portugal; Center for Psychology at University of Porto, Porto, Portugal
| | - Ana Sofia Araujo
- University of Maia, Maia, Portugal; Center for Psychology at University of Porto, Porto, Portugal
| | - Ana Rita Rodrigues
- University of Maia, Maia, Portugal; Center for Psychology at University of Porto, Porto, Portugal
| | | | - Fernando Ferreira-Santos
- Laboratory of Neuropsychophysiology, Faculty of Psychology and Education Sciences, University of Porto, Portugal
| | - Tiago Bento Ferreira
- University of Maia, Maia, Portugal; Center for Psychology at University of Porto, Porto, Portugal
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2
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Deng J, Shou Y, Wang MC, Allen JL, Gao Y, Hawes DJ. Core features of callous-unemotional traits: a cross-cultural comparison of youth in four countries. Eur Child Adolesc Psychiatry 2024; 33:2681-2693. [PMID: 38180536 DOI: 10.1007/s00787-023-02357-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 12/11/2023] [Indexed: 01/06/2024]
Abstract
With considerable debate concerning the impact of culture on the expression of callous-unemotional (CU) traits, it is unclear whether the core features of CU traits generalize to youth across cultures. This study aimed to examine whether cultural differences are reflected in the core features of CU traits and the associations among these features. Network analysis was employed to identify the core features and to examine the network structure of CU traits operationalized by the Inventory of Callous Unemotional traits (ICU) in four community youth samples from different nations (Australia, N = 190; the UK, N = 437; the USA, N = 330; China, N = 503). The item "Apologizes to people" was identified as a cross-cultural core feature in the ICU network with a greater centrality of this item compared to others in all four samples. In addition, some items were identified as culture-specific core features in the network, differing in their centrality across samples. The network structures of the youth self-report ICU items were moderately similar across samples, while the structures of parent-report items showed substantial differences. These findings have important implications for cross-cultural research on CU traits as well as practical implications for screening and treatment. The core features of ICU appear to be generalizable in youth across cultures, although cultural-specific manifestations should be noted.
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Affiliation(s)
- Jiaxin Deng
- Department of Psychology, Guangzhou University, Guangzhou Higher Education Mega Center Guangzhou, 230 Wai Huan Xi Road, 510006, Guangzhou, People's Republic of China
| | - Yiyun Shou
- Research School of Psychology, The Australian National University, Canberra, Australia
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Lloyd's Register Foundation Institute for the Public Understanding of Risk, National University of Singapore, Singapore, Singapore
| | - Meng-Cheng Wang
- Department of Psychology, Guangzhou University, Guangzhou Higher Education Mega Center Guangzhou, 230 Wai Huan Xi Road, 510006, Guangzhou, People's Republic of China.
| | | | - Yu Gao
- Department of Psychology, Brooklyn College and the Graduate Center of the City University of New York, New York, USA
| | - David J Hawes
- School of Psychology, University of Sydney, Sydney, Australia
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3
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López-Romero L, Andershed H, Romero E, Cervin M. In Search of Conceptual Clarity About the Structure of Psychopathic Traits in Children: A Network-Based Proposal. Child Psychiatry Hum Dev 2024:10.1007/s10578-023-01649-z. [PMID: 38236454 DOI: 10.1007/s10578-023-01649-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/04/2023] [Indexed: 01/19/2024]
Abstract
Psychopathic traits in childhood have been revealed as potential identifiers of risk, being predictive of later forms of behavioral maladjustment. Yet, it is still under debate how psychopathic traits in children should be best conceptualized and which are the core dimensions for construct definition and prediction. The present study aims to examine the structure of psychopathic traits in childhood, and its predictive value, by using a combination of traditional factor analysis and more recent network-based methods. Data on psychopathic traits, as measured by the Child Problematic Traits Inventory (CPTI), were collected in a large sample of children (n = 2454; 48.2% girls), aged 3 to 6 at the onset of the study (Mage = 4.26; SD = 0.91), who were followed-up one and two years later using parent- and teacher-reports. Results showed that psychopathic traits measured via CPTI are best conceptualized as five latent factors encompassing grandiosity, deceitfulness, callousness, impulsivity and need of stimulation, a result that converged across informants and time. Callousness and grandiosity emerged as central traits using network analysis of parent-reports, while deceitfulness was most central using teacher-reports. Finally, callousness, impulsivity and deceitfulness emerged as the best predictors of concurrent, prospective and stable conduct problems. These results provide a refined structure of psychopathic traits in children that better accounts for the core elements of the construct. Additional theoretical and practical implications will be discussed in terms of assessment, diagnostic classification and tailored prevention/intervention.
