Liu Jia-Li, Ran Wan-Ting, Wang Zhi, Nie Ze-Min, Huang Gui-Lin, Yi Jun-Wen, Yang Si-Yu, He Zi-Yi, Wang Ya, Chen Gui-Fang
Affiliated Hospital of Zunyi Medical University, Zuiyi, China.
Zunyi Medical University, Zunyi, China.
Psych J. 2025 Aug;14(4):523-533. doi: 10.1002/pchj.70028. Epub 2025 Jun 26.
Since the outbreak of the COVID-19 pandemic, college students experienced changed campus life during the evolving pandemic restrictions. Anxiety and depression have become increasingly prevalent, leading to the necessity for further examining their relationship and comorbidity. This study used the network analysis to investigate the interaction and causal relationship in the anxiety-depression network among Chinese college students during the pandemic. A longitudinal survey with two specific points among 705 college students were conducted from 12 December to 30 December 2022 (lockdown period, T1), and from 8 February to 13 March 2023 (lockdown lift period, T2). Contemporaneous network and cross-lagged panel network (CLPN) analysis were conducted to examine the issue from both cross-sectional and longitudinal perspectives. Both contemporaneous networks exhibited extensive links between anxiety and depression symptoms. The key central symptom was "STAI16: [Not] content" at T1, and was "STAI15: [Not] relaxed" at T2. CLPN analysis suggested that "STAI15: [Not] relaxed" had the highest in-prediction, while "STAI13: Jittery" had the highest out-prediction. The strongest transdiagnostic prediction was from "BDI6: Punishment" to "STAI9: Frightened", and the bridge symptoms in both contemporaneous networks and CLPN included overlaps like "STAI11: [Not] self-confident" and "STAI14: Indecisive", which served as important symptoms contributing to anxiety-depression comorbidity. These findings provide new insights into the causal relationships between depression and anxiety before and after lockdown lift, shed light on the comorbidity factors, and provide support for targeted interventions to address mental health challenges faced by college students in public crisis.
自新冠疫情爆发以来,在不断演变的疫情限制措施下,大学生的校园生活发生了变化。焦虑和抑郁日益普遍,这使得有必要进一步研究它们之间的关系及共病情况。本研究采用网络分析方法,调查疫情期间中国大学生焦虑 - 抑郁网络中的相互作用和因果关系。在2022年12月12日至12月30日(封控期,T1)以及2023年2月8日至3月13日(解封期,T2),对705名大学生进行了两个特定时间点的纵向调查。进行了同期网络分析和交叉滞后面板网络(CLPN)分析,从横断面和纵向两个角度研究该问题。两个同期网络均显示焦虑和抑郁症状之间存在广泛联系。关键的中心症状在T1时是“状态 - 特质焦虑量表16项:[不]满足”,在T2时是“状态 - 特质焦虑量表15项:[不]放松”。CLPN分析表明,“状态 - 特质焦虑量表15项:[不]放松”的向内预测能力最强,而“状态 - 特质焦虑量表13项:紧张不安”的向外预测能力最强。最强的跨诊断预测是从“贝克抑郁量表6项:惩罚”到“状态 - 特质焦虑量表9项:害怕”,同期网络和CLPN中的桥梁症状都包括“状态 - 特质焦虑量表11项:[不]自信”和“状态 - 特质焦虑量表14项:优柔寡断”等重叠症状,这些症状是导致焦虑 - 抑郁共病的重要因素。这些发现为解封前后抑郁与焦虑之间的因果关系提供了新见解,揭示了共病因素,并为应对大学生在公共危机中面临的心理健康挑战的针对性干预提供了支持。