Supplementary file 1_A network analysis study on the relationship between generalized anxiety symptoms, big five personality and perceived social support of Chinese residents during COVID-19.docx

IntroductionUnder 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.
MethodsA 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.
ResultsA 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.
ConclusionAccording 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.

引言
新冠疫情背景下，民众的心理健康问题受到研究者的广泛关注。网络分析是一种在症状层面探索心理健康问题间交互作用的新兴研究方法。本研究从“社会-家庭-人格”视角出发，考察新冠疫情大流行期间中国居民广泛性焦虑症状（generalized anxiety symptoms）的网络结构，并探讨其与大五人格特质（Big Five personality traits）及领悟社会支持（perceived social support）的关联。

方法
本研究于2021年7月10日至2021年9月15日，基于PBICR数据库在中国大陆120个城市开展多阶段随机抽样横断面调查。研究采用大五人格简化量表（Big Five Inventory-10, BFI-10）、领悟社会支持量表（Perceived Social Support Scale, PSSS）以及广泛性焦虑障碍7条目量表（Generalized Anxiety Disorder 7-item scale, GAD-7）进行测评。采用Pearson相关分析检验本研究涉及的变量，并通过网络分析方法估算三类变量的精神病理网络。

结果
本研究共纳入11031名受试者，其中17%的个体存在严重广泛性焦虑症状。研究结果显示三类研究变量间存在相关关系，且发现双维度领悟社会支持与大五人格特质中的宜人性处于网络核心位置，对整体网络具有显著影响。宜人性与家庭支持呈正相关，而与广泛性焦虑症状呈负相关；宜人性可作为连接其余两类变量的指标。通过性别网络检验未发现显著性别差异。

结论
本研究表明，可通过干预家庭氛围与社会交往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间的因果关系，且其在一般情境下的推广性尚未得到证实。未来研究可基于本研究进一步探索变量间的方向性，并考虑文化因素的影响，以拓展其在其他背景下的适用性。