Network analysis of COVID-19-related PTSD symptoms in China: the similarities and differences between the general population and PTSD sub-population

On the path to recovery: traumatic stress research during the COVID-19 pandemic 2021-2023

This Special Issue of the European Journal of Psychotraumatology (EJPT) presents 51 articles published between 2021 and 2023 and follows the Special Issue on pandemic-related traumatic stress research published in 2021 (O'Donnell, M. L., & Greene, T. [2021]. Understanding the mental health impacts of COVID-19 through a trauma lens. European Journal of Psychotraumatology, 12(1), 1982502). Research on traumatic stress during the pandemic has cast the spotlight on vulnerable populations and groups, notably front-line healthcare workers; people faced with major losses including the deaths of loved ones; those who personally survived debilitating and often life-threatening viral infection; and students who were isolated and experienced profound delays in their education, relationships, and emerging independence. The papers in this collection underscore the associations between COVID-19 related stressors and a plethora of adverse mental health sequelae, including posttraumatic stress reactions, and draw attention to the ubiquity of grief and moral injury and their wide-ranging and detrimental impact. Currently, there is a paucity of evidence on interventions to enhance resources, self-efficacy, and hope for affected groups and individuals through societal, organisational, and healthcare systems; however early research on the prevention of COVID-related traumatic stress disorders provides a basis for both hope and preparedness for the future.

The Burden of Survivorship: Survivor Guilt and Its Association with Psychiatric Sequelae in COVID-19 Patients

COVID-19 survivors struggle with intense depressive and post-traumatic symptoms in sub-acute stages. Survivor guilt may affect post-acute psychopathology. Herein, we aim to unveil the potential affective mechanism underpinning post-COVID psychiatric implications by focusing on the association of survivor guilt with psychopathology and maladaptive attributional style. At one month after discharge, we evaluated symptoms of depression on The Zung Severity Rating Scale (ZSDS), post-traumatic distress on Impact of Event Scale-Revised (IES-R), and sleep disturbances on the Women's Health Initiative Insomnia Rating Scale (WHIIRS) in 195 COVID-19 survivors. Interpersonal Guilt Rating Scale (IGRS-15) rated survivor guilt. A discrepancy score between the burden of depression and post-traumatic distress symptoms was computed individually. Dysfunctional depressive attributions were assessed through the Cognition Questionnaire (CQ). Survivor guilt significantly predicts all evaluated psychopathological dimensions. Moreover, higher rates of survivor guilt were associated with an overlap between post-traumatic and depressive symptomatology, thus suggesting that survivor guilt equally sustains both psychiatric manifestations. Finally, survivor guilt fully mediated the relationship between dysfunctional depressive attributions and the discrepancy index. Our results confirm survivor guilt as a clinically relevant form of suffering related to psychopathological dimensions of post COVID-19 infection, gaining the status of a specific phenomenon and a promising treatment target.

Network analysis of distress, suicidality, and resilience in a treatment seeking sample of first responders

INTRODUCTION

First responders are routinely and regularly exposed to traumatic events that can clinically manifest with a symptom constellation of posttraumatic stress disorder (PTSD), generalized anxiety, depression, and suicidality.

METHODS

We used network analysis to examine baseline data from treatment seeking first responders (n = 308) to examine the interrelatedness of those constructs, including a measure of resilience. We estimated two models: a regularized partial correlation network and a Bayesian Directed Acyclic Graph (DAG).

RESULTS

The models reveal converging evidence highlighting the central role of negative alterations in cognitions and mood PTSD cluster along with affective depression. These nodes did not significantly differ, though they were among the strongest in the partial correlation network and shared the most variance with the other nodes. The DAG results suggested that the negative alterations in cognitions and mood PTSD cluster predicted downstream constructs of affective depression; intrusion, hyperarousal, and avoidance PTSD clusters; and resilience. Only resilience and affective depression exhibited direct effects on suicidality. Both somatic depression and suicidality were endogenous endpoints in the DAG. Resilience exhibited an inverse path to suicide. However, resilience was relatively independent of the other constructs in the models and the DAG suggested that it was a consequence of PTSD related distress.

