A network analysis of two conceptual approaches to the etiology of PTSD

Prospective network of post-traumatic stress disorder (PTSD) symptoms across adolescent survivors with distinct trajectories of PTSD: A cohort study of the Wenchuan earthquake

There are multiple trajectories of post-traumatic stress disorder (PTSD) symptoms following disasters. Unraveling the patterns of interactions between PTSD symptoms across distinct PTSD trajectories is crucial. This study was aimed at investigating the temporal sequences, changes, and predictive symptoms in PTSD networks over time across distinct PTSD trajectory groups. Data were exacted from the Wenchuan Earthquake Adolescent Health Cohort (WEAHC) study. The current study included 1022 adolescents (424 males) who participated in follow-up surveys at 12 months and 24 months post-earthquake. Self-reported PTSD symptoms were assessed with the Post-traumatic Stress Disorder Self-Rating Scale. The between-person network revealed significant differences across distinct trajectories. In the chronic dysfunction group, "Intrusive thoughts" had the strongest value in predicting on other PTSD symptoms. In contrast, "Difficulty in study or work" in the recovery group and "Physiological cue reactivity" in the resistance group were highly associated with the remission of other PTSD symptoms. These findings underscore the importance of "Difficulty in study or work" and "Physiological cue reactivity" for promoting the spontaneous remission of PTSD and further suggest that "Intrusive thoughts" maybe helpful to minimize the subsequent presence of other PTSD symptoms. Future research should investigate the causality and associations between within-person networks.

Stress response and experiential avoidance among firefighters: Preliminary insights from network analyses

Firefighters are at increased risk of developing posttraumatic stress disorder (PTSD) due to exposure to potentially traumatic events during their careers. However, little is known about the prevalence of PTSD among this population, particularly when taking moderating variables into account. Using Gaussian Graphical Models and Directed Acyclic Graphs, we conducted network analyses to examine the interactions between clusters of PTSD symptoms, perceived stress, hardiness, and experiential avoidance among 187 firefighters. The data and code are published with the paper. Experiential avoidance, as part of psychological inflexibility, was found to be the only variable that interacted with PTSD symptomatology. Strong positive associations were observed between experiential avoidance and the "negative mood and cognitions" subscale of the PTSD Checklist for DSM-5 (PCL-5). Through this association, other PTSD symptoms were activated, particularly avoidance and arousal. Our findings suggest that experiential avoidance and negative mood and cognition symptoms are particularly important in the expression of PTSD symptomatology in firefighters. In addition, experiential avoidance may be used as a coping strategy to reduce perceived stress during potentially traumatic events. Therefore, experiential avoidance may be a prime target for future interventions and training focused on flexible self-regulation strategies in this population.

Network modeling of major depressive disorder symptoms in adult women

BACKGROUND

Major depressive disorder (MDD) is one of the growing human mental health challenges facing the global health care system. In this study, the structural connectivity between symptoms of MDD is explored using two different network modeling approaches.

METHODS

Data are from 'the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders (VATSPSUD)'. A cohort of N = 2163 American Caucasian female-female twins was assessed as part of the VATSPSUD study. MDD symptoms were assessed using personal structured clinical interviews. Two network analyses were conducted. First, an undirected network model was estimated to explore the connectivity between the MDD symptoms. Then, using a Bayesian network, we computed a directed acyclic graph (DAG) to investigate possible directional relationships between symptoms.

RESULTS

Based on the results of the undirected network, the depressed mood symptom had the highest centrality value, indicating its importance in the overall network of MDD symptoms. Bayesian network analysis indicated that depressed mood emerged as a plausible driving symptom for activating other symptoms. These results are consistent with DSM-5 guidelines for MDD. Also, somatic weight and appetite symptoms appeared as the strongest connections in both networks.

CONCLUSIONS

We discuss how the findings of our study might help future research to detect clinically relevant symptoms and possible directional relationships between MDD symptoms defining major depression episodes, which would help identify potential tailored interventions. This is the first study to investigate the network structure of VATSPSUD data using both undirected and directed network models.

Using network analysis to examine connections between Acceptance and Commitment Therapy (ACT) processes, internalizing symptoms, and well-being in a sample of undergraduates

BACKGROUND

Acceptance and Commitment Therapy (ACT) has been shown to be effective in treating internalizing symptoms. Understanding which ACT processes are most closely linked to certain symptoms may help develop targeted treatments. Network analysis an approach to gain insight into the interconnection between processes and the downstream benefits of targeting a particular process. However, limited work to date has explored networks involving ACT processes specifically.

METHODS

Undergraduate students (N = 447; 76.5 % female; 89.5 % White/Non-Hispanic) completed online questionnaires. The ACT processes assessed included experiential avoidance (AAQ-II), openness, awareness, and engagement (CompACT), and tacting ability (TOF), and internalizing symptoms/well-being (IDAS-II). Zero-order and partial correlation networks were examined as well as resulting communities.

RESULTS

In the association network, dysphoria and experiential avoidance, and suicidality (in the concentration network only) were central nodes. In community analyses, experiential avoidance had the strongest influence in the association network, whereas well-being had the strongest influence in the concentration network. Auto-detected communities were also evaluated.

LIMITATIONS

The present study was cross-sectional and included a largely White, female, undergraduate sample. This limits generalizability to more diverse, clinical, or general community populations. Potential concerns about data are also noted including low reliability on the TOF and two skewed domains on the IDAS-II which may impact stability of centrality metrics.

CONCLUSIONS

Well-being, dysphoria, and suicidality may be important process-based treatment targets. Further work is needed with diverse samples and using longitudinal designs to examine within person change of the associations between ACT processes and internalizing symptoms.

Using network analysis to explore the key bridge symptoms between posttraumatic stress symptoms and posttraumatic growth among survivors 10 years after the Wenchuan earthquake in China

Despite previous research has illustrated there is high-coexistence between posttraumatic stress disorder (PTSD) and posttraumatic growth (PTG) in the aftermath of traumatic events, few studies have conceptualized the coexistence mechanism of the two psychological phenomena. Using the network analysis, this study aimed to identify the key bridge symptoms and compare sex differences between PTSD symptoms and PTG elements in survivors 10 years after the Wenchuan earthquake in China. A total of 744 survivors 10 years after the Wenchuan earthquake in China completed self-reported questionnaires on demographics, PTSD symptoms (4-item of Posttraumatic Stress Disorder Checklist), and PTG (10-item of Posttraumatic Growth Inventory). Network analysis was used to identify the network structure of PTSD symptoms and elements of PTG, along with bridge symptoms. Additionally, sex differences in the network structure were compared by the Network Comparison Test. Results revealed that the network of PTSD symptoms and elements of PTG was robust to stability and accuracy tests. The key bridge symptoms in the network were "Stronger religious faith", "Changed priorities", and "Easily startled". There were significant differences in network global strength across sex, and network structure across the severity of property loss other than house damage. Future interventions targeting the three key bridge symptoms are expected to relieve the severity of PTSD and promote growth following exposure to traumatic events.