In the current study, we aimed to investigate the network structure of COVID-19 symptoms and its related psychiatric symptoms, using a network approach. Specifically, we examined how COVID-19 symptoms relate to psychiatric symptoms and highlighted potential pathways between COVID-19 severity and psychiatric symptoms. With a sample of six hundred seventy-five recovered COVID-19 patients recruited 1 month after hospital discharge, we respectively integrated COVID-19 symptoms with PTSD, depression, and anxiety symptoms and analyzed the three network structures. In all three networks, COVID-19 severity and ICU admission are not linked directly to COVID-19 symptoms after hospitalization, while COVID-19 severity (but not ICU admission) is linked directly to one or more psychiatric symptoms. Specific pathways between COVID-19 symptoms and psychiatric symptoms were discussed. Finally, we used directed acyclic graph estimation to show potential causal effects between COVID-19 related variables and demographic characteristics.

在当前的研究中，我们旨在使用网络方法调查 COVID-19 症状及其相关精神症状的网络结构。具体来说，我们研究了 COVID-19 症状与精神症状之间的关系，并强调了 COVID-19 严重程度与精神症状之间的潜在途径。我们以出院后 1 个月招募的 675 名康复的 COVID-19 患者为样本，分别将 COVID-19 症状与 PTSD、抑郁和焦虑症状相结合，并分析了三种网络结构。在所有三个网络中，COVID-19 的严重程度和 ICU 入院与住院后的 COVID-19 症状没有直接联系，而 COVID-19 的严重程度（但不是 ICU 入院）与一种或多种精神症状直接相关。讨论了 COVID-19 症状和精神症状之间的特定途径。最后，我们使用有向无环图估计来显示 COVID-19 相关变量与人口特征之间的潜在因果关系。