创伤事件后，创伤后应激障碍（Posttraumatic Stress Disorder, PTSD）和重性抑郁障碍（Major Depressive Disorder, MDD）有关症状往往相伴而生，二者的共病检出率很高。以往关于PTSD和MDD共病现象的实证研究大多基于共同因素假说，使用潜变量模型，在障碍或维度层面探讨二者间的关系，这会忽视症状间天然存在的因果联系。精神障碍的网络理论则认为，症状间稳定存在的共变模式并不需要借助潜变量来解释，因为症状间天然就存在直接的因果联系，当症状网络中的反馈环路被激活时，精神障碍也就随之出现了。近5年来，有不少实证研究使用网络分析模型在症状层面考察了PTSD和MDD的共病模式，确定了二者间的桥症状。但这些研究均采用的是横断调查范式，在现有诊断标准所界定的边界下确定二者间的桥症状，且大都是在成人（例如：军人）群体中开展的。目前，尚未有研究采用纵向追踪设计，借助网络分析模型，从症状层面出发，在经历重大自然灾难（例如：地震）后的儿童和青少年群体中探讨PTSD和MDD的共病模式。

为此，本研究采用纵向追踪设计，分别在汶川地震、雅安地震后1年和1.5年时对灾区中小学生开展调查，并借助网络分析模型，从症状层面出发，考察PTSD和MDD在这一群体中的共病模式。同时，为保证研究结论的可重复性，对汶川和雅安两个样本的结果进行交叉验证。结果发现：

（1）在囊括PTSD和MDD所有症状/节点的共病网络中，二者的4个重叠症状：睡眠问题、注意力问题、兴趣减退和烦躁易怒，以及躁郁维度下的疏离、未来受限和情绪麻木这3个症状被确认为是二者间的桥症状。

（2）在将上述4个重叠症状剔除后，借助子网络探测算法在共病网络中发现了3个子网络。其中，躁郁维度下的疏离、未来受限、情绪麻木和失忆症状与MDD（除恐惧症状外）各症状组成一个子网络，即MDD类子网络；而隶属于MDD的恐惧症状则和剩余的PTSD症状组成另一个子网络，即PTSD类子网络。若以探寻得到的子网络为基础，则发现：恐惧、情绪麻木、惊跳反应和高警觉症状是PTSD类子网络和MDD类子网络间的桥症状。

（3）在PTSD和MDD的共病时序网络中，各症状在时间历程中存在相互预测、互为因果的关系。在汶川地震样本中，更多的体现为MDD症状激发PTSD症状；但在雅安样本中，则是PTSD症状更可能激发MDD症状。

（4）闯入性症状和回避性症状被确认为是PTSD的核心症状，且在时间历程中，主要表现为是闯入性症状激发回避性症状，并在此基础上形成了症状间的反馈环路。

（5）从障碍的视角出发，两个样本中PTSD和MDD在时间历程中的因果指向性存在差异。除此之外，本研究的所有结论均在汶川和雅安两个样本中得到了交叉验证。

综上，本研究首次在经历了重大自然灾难后的儿童和青少年群体中，利用追踪数据，抛开现有诊断标准所界定的边界构建网络分析模型，在症状层面考察了PTSD和MDD的共病模式，并得到如下结论：（1）在震后的儿童和青少年群体中，DSM-IV所界定的PTSD症状边界并不准确；（2）躁郁维度在PTSD和MDD的共病现象中起到了重要作用，可将其视为PTSD的一种亚形；（3）从症状的层面出发，PTSD和MDD的各症状在时间历程中互为因果；但若从障碍的视角出发，PTSD和MDD在时间历程中的因果指向性仍不明确。

Following a traumatic event, symptoms related to Posttraumatic Stress Disorder (PTSD) and Major Depressive Disorder (MDD) often co-occur, with a high rate of co-morbidity detection between the two. Most previous empirical studies on the co-morbidity of PTSD and MDD have been based on the common factor hypothesis, using latent variable models to explore the relationship between the two at the disorder or dimensional level, which can ignore the causal links between symptoms. The network approach to psychiatry, on the other hand, suggests that the covariation among symptoms does not need to be explained by latent variables, because direct causal links naturally exist among symptoms, and mental disorders emerge when feedback loops in the symptom network are activated. In the last 5 years, a number of empirical studies have examined the co-morbidity patterns of PTSD and MDD at the symptom level using network analysis models to identify bridging symptoms between the two. However, these studies have all used a cross-sectional survey paradigm to identify bridge symptoms between the two within the boundaries defined by existing diagnostic criteria and have mostly been conducted in adult (e.g., military) populations. No study has yet used a longitudinal follow-up design to explore co-morbidity patterns of PTSD and MDD at the symptom level in a population of children and adolescents who have experienced a major natural disaster (e.g., earthquake) with the help of a network analysis model.

For this reason, this study used a longitudinal paradigm to investigate children and adolescents at 1 and 1.5 years after the Wenchuan and Ya'an earthquake, respectively. And modeled data using network analysis model to examine the co-morbidity patterns of PTSD and MDD in this population at the level of symptoms. Also, to improve the generalizability of our findings, the results were cross-validated in both Wenchuan and Ya'an sample. We found that:

(1) In the co-morbidity network encompassing all symptoms/nodes of PTSD and MDD, four overlapping symptoms: sleep problems, attention problems, diminished interest and irritability, and three symptoms of detachment, restricted future and emotional numbness under the dysphoria dimension were identified as bridge symptoms between the two.

(2) After eliminating the four overlapping symptoms, three sub-networks were identified in the co-morbidity network. Among them, detachment, future limitation, emotional numbness and amnesia symptoms in the dysphoria dimension formed a subnetwork with each node of MDD (except "fear" symptom), while fear symptom belonging to MDD formed another subnetwork with the remaining PTSD symptoms. It is found that: fear, emotional numbness, startle response and hypervigilance symptoms are the bridge symptoms between the two subnetworks.

(3) In the co-morbidity temporal network of PTSD and MDD, the symptoms are predictive of each other and are mutually causal. In the Wenchuan sample, it was more likely that MDD symptoms triggered PTSD symptoms; however, in the Ya'an sample, it was more likely that PTSD symptoms triggered MDD symptoms.

(4) Intrusive and avoidant symptoms were identified as the core symptoms of PTSD, and in the co-morbidity temporal network, intrusive symptoms stimulate avoidance symptoms, and on this basis, a feedback loop between symptoms was formed.

(5) From a disorder perspective, there were differences in the directionality of PTSD and MDD in co-morbidity temporal network of the two samples. Besides, all the findings of this study were cross-validated in both Wenchuan and Ya'an samples.

In summary, this study examined the co-morbidity patterns of PTSD and MDD at the symptom level for the first time in children and adolescents who experienced a natural disaster, using longitudinal data and constructing network analysis model by setting aside existing diagnostic criteria, and concluded that: (1) the symptom boundaries of PTSD as defined by the DSM-IV were not accurate, at least in the post-earthquake children and adolescents; (2) the dysphoria dimension plays an important role in the co-morbidity patterns of PTSD and MDD and can be considered as a subform of PTSD; and (3) From the symptom level, the symptoms are predictive of each other and are mutually causal; however, when viewed from the perspective of the disorder, the causal directionality of PTSD and MDD in the co-morbidity temporal network remains unclear.