Aims This study aimed to investigate the prevalence of anxiety, depression and PTSD symptoms, and associated risk factors among a large-scale sample of adolescents from China after the pandemic and lockdown. Method A total of 57,948 high school students took part in an online survey from July 13 to 29, 2020. The mental health outcomes included anxiety, depression and PTSD symptoms. Risk factors included negative family relationships, COVID-19 related exposure, and a lack of social support. Results The prevalence of anxiety, depression and PTSD symptoms was 7.1%, 12.8%, and 16.9%, respectively. COVID-19 related exposure significantly linked to the mental health outcomes (all p < .001). The most important predictors for the mental health outcomes were family relationship and social support (all p < .001). Conclusion The pandemic may have long-term adverse mental health consequences among adolescents. Adverse family relationships and lack of social support could be the major risk factors for the post-pandemic mental health outcomes of adolescents.

Background Experiencing natural disasters is associated with common mental disorders including major depressive disorder (MDD). However, the latent structure of MDD is widely debated, and few studies tested the MDD factor structure in Chinese natural disaster survivors. Therefore, the aim of the current study was to evaluate the factorial validity of the Patient Health Questionnaire-9 (PHQ-9) for DSM-5 major depressive disorder (MDD) symptoms in Chinese earthquake survivors. Method Participants were 1058 Chinese earthquake survivors. Self-reported measures included the PHQ-9 and the Short-Form Health Survey (SF-36). Confirmatory factor analysis (CFA) and structural equation modelling (SEM) was used to examine the latent structure of MDD and the associations between latent factors of MDD and different domains of health-related quality of life (HRQoL), respectively. Results In the current sample, the model consisted of somatic and cognitive/affective (non-somatic) factors demonstrated significantly better fit than the other competing MDD models (χ2 = 173.89, df = 26, CFI = 0.986, TLI = 0.981, RMSEA = 0.073, BIC = 18,091.13). Further SEM analyses indicated that the non-somatic factor was significantly related to both physical (β = − 0.362, p < .01) and psychosocial HRQoL (β = − 0.773, p < .01), while the somatic factor was a uniquely predictor of physical HRQoL (β = − 0.336, p < .01). Furthermore, we found the somatic factor partially mediated the relationship between the cognitive/affective factor and physical HRQoL (all ps < .05). Conclusions The MDD symptoms was best captured by a two-factor model comprised of somatic and cognitive/affective factors in Chinese natural disaster survivors. The two MDD factors were differentially associated with physical and psychosocial HRQoL, and the cognitive/affective factor associated physical HRQoL partially through the somatic factor. The current findings increase our understanding of latent structure of MDD symptoms, and carry implications for assessment and intervention of post-disaster mental health problems.

Background: Both the latent variable model and the network model have been widely used to conceptualize mental disorders. However, it has been pointed out that there is no clear dichotomy between the two models, and a combination of these two model could enable a better understanding of psychopathology. The recently proposed latent network model (LNM) has provided a statistical framework to enable this combination. Evidence has shown that posttraumatic stress disorder (PTSD) could be a suitable candidate disorder to study the combined model. In the current study, we initiated the first investigation of the latent network of PTSD symptoms. Methods: The latent network of DSM-5 PTSD symptoms was estimated in 1196 adult survivors of China's 2008 Wenchuan earthquake. Validation testing of the latent network was conducted in a replication sample of children and adolescent who experienced various trauma types. PTSD symptoms were measured by the PTSD Checklist for DSM-5 (PCL-5). The latent network was estimated using the seven-factor hybrid model of DSM-5 PTSD symptoms, analysed using the R package lvnet. Results: The latent network model demonstrated good fit in both samples. A strong weighted edge between the intrusion and avoidance dimensions was identified (regularized partial correlation = 0.75). The externalizing behaviour dimension demonstrated the highest centrality in the latent network. Conclusions: This study is the first to investigate the latent network of DSM-5 PTSD symptoms. Results suggest that both latent symptom dimension and associations between the dimensions should be considered in future PTSD studies and clinical practices.