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Affiliation(s)
- Laura López-Romero
- Departamento de Psicología Clínica y Psicobiología, Facultad de Psicología, Universidade de Santiago de Compostela, Rua Xose María Suárez Núñez S/N, Campus Sur, 15782, Santiago de Compostela, Spain.
| | | | - Estrella Romero
- Departamento de Psicología Clínica y Psicobiología, Facultad de Psicología, Universidade de Santiago de Compostela, Rua Xose María Suárez Núñez S/N, Campus Sur, 15782, Santiago de Compostela, Spain
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4
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Wang H, Shuai P, Deng Y, Yang J, Shi Y, Li D, Yong T, Liu Y, Huang L. A correlation-based feature analysis of physical examination indicators can help predict the overall underlying health status using machine learning. Sci Rep 2022; 12:19626. [PMID: 36379988 PMCID: PMC9666446 DOI: 10.1038/s41598-022-20474-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 09/13/2022] [Indexed: 11/16/2022] Open
Abstract
As a systematic investigation of the correlations between physical examination indicators (PEIs) is lacking, most PEIs are currently independently used for disease warning. This results in the general physical examination having limited diagnostic values. Here, we systematically analyzed the correlations in 221 PEIs between healthy and 34 unhealthy statuses in 803,614 individuals in China. Specifically, the study population included 711,928 healthy participants, 51,341 patients with hypertension, 12,878 patients with diabetes, and 34,997 patients with other unhealthy statuses. We found rich relevance between PEIs in the healthy physical status (7662 significant correlations, 31.5%). However, in the disease conditions, the PEI correlations changed. We focused on the difference in PEIs between healthy and 35 unhealthy physical statuses and found 1239 significant PEI differences, suggesting that they could be candidate disease markers. Finally, we established machine learning algorithms to predict health status using 15-16% of the PEIs through feature extraction, reaching a 66-99% accurate prediction, depending on the physical status. This new reference of the PEI correlation provides rich information for chronic disease diagnosis. The developed machine learning algorithms can fundamentally affect the practice of general physical examinations.
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Affiliation(s)
- Haixin Wang
- grid.54549.390000 0004 0369 4060Sichuan Provincial Key Laboratory for Human Disease Gene Study, Center for Medical Genetics, Sichuan Academy of Medical Sciences & Sichuan Provincial People′s Hospital, University of Electronic Science and Technology of China, Chengdu, China ,grid.410646.10000 0004 1808 0950Research Unit for Blindness Prevention of Chinese Academy of Medical Sciences (2019RU026), Sichuan Academy of Medical Sciences, 32 The First Ring Road West 2, Chengdu, 610072 Sichuan China
| | - Ping Shuai
- grid.54549.390000 0004 0369 4060Health Management Center and Physical Examination Center of Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Yanhui Deng
- grid.54549.390000 0004 0369 4060Sichuan Provincial Key Laboratory for Human Disease Gene Study, Center for Medical Genetics, Sichuan Academy of Medical Sciences & Sichuan Provincial People′s Hospital, University of Electronic Science and Technology of China, Chengdu, China ,grid.410646.10000 0004 1808 0950Research Unit for Blindness Prevention of Chinese Academy of Medical Sciences (2019RU026), Sichuan Academy of Medical Sciences, 32 The First Ring Road West 2, Chengdu, 610072 Sichuan China
| | - Jiyun Yang
- grid.54549.390000 0004 0369 4060Sichuan Provincial Key Laboratory for Human Disease Gene Study, Center for Medical Genetics, Sichuan Academy of Medical Sciences & Sichuan Provincial People′s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Yi Shi
- grid.54549.390000 0004 0369 4060Sichuan Provincial Key Laboratory for Human Disease Gene Study, Center for Medical Genetics, Sichuan Academy of Medical Sciences & Sichuan Provincial People′s Hospital, University of Electronic Science and Technology of China, Chengdu, China
| | - Dongyu Li
- grid.54549.390000 0004 0369 4060Health Management Center and Physical Examination Center of Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Tao Yong
- grid.54549.390000 0004 0369 4060Medical Information Center of Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuping Liu
- grid.54549.390000 0004 0369 4060Health Management Center and Physical Examination Center of Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Lulin Huang
- grid.54549.390000 0004 0369 4060Sichuan Provincial Key Laboratory for Human Disease Gene Study, Center for Medical Genetics, Sichuan Academy of Medical Sciences & Sichuan Provincial People′s Hospital, University of Electronic Science and Technology of China, Chengdu, China ,grid.410646.10000 0004 1808 0950Research Unit for Blindness Prevention of Chinese Academy of Medical Sciences (2019RU026), Sichuan Academy of Medical Sciences, 32 The First Ring Road West 2, Chengdu, 610072 Sichuan China
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Longitudinal network structure of child psychopathy across development in chinese community children. CURRENT PSYCHOLOGY 2022. [DOI: 10.1007/s12144-022-03799-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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6
