Yu Xinle, Zhang Xuanzhi, Wu Kusheng, Xu Zhenqiang, Liang Zhiya, Wen Wanyi, Wang Dinghui, Huang Yanhong
Mental Health Center of Shantou University, Shantou, Guangdong, China.
Shantou University Medical College-Faculty of Medicine of University of Manitoba Joint Laboratory of Biological Psychiatry, Shantou, Guangdong, China.
Child Adolesc Psychiatry Ment Health. 2025 Jul 26;19(1):89. doi: 10.1186/s13034-025-00947-9.
Childhood loneliness is a significant public health concern, particularly in China due to distinct sociocultural contexts. Prior research often overlooks symptom-level interactions, limiting the precision of targeted interventions. This study applied network-based methodologies to clarify the structure of loneliness, identify intervention targets, and examine the roles of psychological factors and family socioeconomic status (SES).
A total of 2,593 school-age children from Shantou, China, were assessed for loneliness, depressive symptoms, anxiety symptoms, ADHD symptoms, perceived social support, hope, and family SES. In silico interventions using the NodeIdentifyR algorithm (NIRA) within an Ising model identified effective targets for prevention and intervention. A Graphical Gaussian Model (GGM) mapped loneliness within a broader psychological context, and a Moderated Network Model (MNM) tested SES influences.
Lack of friendship and peer acceptance emerged as key targets for prevention and intervention, respectively. Loneliness functioned as both a central and bridging symptom in the psychological network, closely connected to other psychological variables. Higher SES buffered its associations with depressive symptoms and hope.
Early, peer-focused, and context-sensitive strategies may more effectively support children's well-being. This study is the first to apply network analysis and in silico intervention methods, providing novel perspectives and strategies for the prevention and intervention of childhood loneliness among Chinese children.
儿童期孤独是一个重大的公共卫生问题，在中国尤其如此，因为其社会文化背景独特。先前的研究往往忽视症状层面的相互作用，限制了针对性干预措施的精准度。本研究应用基于网络的方法来阐明孤独的结构、确定干预目标，并考察心理因素和家庭社会经济地位（SES）的作用。
对来自中国汕头的2593名学龄儿童进行了孤独感、抑郁症状、焦虑症状、注意力缺陷多动障碍（ADHD）症状、感知到的社会支持、希望和家庭SES的评估。在伊辛模型中使用NodeIdentifyR算法（NIRA）进行的计算机模拟干预确定了预防和干预的有效目标。图形高斯模型（GGM）在更广泛的心理背景下描绘了孤独感，而调节网络模型（MNM）则测试了SES的影响。
缺乏友谊和同伴接纳分别成为预防和干预的关键目标。孤独感在心理网络中既是核心症状又是桥梁症状，与其他心理变量紧密相连。较高的SES缓冲了其与抑郁症状和希望的关联。
早期、以同伴为重点且因地制宜的策略可能更有效地促进儿童的幸福感。本研究首次应用网络分析和计算机模拟干预方法，为中国儿童童年期孤独的预防和干预提供了新的视角和策略。
