Wu Yuanyuan, Cai Meng, Yu Chang
School of Humanities and Social Science, Xi'an Jiaotong University, 28 Xianning West Rd., Beilin District, Xi'an, Shaanxi, 710049, P.R. China.
Department of Sociology and Criminology, University at Buffalo, State University of New York, Buffalo, NY, USA.
BMC Psychol. 2025 Jul 17;13(1):797. doi: 10.1186/s40359-025-03119-8.
BACKGROUND: The COVID-19 pandemic exacerbates the effects of social isolation on the mental health of middle-aged and older adults. This study aimed to explore the network structures of depressive symptoms among Chinese middle-aged and older adults before and after the COVID-19 outbreak and investigate their associations with Internet use. METHODS: Two cross-sectional datasets were obtained from the 2018 and 2020 waves of the China Health and Retirement Longitudinal Study (CHARLS). Depressive symptoms and Internet use were assessed using the Center for Epidemiological Studies-Depression Scale (CES-D) and self-reported Internet use. Network analysis was conducted to identify central symptoms and differences between the two networks and their associations with Internet use. RESULTS: Network analysis revealed that CESD3 "Felt depressed" was the central symptom of the depression network in both waves. No significant differences in network structure were observed, but significant differences in global strength and edge strength were found. Furthermore, Internet use showed a more complex association with depressive symptoms among middle-aged and older adults in wave 2. CONCLUSION: This study provides novel insights into the central features of depressive symptoms among middle-aged and older adults before and after the COVID-19 outbreak. Targeting interventions to central symptoms and strong edges may have significant implications for depression treatment. In addition, strategies aimed at enhancing Internet use guidance could potentially benefit the mental health of middle-aged and older adults.
背景:2019冠状病毒病疫情加剧了社会隔离对中老年人心心理健康的影响。本研究旨在探讨2019冠状病毒病疫情前后中国中老年人抑郁症状的网络结构,并调查其与互联网使用的关联。 方法:从中国健康与养老追踪调查(CHARLS)2018年和2020年两轮调查中获取两个横断面数据集。使用流行病学研究中心抑郁量表(CES-D)和自我报告的互联网使用情况评估抑郁症状和互联网使用情况。进行网络分析以识别核心症状、两个网络之间的差异及其与互联网使用的关联。 结果:网络分析显示,CESD3“感到沮丧”是两轮调查中抑郁网络的核心症状。未观察到网络结构的显著差异,但发现全局强度和边强度存在显著差异。此外,在第二轮调查中,互联网使用与中老年人抑郁症状的关联更为复杂。 结论:本研究为2019冠状病毒病疫情前后中老年人抑郁症状的核心特征提供了新的见解。针对核心症状和强关联进行干预可能对抑郁症治疗具有重要意义。此外,旨在加强互联网使用指导的策略可能有利于中老年人的心理健康。
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