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Psychopathic Traits, Treatment Engagement, and Their Interrelation in Criminal Justice-Involved Boys: A Cross-Sectional Network Analysis. Res Child Adolesc Psychopathol 2022; 50:1589-1604. [DOI: 10.1007/s10802-022-00974-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/23/2022] [Indexed: 10/14/2022]
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7
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Garcia M, Rouchy E, Garcia M, Michel G. The network structure of psychopathic personality traits in a community sample of young adult females. Encephale 2022:S0013-7006(22)00101-4. [DOI: 10.1016/j.encep.2022.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 02/16/2022] [Accepted: 02/18/2022] [Indexed: 10/15/2022]
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8
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Network analysis of psychopathic traits among Chinese male offenders based on three self-report psychopathy measures. CURRENT PSYCHOLOGY 2022. [DOI: 10.1007/s12144-022-03205-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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9
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Wang MC, Deng J, Shou Y, Sellbom M. Cross-Cultural Examination of Psychopathy Network in Chinese and U.S. Prisoners. JOURNAL OF PSYCHOPATHOLOGY AND BEHAVIORAL ASSESSMENT 2022. [DOI: 10.1007/s10862-022-09960-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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10
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Symptom centrality and infrequency of endorsement identify adolescent depression symptoms more strongly associated with life satisfaction. J Affect Disord 2021; 289:90-97. [PMID: 33962367 DOI: 10.1016/j.jad.2021.02.064] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 12/21/2020] [Accepted: 02/27/2021] [Indexed: 11/24/2022]
Abstract
Although depression symptoms are often treated as interchangeable, some symptoms may relate to adolescent life satisfaction more strongly than others. To assess this premise, we first conducted a network analysis on the Mood and Feelings Questionnaire (MFQ) in a large (N = 1,059), cross-sectional sample of community adolescents (age M = 14.72 ± 1.79). The most central symptoms of adolescent depression, as indexed by strength, were self-hatred, loneliness, sadness, and worthlessness while the least frequently endorsed symptoms were self-hatred, anhedonia, feeling like a bad person, and feeling unloved. Moreover, the more central a depression symptom was in the network (i.e., higher strength), the more variance it shared with life satisfaction (r = 0.59, 95% CI: 0.27, 0.76). How frequently a symptom was endorsed was negatively associated with the variance symptoms shared with life satisfaction (r = -0.48, 95% CI: -0.63, -0.21). Cross-validated, prediction focused models found central symptoms were expected to predict more out of fold variance in life satisfaction than peripheral symptoms and frequently endorsed symptoms, but not the least frequently endorsed symptoms. These findings show certain depression symptoms may be more strongly associated with life satisfaction in adolescence and these symptoms can be identified by multiple symptom-level metrics. Limitations include use of cross-sectional data and utilizing a community sample. Better understanding which symptoms of depression share more variance with important outcomes like life satisfaction could help us develop a more fine-grained understanding of adolescent depression.
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Domínguez-Álvarez B, Romero E, López-Romero L, Isdahl-Troye A, Wagner NJ, Waller R. A Cross-Sectional and Longitudinal Test of the Low Sensitivity to Threat and Affiliative Reward (STAR) Model of Callous-Unemotional Traits Among Spanish Preschoolers. Res Child Adolesc Psychopathol 2021; 49:877-889. [PMID: 33624154 DOI: 10.1007/s10802-021-00785-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/07/2021] [Indexed: 10/22/2022]
Abstract
Despite advances in the theoretical and empirical literature, a better understanding of the etiological determinants of callous-unemotional (CU) traits is needed. In this study, we tested the hypotheses advanced by the Sensitivity to Threat and Affiliative Reward (STAR) model, a theoretical framework, which proposes that individual differences in two temperament dimensions, fearlessness and low affiliation, jointly contribute to the development of CU traits. Specifically, we examined the unique and interactive effects of fearlessness and low affiliation on CU traits, both cross-sectionally and longitudinally and within and across informants (teachers and parents) in a large community sample of Spanish preschoolers (N = 2467, 48.1% girls, M = 4.25 years; SD = 0.91). Both fearlessness and low affiliation were independently related to higher CU traits across models. Consistent with the purported relationships outlined in the STAR model, we also found that a significant interaction between fearlessness and low affiliation explained unique variance in CU traits. The results suggested that main and interactive effects were specific to CU traits and not to other related dimensions of psychopathic traits that are measurable in early childhood (i.e. grandiose-deceitfulness and impulse need of stimulation). Thus, we provide new empirical support to the hypotheses generated by the STAR model in relation to the development of CU traits. Fearlessness and low affiliation are potential targets of future child-focused interventions to prevent or treat the development of CU traits and childhood conduct problems.
