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The relations of psychotic-like experiences (PLEs) and depressive symptoms and the bias of depressive symptoms during the clustering among Chinese adolescents: Findings from the network perspective

透视图(图形) 抑郁症状 心理学 中心性 临床心理学 精神科 聚类分析 认知 计算机科学 人工智能 机器学习 数学 组合数学
作者
Peng Cheng,Zhening Liu,Meng Sun,Wen Zhang,Rui Guo,Aimin Hu,Yicheng Long
出处
期刊:Journal of Affective Disorders [Elsevier BV]
卷期号:350: 867-876 被引量:3
标识
DOI:10.1016/j.jad.2024.01.180
摘要

There are rare studies about the network structure of psychotic-like experiences (PLEs) and depressive symptoms among adolescents. Studies have widely acknowledged that PLEs in adolescents confer a higher risk of depressive symptoms, but the complex interactions remain inadequately understood. Our study aimed to examine the hierarchy and inter-associations of PLEs and depressive symptoms in a large adolescent sample from the network analysis perspective. A total of 5008 Chinese adolescents were enrolled in our sample. Community Assessment of Psychic Experiences-42 (CAPE-42) was applied to build the network. Centrality indexes were calculated to represent the significance of nodes in the network. Community detection was conducted to figure out the specific clustering of nodes. Demographic information was collected for the sub-network comparisons. Accuracy and stability of the network were also tested. "Failure", "External control", and "Lack of activity" were the most central nodes. The main bridge nodes linking PLEs and depressive symptoms were "Failure", "Guilty", and "No future". Positive PLE "Odd looks" and negative PLE "Unable to terminate" are the two PLEs that were most relevant to depressive nodes. Community detection further demonstrated the bias of depressive nodes in the data-driven clustering. Comparative sub-network analysis suggested that age was the only demographic factor related to the current network. In this study of a large adolescent sample, we first demonstrated the network structure and specific clustering preference of PLEs and depressive symptoms. Our findings may enhance the understanding of the relationship between PLE and depressive symptoms.
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