Unit of Psychiatry, Department of Public Health and Medicinal Administration, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China; Centre for Cognitive and Brain Sciences, University of Macau, Macao SAR, China.
Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
J Affect Disord. 2024 Jan 1;344:33-40. doi: 10.1016/j.jad.2023.09.034. Epub 2023 Oct 2.
Depressive and anxiety symptoms (depression and anxiety hereafter) are common among psychiatric patients and their caregivers during the COVID-19 pandemic. Network analysis is a novel method to assess the associations between psychiatric syndromes/disorders at the symptom level. This study examined depression and anxiety among caregivers of psychiatric inpatients during the late stage of the COVID-19 pandemic from the perspective of network analysis.
A total of 1101 caregivers of psychiatric inpatients were included in this study. The severity of depression was assessed using the nine-item Patient Health Questionnaire (PHQ-9), while anxiety was assessed with the seven-item Generalized Anxiety Disorder Scale (GAD-7). The expected index (EI) and bridge EI index were used to identify the central and bridge symptoms, respectively. The stability of the network was evaluated via a case-dropping bootstrap procedure.
The prevalence of depression and anxiety were 32.4 % (95%CI: 29.7 %-35.3 %) and 28.0 % (95%CI: 25.4 %-30.7 %), respectively while the prevalence of comorbid depression and anxiety was 24.9 % (95%CI: 22.4 %-27.6 %). The most central symptom was "Fatigue", followed by "Trouble Relaxing" and "Restlessness". The highest bridge symptom was "Restlessness", followed by "Uncontrollable worry" and "Suicide ideation". The bootstrap test indicated that the whole network model was stable, and no network difference was detected between genders and between different education levels.
Depression, anxiety, and comorbid depression and anxiety were common among caregivers of psychiatric inpatients during the late stage of the COVID-19 pandemic. Central and bridge symptoms identified in this network analysis should be considered key target symptoms to address in caregivers of patients.
在 COVID-19 大流行期间，精神科患者及其照顾者中常见抑郁和焦虑症状（以下简称抑郁和焦虑）。网络分析是一种评估精神障碍症状水平关联的新方法。本研究从网络分析的角度，考察了 COVID-19 大流行后期精神科住院患者照顾者的抑郁和焦虑情况。
共纳入 1101 名精神科住院患者的照顾者。采用 9 项患者健康问卷（PHQ-9）评估抑郁严重程度，采用 7 项广泛性焦虑症量表（GAD-7）评估焦虑严重程度。分别采用预期指数（EI）和桥接 EI 指数识别核心症状和桥接症状。通过病例剔除 Bootstrap 程序评估网络的稳定性。
抑郁和焦虑的患病率分别为 32.4%（95%CI：29.7%-35.3%）和 28.0%（95%CI：25.4%-30.7%），共病抑郁和焦虑的患病率为 24.9%（95%CI：22.4%-27.6%）。最核心的症状是“疲劳”，其次是“难以放松”和“烦躁不安”。最高的桥接症状是“烦躁不安”，其次是“无法控制的担忧”和“自杀意念”。Bootstrap 检验表明，整个网络模型是稳定的，且未发现性别和不同受教育程度之间的网络差异。
COVID-19 大流行后期，精神科住院患者照顾者中常见抑郁、焦虑和共病抑郁焦虑。本网络分析中识别的核心和桥接症状应被视为照顾者中患者的关键目标症状。