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Affiliation(s)
- Beatriz Domínguez-Álvarez
- Department of Clinical Psychology and Psychobiology, University of Santiago de Compostela, Coruña, Spain.
| | - Estrella Romero
- Department of Clinical Psychology and Psychobiology, University of Santiago de Compostela, Coruña, Spain
| | - Laura López-Romero
- Department of Clinical Psychology and Psychobiology, University of Santiago de Compostela, Coruña, Spain
| | - Aimé Isdahl-Troye
- Department of Clinical Psychology and Psychobiology, University of Santiago de Compostela, Coruña, Spain
| | - Nicholas J Wagner
- Department of Psychological and Brain Sciences, Boston University, Boston, USA
| | - Rebecca Waller
- Department of Psychology, University of Pennsylvania, Philadelphia, USA
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Bogaerts S, Spreen M, Masthoff E, Jankovic M. Longitudinal Network Structure and Changes of Clinical Risk and Protective Factors in a Nationwide Sample of Forensic Psychiatric Patients. INTERNATIONAL JOURNAL OF OFFENDER THERAPY AND COMPARATIVE CRIMINOLOGY 2020; 64:1533-1550. [PMID: 32468885 PMCID: PMC7495686 DOI: 10.1177/0306624x20923256] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
In this study, we investigated network configurations of 14 Clinical risk and protective factors in a sample of 317 male forensic psychiatric patients across two time points: at the time of admission to the forensic psychiatric centers (T1) and at the time of unconditional release (T2). In terms of network structure, the strongest risk edge was between "hostility-violation of terms" at T1, and between "hostility-impulsivity" at T2. "Problem insight-crime responsibility" was the strongest protective edge, and "impulsivity-coping skills" was the strongest between-cluster edge, at both time points, respectively. In terms of strength centrality, "cooperation with treatment" had the highest strength centrality at both measurement occasions. This study expands the risk assessment field toward a better understanding of dynamic relationships between individual clinical risk and protective factors and points to the highly central risk and protective factors, which would be the best for future treatment targets.
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Affiliation(s)
- Stefan Bogaerts
- Tilburg University, the Netherlands
- Fivoor Science and Treatment Innovation (FARID), Rotterdam, the Netherlands
| | - Marinus Spreen
- NHL Stenden University of Applied Sciences, Leeuwarden, the Netherlands
| | - Erik Masthoff
- Fivoor Science and Treatment Innovation (FARID), Rotterdam, the Netherlands
| | - Marija Jankovic
- Tilburg University, the Netherlands
- Fivoor Science and Treatment Innovation (FARID), Rotterdam, the Netherlands
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Reale KS, Bouchard M, Lim YL, Cook AN, Hart SD. Are Psychopathic Traits Associated with Core Social Networks? An Exploratory Study in University Students. SOCIAL PSYCHOLOGY QUARTERLY 2020. [DOI: 10.1177/0190272520902105] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
In a sample of 480 university students, we examined associations between self-ratings of psychopathic traits, made using the Comprehensive Assessment of Psychopathic Personality (CAPP), the Psychopathic Personality Inventory: Short Form (PPI: SF), and self-ratings of the structure of their core social networks (i.e., best friends, intimates). Results indicated that higher self-ratings of domains (CAPP) and subscales (PPI: SF) related to interpersonal dominance, manipulation, poor attachment, and emotional regulation were associated with less connected core networks. We interpret the dominance and manipulation domain and subscale findings as preliminary evidence of a deliberate strategy to provide a more influential position within one’s social network. As for the associations with the attachment and emotional regulation domain and subscale findings, we suggest this could be reflective of deficits or a lack of desire both in establishing and maintaining long-term relationships.
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Affiliation(s)
| | | | - Yan L. Lim
- Simon Fraser University, Burnaby, BC, Canada
| | | | - Stephen D. Hart
- Simon Fraser University, Burnaby, BC, Canada
- University of Bergen, Norway
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Co-occurring psychopathy symptoms in offending boys: Do patterns of interactions among symptoms depend on levels of psychopathic tendencies? PERSONALITY AND INDIVIDUAL DIFFERENCES 2020. [DOI: 10.1016/j.paid.2019.109682] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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