Zhang Chi, Zhao Yuefan, Wei Lei, Tang Qian, Deng Ruyue, Yan Shiyuan, Yao Jun
School of Health Policy and Management, Nanjing Medical University, Nanjing 211166, China.
School of Nursing, Nanjing Medical University, Nanjing 211166, China.
Healthcare (Basel). 2024 Sep 10;12(18):1802. doi: 10.3390/healthcare12181802.
Many Chinese migrant older adults are more prone to mental health problems due to their "migrant" status. During the COVID-19 pandemic, restrictions on their mobility exacerbated these conditions. Mental health is a crucial dimension of healthy aging. Network analysis offers a novel method for exploring interactions between mental health problems at the symptom level. This study employs network analysis to examine the interactions between comorbid depressive and anxiety symptoms across different stages of the COVID-19 pandemic. Surveys were conducted from September 2019 to January 2020 (T1), September 2020 to January 2021 (T2), and September 2021 onwards (T3). Depression and anxiety symptoms were measured by the Patient Health Questionnaire-9 (PHQ-9) and the Hospital Anxiety and Depression Scale-Anxiety (HADS-A). Expected Influence (EI) and Bridge Expected Influence (Bridge EI) were used to identify central and bridge symptoms in the network. Network stability and accuracy tests were performed. Among the Chinese migrant older adults, the anxiety prevalence was 18.50% at T1, 21.11% at T2, and 9.38% at T3. The prevalence of depression was 26.95% at T1, 55.44% at T2, and 60.24% at T3. The primary central symptoms included 'Afraid something will happen' (A2), 'Irritability' (A6), 'Panic' (A7), 'Feeling of worthlessness' (D6), 'Anhedonia' (D1), and 'Feeling of fear' (A5). The major bridge symptoms included 'Feeling of fear' (A5), 'Panic' (A7), 'Irritability' (A6), 'Fatigue' (D4), 'Anhedonia' (D1), and 'Depressed or sad mood' (D2). Differences in network structure were observed across the periods. The network analysis further revealed the evolving relationships between central and bridge symptoms over time, highlighting the importance of targeted intervention strategies for central and bridge symptoms of comorbid depression and anxiety at different periods.
许多中国老年移民因其“移民”身份更容易出现心理健康问题。在新冠疫情期间,对他们行动的限制加剧了这些情况。心理健康是健康老龄化的一个关键维度。网络分析为探索症状层面心理健康问题之间的相互作用提供了一种新方法。本研究采用网络分析来考察新冠疫情不同阶段共病的抑郁和焦虑症状之间的相互作用。调查在2019年9月至2020年1月(T1)、2020年9月至2021年1月(T2)以及2021年9月起(T3)进行。抑郁和焦虑症状通过患者健康问卷-9(PHQ-9)和医院焦虑抑郁量表-焦虑(HADS-A)进行测量。使用预期影响(EI)和桥梁预期影响(桥梁EI)来识别网络中的核心症状和桥梁症状。进行了网络稳定性和准确性测试。在中国老年移民中,焦虑患病率在T1为18.50%,在T2为21.11%,在T3为9.38%。抑郁患病率在T1为26.95%,在T2为55.44%,在T3为60.24%。主要的核心症状包括“担心会发生什么事”(A2)、“易怒”(A6)、“恐慌”(A7)、“无价值感”(D6)、“快感缺失”(D1)和“恐惧情绪”(A5)。主要的桥梁症状包括“恐惧情绪”(A5)、“恐慌”(A7)、“易怒”(A6)、“疲劳”(D4)、“快感缺失”(D1)和“情绪低落或悲伤”(D2)。不同时期观察到网络结构存在差异。网络分析进一步揭示了核心症状和桥梁症状随时间的演变关系,凸显了针对不同时期共病抑郁和焦虑的核心症状和桥梁症状采取有针对性干预策略的重要性。