Yang Jiaqin, Man Xiaotong, Liu Chunlei
School of Psychology, Qufu Normal University, Qufu, China.
Key Laboratory of Modern Teaching Technology (Ministry of Education), Shaanxi Normal University, Xi'an, China.
Front Public Health. 2025 Feb 13;13:1548718. doi: 10.3389/fpubh.2025.1548718. eCollection 2025.
Under the background of COVID-19, people's mental health problems are concerned by researchers. Network analysis is a new method of exploring the interactions between mental health issues at the symptom level. This study investigates the network structure of generalized anxiety symptoms among Chinese residents during the COVID-19 pandemic from the perspective of "society-family-personality," and explores its relationship with the Big Five personality traits and perceived social support.
A multi-stage random sampling cross-sectional survey was conducted in 120 cities across China Mainland from July 10, 2021 to September 15, 2021, based on the PBICR database. The Big Five Scale (BFI-10), Perceived Social Support Scale (PSSS), and Generalized Anxiety Scale (GAD-7) were used for measurement. Pearson correlation analysis was used to examine the variables mentioned in this research, and network analysis was used to estimate the psychopathological network of the three variables.
A total of 11,031 subjects were included in the study, with 17% of individuals suffering from severe generalized anxiety symptoms. The results showed a correlation between the three research variables, and it was found that perceived social support in both dimensions and agreeableness of the Big Five personality traits were at the center of the network, with a significant impact on the overall network. There is a positive correlation between agreeableness and family support, but a negative correlation with generalized anxiety symptoms. Agreeableness serves as an indicator linking the other two variables; No significant gender differences were found through gender network testing.
According to this study, we believe that interventions in family atmosphere and social interaction can be used to prevent symptoms of generalized anxiety disorder. The limitation of this study is that it cannot determine the causal relationship between variables and its generalizability in general contexts has not been confirmed. Future research can further explore its directionality based on this study and consider the influence of cultural factors to extend its applicability to other backgrounds.
在新冠疫情背景下，人们的心理健康问题受到研究者关注。网络分析是一种在症状层面探索心理健康问题之间相互作用的新方法。本研究从“社会-家庭-人格”角度调查新冠疫情期间中国居民广泛性焦虑症状的网络结构，并探讨其与大五人格特质及感知社会支持的关系。
基于PBICR数据库，于2021年7月10日至2021年9月15日在中国内地120个城市进行多阶段随机抽样横断面调查。使用大五人格量表（BFI-10）、感知社会支持量表（PSSS）和广泛性焦虑量表（GAD-7）进行测量。采用Pearson相关分析检验本研究中提及的变量，并使用网络分析估计这三个变量的心理病理网络。
本研究共纳入11031名受试者，其中17%的个体患有严重的广泛性焦虑症状。结果显示三个研究变量之间存在相关性，发现感知社会支持的两个维度以及大五人格特质中的宜人性处于网络中心，对整体网络有显著影响。宜人性与家庭支持呈正相关，但与广泛性焦虑症状呈负相关。宜人性作为连接其他两个变量的指标；通过性别网络测试未发现显著的性别差异。
根据本研究，我们认为可以通过干预家庭氛围和社会互动来预防广泛性焦虑障碍症状。本研究的局限性在于无法确定变量之间的因果关系，且其在一般情境中的可推广性尚未得到证实。未来研究可基于本研究进一步探索其方向性，并考虑文化因素的影响，以将其适用性扩展到其他背景。
