Wu Lin, Ren Lei, Li Fengzhan, Shi Kang, Fang Peng, Wang Xiuchao, Feng Tingwei, Wu Shengjun, Liu Xufeng
Department of Military Medical Psychology, Air Force Medical University, Xi'an 710032, China.
Military Psychology Section, Logistics University of PAP, Tianjin 300309, China.
Brain Sci. 2023 Aug 1;13(8):1155. doi: 10.3390/brainsci13081155.
This research analyses the relations between anxiety symptoms from the network perspective to deepen the understanding of anxiety in front-line medical staff during the COVID-19 pandemic and can also provide a reference for determining potential goals of clinical interventions.
A convenience sampling was adopted, and the Generalized Anxiety Disorder 7-item scale (GAD-7) was administered to front-line medical staff through online platforms. A regularized partial correlation network of anxiety was constructed and then we evaluated its accuracy and stability. The expected influence and predictability were used to describe the relative importance and the controllability, using community detection to explore community structure. The gender-based differences and the directed acyclic graph were implemented.
The connections between A1 "Feeling nervous, anxious or on edge" and A2 "Not being able to stop or control worrying", A6 "Becoming easily annoyed or irritable" and A7 "Feeling afraid as if something awful might happen", etc., were relatively strong; A2 "Not being able to stop or control worrying" and A3 "Worrying too much about different things" had the highest expected influence, and A2 "Not being able to stop or control worrying" had the highest predictability. The community detection identified two communities. The results of the gender network comparison showed the overall intensity of the anxiety network in women was higher than that in men; DAG indicated that A2 "Not being able to stop or control worrying" had the highest probabilistic priority; the lines from A2 "Not being able to stop or control worrying" to A1 "Feeling nervous, anxious or on edge" and A2 "Not being able to stop or control worrying" to A7 "Feeling afraid as if something awful might happen" represented the most important arrows.
There exist broad interconnections among anxiety symptoms of front-line medical staff on the GAD-7. A2 "Not being able to stop or control worrying" might be the core symptom and a potential effective intervention target. It was possible to bring an optimal result for the entire GAD symptom network by interfering with A2 "Not being able to stop or control worrying". GAD may have two "subsystems". The modes of interconnection among anxiety may be consistent between genders.
本研究从网络视角分析焦虑症状之间的关系，以加深对新冠疫情期间一线医护人员焦虑状况的理解，也可为确定临床干预的潜在目标提供参考。
采用便利抽样法，通过在线平台对一线医护人员施测广泛性焦虑障碍7项量表（GAD-7）。构建焦虑的正则化偏相关网络，然后评估其准确性和稳定性。用预期影响和可预测性描述相对重要性和可控性，利用社区检测探索社区结构。实施基于性别的差异分析和有向无环图分析。
A1“感到紧张、焦虑或不安”与A2“无法停止或控制担忧”、A6“容易烦恼或急躁”与A7“感到害怕，好像有可怕的事情要发生”等之间的联系相对较强；A2“无法停止或控制担忧”与A3“对不同事情过度担忧”的预期影响最高，A2“无法停止或控制担忧”的可预测性最高。社区检测识别出两个社区。性别网络比较结果显示，女性焦虑网络的整体强度高于男性；有向无环图表明A2“无法停止或控制担忧”具有最高的概率优先级；从A2“无法停止或控制担忧”到A1“感到紧张、焦虑或不安”以及从A2“无法停止或控制担忧”到A7“感到害怕，好像有可怕的事情要发生”的连线代表最重要的箭头。
一线医护人员在GAD-7上的焦虑症状之间存在广泛的相互联系。A2“无法停止或控制担忧”可能是核心症状和潜在的有效干预靶点。通过干预A2“无法停止或控制担忧”，可能为整个GAD症状网络带来最佳效果。GAD可能有两个“子系统”。焦虑之间的相互联系模式在性别之间可能是一致的。
