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网络分析埃塞俄比亚亚的斯亚贝巴成年人的心理健康问题:COVID-19 大流行期间的一项基于社区的研究。

Network analysis of mental health problems among adults in Addis Ababa, Ethiopia: a community-based study during the COVID-19 pandemic.

机构信息

Department of Epidemiology and Biostatistics, Addis Continental Institute of Public Health, Addis Ababa, Ethiopia

Department of Epidemiology and Biostatistics, Addis Continental Institute of Public Health, Addis Ababa, Ethiopia.

出版信息

BMJ Open. 2024 Jan 22;14(1):e075262. doi: 10.1136/bmjopen-2023-075262.

Abstract

OBJECTIVE

COVID-19 has negatively impacted mental health of adults globally with increased rates of psychiatric comorbidities. However, network analysis studies to examine comorbidities and correlations between symptoms of different mental disorders are uncommon in low-income countries. This study aimed to investigate the network structure of depression, anxiety and perceived stress among adults in Addis Ababa and identify the most central and bridge symptoms within the depressive-anxiety-perceived symptoms network model.

DESIGN

Community-based cross-sectional study.

SETTING

This study was carried out on a sample of the general population in Addis Ababa during the first year of the COVID-19 pandemic. A total of 1127 participants were included in this study, of which 747 (66.3%) were females, and the mean age was 36 years.

PRIMARY AND SECONDARY OUTCOME MEASURES

Symptoms of depression, anxiety and stress were measured using the Patient Health Questionnaire, Generalized Anxiety Disorder Scale and the Perceived Stress Scale, respectively.Network analysis was conducted to investigate the network structure. The centrality index expected influence (EI) and bridge EI (1-step) were applied to determine the central and bridge symptoms. Case-dropping procedure was used to examine the network stability.

RESULT

The sad mood (EI=1.52) was the most central and bridge symptom in the depression, anxiety and perceived stress network model. Irritability (bridge EI=1.12) and nervousness and stressed (bridge EI=1.33) also served as bridge symptoms. The strongest edge in the network was between nervousness and uncontrollable worry (weight=0.36) in the anxiety community. The network had good stability and accuracy. The network structure was invariant by gender and age based on the network structure invariance test.

CONCLUSIONS

In this study, the sad mood was the core and bridge symptom. This and the other central and bridge symptoms identified in the study should be targeted to prevent mental health disorders and comorbidities among adults.

摘要

目的

COVID-19 对全球成年人的心理健康产生了负面影响,导致精神共病率增加。然而,在低收入国家,检查不同精神障碍症状之间共病和相关性的网络分析研究并不常见。本研究旨在调查 COVID-19 大流行第一年期间在亚的斯亚贝巴成年人中抑郁、焦虑和感知压力的网络结构,并确定抑郁-焦虑-感知症状网络模型中最核心和桥梁症状。

设计

基于社区的横断面研究。

地点

本研究在 COVID-19 大流行期间对亚的斯亚贝巴的一般人群样本进行。共有 1127 名参与者纳入本研究,其中 747 名(66.3%)为女性,平均年龄为 36 岁。

主要和次要结果测量

使用患者健康问卷、广泛性焦虑症量表和感知压力量表分别测量抑郁、焦虑和压力症状。进行网络分析以调查网络结构。应用中心度指数预期影响(EI)和桥接 EI(1 步)确定核心和桥梁症状。采用病例剔除程序检查网络稳定性。

结果

在抑郁、焦虑和感知压力网络模型中,悲伤情绪(EI=1.52)是最核心和桥梁症状。易怒(桥接 EI=1.12)和紧张不安(桥接 EI=1.33)也是桥梁症状。在焦虑社区中,网络中最强的边缘是神经质和无法控制的担忧(权重=0.36)之间。该网络具有良好的稳定性和准确性。基于网络结构不变性检验,网络结构不受性别和年龄的影响。

结论

在这项研究中,悲伤情绪是核心和桥梁症状。本研究确定的其他核心和桥梁症状应该成为预防成年人心理健康障碍和共病的目标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8ea/10806846/9368e4963233/bmjopen-2023-075262f01.jpg

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