Li Tingting, Zhang Dan, Jiang Tangjun, Che Wanyu, Zhang Yi, Wan Yuhui, Tao Fangbiao, Tao Shuman, Wu Xiaoyan
Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
MOE Key Laboratory of Population Health Across Life Cycle, No 81 Meishan Road, Hefei, 230032, Anhui, China.
BMC Psychiatry. 2025 Jul 1;25(1):598. doi: 10.1186/s12888-025-07036-3.
This study employed network analysis to investigate the comorbidity model between depression and anxiety among Chinese adolescents during the normalization phase of COVID-19 pandemic prevention and control.
From October to December 2021, a total of 22 868 adolescents were selected from 27 schools in 8 cities of China by multistage cluster sampling. Depressive symptoms and anxiety symptoms of adolescents were evaluated by the Patient Health Questionnaire 9 (PHQ-9) and the Generalized Anxiety Disorder scale 7 (GAD-7), respectively. The network structure between depression and anxiety was explored using the Extended Bayesian Information Criterion (EBIC) and the graphical Least Absolute Shrinkage and Selection Operator (LASSO) method. The centrality of nodes, stability, accuracy, central symptoms, bridging symptoms, and network comparison were analyzed.
In the present study, 7 236 (31.6%) participants reported with depression-anxiety comorbidity. The obtained network model was highly stable. The edges between 'Control worry' and 'Too much worry', between 'Restless' and 'Irritable', and between 'Anhedonia' and 'Sad mood' were the three strongest positive edges in the anxiety and depression community. The edges between 'Motor' and 'Restless', between 'Guilt' and 'Nervous', and between 'Suicide' and 'Afraid' were the three strongest positive edges in the comorbidity community. 'Sad mood' and 'Too much worry' were the core symptoms within the 'depression' network and 'anxiety' network. 'Nervous', 'Guilt', and 'Restless' were three crucial bridge symptoms linking the comorbidity of depression and anxiety networks. Furthermore, 'Too much worry' (strength index = 1.087) has the highest strength value. 'Nervous' (bridge strength index = 0.51, expected influence (1-step) = 0.51, expected influence (2-step) = 0.93) not only demonstrated the highest bridge strength but also exhibited the highest bridge expected influence. At last, we found that there were no significant differences between genders.
In this study, 'Nervous', 'Guilt', and 'Restless' were identified as three crucial bridge symptoms linking the comorbidity of depression and anxiety networks. Timely and multilevel interventions targeting these bridge symptoms may help alleviate the comorbidity of depression and anxiety in Chinese adolescents.
Not applicable.
本研究采用网络分析方法,调查在新冠疫情防控常态化阶段中国青少年抑郁与焦虑的共病模式。
2021年10月至12月,通过多阶段整群抽样从中国8个城市的27所学校选取了22868名青少年。分别采用患者健康问卷9项(PHQ-9)和广泛性焦虑障碍量表7项(GAD-7)对青少年的抑郁症状和焦虑症状进行评估。使用扩展贝叶斯信息准则(EBIC)和图形化最小绝对收缩和选择算子(LASSO)方法探索抑郁与焦虑之间的网络结构。分析节点的中心性、稳定性、准确性、核心症状、桥梁症状及网络比较。
在本研究中,7236名(31.6%)参与者报告有抑郁-焦虑共病。所获得的网络模型高度稳定。“控制担忧”与“过度担忧”之间、“坐立不安”与“易怒”之间以及“快感缺失”与“悲伤情绪”之间的边是焦虑和抑郁群落中最强的三条正向边。“多动”与“坐立不安”之间、“内疚”与“紧张”之间以及“自杀”与“恐惧”之间的边是共病群落中最强的三条正向边。“悲伤情绪”和“过度担忧”是“抑郁”网络和“焦虑”网络中的核心症状。“紧张”“内疚”和“坐立不安”是连接抑郁和焦虑网络共病的三个关键桥梁症状。此外,“过度担忧”(强度指数=1.087)具有最高的强度值。“紧张”(桥梁强度指数=0.51,预期影响(一步)=0.51,预期影响(两步)=0.93)不仅表现出最高的桥梁强度,而且具有最高的桥梁预期影响。最后,我们发现性别之间没有显著差异。
在本研究中,“紧张”“内疚”和“坐立不安”被确定为连接抑郁和焦虑网络共病的三个关键桥梁症状。针对这些桥梁症状进行及时且多层次的干预可能有助于缓解中国青少年的抑郁和焦虑共病情况。
不适用。