Ma Shumeng, Jia Ning
College of Education, Hebei Normal University, Shijiazhuang, People's Republic of China.
Psychol Res Behav Manag. 2024 Oct 29;17:3731-3747. doi: 10.2147/PRBM.S483231. eCollection 2024.
In China, as educational reforms progress, the characteristics of teachers' work have undergone significant changes, resulting in extremely high levels of stress that can trigger anxiety and depression. Anxiety and depression often co-occur, with two mainstream theories explaining this co-existence: the tripartite model and the diathesis-stress model. However, systematic research focusing on this population is relatively scarce, and the applicability of these models has not been thoroughly tested. This study aims to use network analysis methods to examine the interactions between symptoms and analyze the co-existence of anxiety and depression, thereby expanding the research on teachers.
Data were provided by the Science Database of People Mental Health, which includes 1670 teachers with a mean age of 30.01. The Self-Rating Anxiety Scale and Self-Rating Depression Scale were used to estimate the network structures of anxiety and depression, respectively. Shared symptoms between depression and anxiety were identified using network analysis and clique percolation methods. Bayesian Networks was used to estimate causal relationships between symptoms. Data were analyzed using R packages. Network structure was constructed with the qgraph package, node centrality and bridge symptoms were evaluated using the networktools package, and network stability was measured via the bootnet package. The Clique Percolation method was implemented with the CliqurPercolation package, and Bayesian network modeling was performed via the Bnlearn package.
Dizziness and Easy Fatigability & Weakness were central symptoms in the network. Bridging strength results showed that, the important bridging symptoms included Tachycardia, Depressed Affect, Fatigue, Crying Spell, Easy Fatigability & Weakness, Nightmares, Face Flushing, and Sweating were the strong bridging symptoms. Additionally, Sleep Disturbance played a key mediating role. Depressed Affect and Dissatisfaction were activation symptoms for anxiety-depression co-existence.
Using network analysis, this study elucidated core, bridging, and shared symptoms, as well as potential causal pathways between anxiety and depression. Specifically, somatic symptoms are crucial in maintaining and developing the anxiety-depression network among teachers. Sleep disturbance serves as the sole gateway for mild symptoms to develop into other communities. The Bayesian network identified two key activating symptoms within the teacher anxiety-depression network, validating the applicability of the tripartite model among teachers.
在中国，随着教育改革的推进，教师工作的特点发生了显著变化，导致压力极大，可能引发焦虑和抑郁。焦虑和抑郁常常同时出现，有两种主流理论解释这种共存现象：三方模型和素质-应激模型。然而，针对这一群体的系统研究相对较少，这些模型的适用性尚未得到充分检验。本研究旨在使用网络分析方法来检验症状之间的相互作用，并分析焦虑和抑郁的共存情况，从而拓展对教师的研究。
数据由人民心理健康科学数据库提供，该数据库包含1670名平均年龄为30.01岁的教师。分别使用自评焦虑量表和自评抑郁量表来估计焦虑和抑郁的网络结构。使用网络分析和团渗流方法识别抑郁和焦虑之间的共同症状。使用贝叶斯网络估计症状之间的因果关系。使用R包进行数据分析。使用qgraph包构建网络结构，使用networktools包评估节点中心性和桥梁症状，通过bootnet包测量网络稳定性。使用CliqurPercolation包实现团渗流方法，通过Bnlearn包进行贝叶斯网络建模。
头晕和易疲劳及虚弱是网络中的核心症状。桥梁强度结果显示，重要的桥梁症状包括心动过速、情绪低落、疲劳、哭泣发作、易疲劳及虚弱、噩梦、面部潮红和出汗是强烈的桥梁症状。此外，睡眠障碍起到了关键的中介作用。情绪低落和不满是焦虑-抑郁共存的激活症状。
本研究通过网络分析阐明了核心、桥梁和共同症状，以及焦虑和抑郁之间潜在的因果途径。具体而言，躯体症状在维持和发展教师焦虑-抑郁网络中至关重要。睡眠障碍是轻度症状发展为其他症状群的唯一通道。贝叶斯网络在教师焦虑-抑郁网络中识别出两个关键的激活症状，验证了三方模型在教师中的适用性。
