Song Xiaoxiao, Li Yaoyao, Wang Xiaoyan, Wang Xindi, Bao Yanping, Zhang Dianshun, Li Zhiqiang, Meng Chenxia, Wang Changming, Zhang Xiujun, Lyu Shaobo
Tangshan Key Laboratory of Mental Health and Cognitive Neuroscience, School of Psychology and Mental Health, North China University of Science and Technology, Hebei, China.
Library, North China University of Science and Technology, Hebei, China.
Depress Anxiety. 2025 May 9;2025:2309327. doi: 10.1155/da/2309327. eCollection 2025.
Adolescence is a high-risk period for depression, especially after the COVID-19 pandemic, when adolescent depression has become increasingly severe. This study employs network analysis to identify core symptoms at various stages. It explores the differences in depression symptom characteristics among Chinese adolescents of different genders during elementary, middle, and high school periods. A convenience sampling method was used to select 1553 students from various elementary, middle, and high schools in a specific city as participants. Their depression symptoms were assessed using the The Patient Health Questionnaire-9 (PHQ-9) depression screening scale. Using graph theory-based network analysis, this study constructs a depression symptom model via a correlation network and evaluates symptom nodes and their interconnections. The study found significant differences in the detection rates of depression symptoms among the three grade levels ( < 0.001). However, no significant differences were found between male and female students in the detection rates and PHQ-9 scores ( > 0.05). Through network analysis, this study identified the network changes in depression symptoms among Chinese adolescents of different grades and genders. The results show that "depressed mood" is the core symptom in the elementary and high school groups. At the same time, "fatigue" is the central factor affecting the depression network in the middle school group. Negative emotions and fatigue are the primary symptoms that run through the entire adolescent depression network. This study reveals the heterogeneity of depression symptom networks among adolescent groups of different genders and grades, providing a theoretical basis for personalized interventions for adolescent depression in the future.
青春期是抑郁症的高发期,尤其是在新冠疫情之后,青少年抑郁症愈发严重。本研究采用网络分析来识别不同阶段的核心症状。它探讨了中国不同性别青少年在小学、初中和高中阶段抑郁症状特征的差异。采用便利抽样法,从某特定城市的各所小学、初中和高中选取1553名学生作为参与者。使用患者健康问卷-9(PHQ-9)抑郁筛查量表评估他们的抑郁症状。本研究基于图论的网络分析,通过相关网络构建抑郁症状模型,并评估症状节点及其相互联系。研究发现三个年级水平的抑郁症状检出率存在显著差异(<0.001)。然而,男女生在检出率和PHQ-9得分方面未发现显著差异(>0.05)。通过网络分析,本研究确定了不同年级和性别的中国青少年抑郁症状的网络变化。结果表明,“情绪低落”是小学组和高中组的核心症状。同时,“疲劳”是影响初中组抑郁网络的核心因素。负面情绪和疲劳是贯穿整个青少年抑郁网络的主要症状。本研究揭示了不同性别和年级青少年群体抑郁症状网络的异质性,为未来青少年抑郁症的个性化干预提供了理论依据。