LIMITATIONS

The data is cross-sectional in nature that should be followed up in longitudinal studies.

CONCLUSION

Findings are discussed in respect to the role of distress and emotional dysregulation as common factors underlying a broad range of internalizing problems.

Co-occurrence of PTSD and affective symptoms in a large sample with childhood trauma subtypes: A network analysis

Background

Exposure to childhood trauma (CT) is associated with various deleterious mental health outcomes, increasing the risk of suicidal behaviors. The objective of this study is to investigate the different effects of three forms of CT, including emotional abuse (EA), physical abuse (PA), and sexual abuse (SA), on potential psychopathological symptoms among college students.

Methods

A total of 117,769 students from 63 Chinese colleges participated in this study. There were 1,191 participants in the EA group (1.24%; 95% CI: 1.17-1.31%), 1,272 participants in the PA group (1.32%; 95% CI: 1.25-1.40%), and 3,479 participants in the SA group (3.62%; 95% CI: 3.50-3.73%). CT was measured by the Childhood Trauma Questionnaire-Short Form. Psychopathological symptoms (i.e., depression, anxiety, and PTSD) were measured by the PHQ-9, GAD-7, and Trauma Screening Questionnaire, respectively. Network analysis was applied to analyze psychopathological symptoms between three CT subgroups (EA, PA, and SA). The associations and centralities of the networks were calculated, and the network characteristics of the three subgroups were contrasted.

Results

The main symptoms across all three groups are uncontrollable worry, sad mood, irritability, and fatigue, which indicates these core symptoms play essential roles in maintaining the whole psychological symptoms network. Furthermore, there are significant differences in symptom associations between the three groups. The comparison of network structures of the three groups shows that the SA group reports more PTSD symptoms, the EA group reports more suicide-related symptoms, and the PA group reports more anxiety symptoms.

Conclusion

Specific symptoms were disclosed across each group by the distinctive core psychopathological symptoms found in the CT subgroup networks. The present study's findings show different associations between CT and psychopathology and may help classify potential diagnostic processes. Therefore, local governments and academic institutions are recommended for early intervention to promote the psychological well-being of CT survivors.

Depression and PTSD in the aftermath of strict COVID-19 lockdowns: a cross-sectional and longitudinal network analysis

Background: Post-traumatic stress disorder (PTSD) and major depressive disorder (MDD) are two highly comorbid psychological outcomes commonly studied in the context of stress and potential trauma. In Hubei, China, of which Wuhan is the capital, residents experienced unprecedented stringent lockdowns in the early months of 2020 when COVID-19 was first reported. The comorbidity between PTSD and MDD has been previously studied using network models, but often limited to cross-sectional data and analysis. Objectives: This study aims to examine the cross-sectional and longitudinal network structures of MDD and PTSD symptoms using both undirected and directed methods. Methods: Using three types of network analysis - cross-sectional undirected network, longitudinal undirected network, and directed acyclic graph (DAG) - we examined the interrelationships between MDD and PTSD symptoms in a sample of Hubei residents assessed in April, June, August, and October 2020. We identified the most central symptoms, the most influential bridge symptoms, and causal links among symptoms. Results: In both cross-sessional and longitudinal networks, the most central depressive symptoms included sadness and depressed mood, whereas the most central PTSD symptoms changed from irritability and hypervigilance at the first wave to difficulty concentrating and avoidance of potential reminders at later waves. Bridge symptoms showed similarities and differences between cross-sessional and longitudinal networks with irritability/anger as the most influential bridge longitudinally. The DAG found feeling blue and intrusive thoughts the gateways to the emergence of other symptoms. Conclusions: Combining cross-sectional and longitudinal analysis, this study elucidated central and bridge symptoms and potential causal pathways among PTSD and depression symptoms. Clinical implications and limitations are discussed.