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Unveiling common psychological characteristics of proneness to aggression and general psychopathology in a large community youth cohort

Authors :
Ting Yat Wong
Zhiqian Fang
Charlton Cheung
Corine S. M. Wong
Yi Nam Suen
Christy L. M. Hui
Edwin H. M. Lee
Simon S. Y. Lui
Sherry K. W. Chan
Wing Chung Chang
Pak Chung Sham
Eric Y. H. Chen
Source :
Translational Psychiatry, Vol 13, Iss 1, Pp 1-9 (2023)
Publication Year :
2023
Publisher :
Nature Publishing Group, 2023.

Abstract

Abstract Elevated aggression in individuals with psychiatric disorders is frequently reported yet aggressive acts among people with mental illness are often intertwined with proneness to aggression and other risk factors. Evidence has suggested that both general psychopathology and proneness to aggression may share common psychological characteristics. This study aims to investigate the complex relationship between general psychopathology, proneness to aggression, and their contributing factors in community youth. Here, we first examined the association between proneness to aggression and the level of general psychopathology in 2184 community youths (male: 41.2%). To identify common characteristics, we trained machine learning models using LASSO based on 230 features covering sociodemographic, cognitive functions, lifestyle, well-being, and psychological characteristics to predict levels of general psychopathology and proneness to aggression. A subsequent Gaussian Graph Model (GGM) was fitted to understand the relationships between the general psychopathology, proneness to aggression, and selected features. We showed that proneness to aggression was associated with a higher level of general psychopathology (discovery: r = 0.56, 95% CI: [0.52–0.59]; holdout: r = 0.60, 95% CI: [0.54–0.65]). The LASSO model trained on the discovery dataset for general psychopathology was able to predict proneness to aggression in the holdout dataset with a moderate correlation coefficient of 0.606. Similarly, the model trained on the proneness to aggression in the discovery dataset was able to predict general psychopathology in the holdout dataset with a correlation coefficient of 0.717. These results suggest that there is substantial shared information between the two outcomes. The GGM model revealed that isolation and impulsivity factors were directly associated with both general psychopathology and proneness to aggression. These results revealed shared psychological characteristics of general psychopathology and proneness to aggression in a community sample of youths.

Details

Language :
English
ISSN :
21583188
Volume :
13
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Translational Psychiatry
Publication Type :
Academic Journal
Accession number :
edsdoj.934b8b2e55b4b658f364732b664ca64
Document Type :
article
Full Text :
https://doi.org/10.1038/s41398-023-02538-8