Posttraumatic Stress Disorder Symptom Network Analysis in U.S. Military Veterans: Examining the Impact of Combat Exposure

Longitudinal changes in the PTSD symptom network following trauma-focused treatment in military populations: Identifying central symptoms and the role of military sexual trauma

Posttraumatic stress disorder (PTSD) is a debilitating condition affecting military populations, with a higher prevalence compared to the general population. Despite the development of first-line trauma-focused treatments such as Cognitive Processing Therapy (CPT) and Prolonged Exposure Therapy (PE), a significant proportion of patients continue to experience persistent PTSD symptoms following treatment. This study utilized network analysis to explore the PTSD symptom network's dynamics pre- and post- trauma-focused treatment and investigated the role of military sexual trauma (MST) history in shaping the network. Network analysis is a novel approach that can guide treatment target areas. The sample was comprised of 1648 service members and veterans who participated in a two-week intensive PTSD treatment program, which included completion of evidenced-based individual therapy as well as skill-building focused group therapy. PTSD severity was assessed using the PTSD Checklist for DSM-5 at baseline and post-treatment. Network analyses revealed strong connections within symptom clusters, with negative emotions emerging as one of the most central symptoms. Interestingly, the symptom network's overall structure remained stable following treatment, whereas global strength significantly increased. MST history did not significantly impact the network's structure or its change relative to treatment. Future research should further examine whether targeting negative emotions optimizes PTSD treatment outcomes for military populations.

A network analysis of pain intensity and pain-related measures of physical, emotional, and social functioning in US military service members with chronic pain

OBJECTIVE

The purpose of this study was to apply network analysis methodology to better understand the relationships between pain-related measures among people with chronic pain.

METHODS

We analyzed data from a cross-sectional sample of 4614 active duty service members with chronic pain referred to 1 military interdisciplinary pain management center between 2014 and 2021. Using a combination of Patient-Reported Outcomes Measurement Information System measures and other pain-related measures, we applied the "EBICglasso" algorithm to create regularized partial correlation networks that would identify the most influential measures.

RESULTS

Pain interference, depression, and anxiety had the highest strength in these networks. Pain catastrophizing played an important role in the association between pain and other pain-related health measures. Bootstrap analyses showed that the networks were very stable and the edge weights accurately estimated in 2 analyses (with and without pain catastrophizing).

CONCLUSIONS

Our findings offer new insights into the relationships between symptoms using network analysis. Important findings highlight the strength of association between pain interference, depression and anxiety, which suggests that if pain is to be treated depression and anxiety must also be addressed. What was of specific importance was the role that pain catastrophizing had in the relationship between pain and other symptoms suggesting that pain catastrophizing is a key symptom on which to focus for treatment of chronic pain.

Clinical and psychological implications of post-traumatic stress in firefighters: a moderated network study

Firefighters are frequently exposed to trauma and may experience a unique symptom presentation of post-traumatic stress. Prior research has identified stronger associations between certain post-traumatic stress symptoms (e.g. detachment, intrusions, physiological reactivity) using network analysis. However, little is known about the effects of symptom severity and emergency work-related trauma on symptom networks. The present study probed the network structure of post-traumatic stress symptoms in trauma-exposed firefighters (N = 871) to model the dynamic interactions of psychological symptoms. We developed a network of post-traumatic stress symptoms and a network of post-traumatic stress with clinical covariates and used moderated network modelling to assess the effects of having PTSD and experiencing work-related trauma on the networks. We identified high edge correlations between several nodes (e.g. startle/hypervigilance, internal/external cue avoidance, detachment/lack of interest) and high centrality of detachment, external cue avoidance, and flashbacks. Additionally, having PTSD moderated positive network associations between risk-taking and suicidality and between distorted blame and post-traumatic cognitions. Work-related trauma moderated negative associations between appetite gain and loss and appetite loss and suicidality. Findings suggest that targeting specific symptoms of detachment, external cue avoidance, and flashbacks could allow for the development of effective trauma-informed interventions for these populations.

The relationship between combat exposure and suicide risk in U.S. military veterans: Exploring the role of posttraumatic stress symptoms and religious coping

BACKGROUND

Rising suicide rates in the U.S. veteran population are a growing concern. Combat exposure has been identified as a potential predictor of suicide risk, but factors that may mediate the relation between combat exposure and suicide risk, and the role of potential coping mechanisms remain largely understudied. To address this gap, this study examined the association between lifetime combat exposure and current suicide risk; whether this association is mediated by posttraumatic stress disorder (PTSD) symptoms; and whether direct and/or indirect associations with combat exposure are moderated by organizational, non-organizational, and intrinsic religiosity.

METHODS

Data were analyzed from the National Health and Resilience in Veterans Study (2019-2020; n = 3843). Ordinary least squares and conditional process analyses were conducted to evaluate the conditional direct and indirect predictors of suicide risk.

RESULTS

PTSD symptoms significantly mediated the association between combat exposure and suicide risk. Intrinsic religiosity showed significant moderation and reduced the coefficient of PTSD symptoms predicting suicide risk but increased the coefficient of combat exposure predicting PTSD symptoms.

LIMITATIONS

In this cross-sectional, observational study, no conclusions can be made regarding causality.

CONCLUSIONS

Results of this study suggest a multifaceted relationship between combat exposure, PTSD, religiosity/spirituality, and suicide risk in U.S. veterans, and underscore the importance of PTSD and religious coping as part of ongoing suicide prevention efforts in this population.

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.

A network analysis investigating the associations between posttraumatic stress symptoms, markers of inflammation and metabolic syndrome

Chronic systemic inflammation has been implicated in trauma exposure, independent of a psychiatric diagnosis, and in posttraumatic stress disorder (PTSD) and its highly comorbid conditions, such as metabolic syndrome (MetS). The present study used network analysis to examine the interacting associations between pro-inflammatory cytokines, posttraumatic stress (PTS) symptoms and symptom clusters, and individual components of MetS, in a cohort of 312 participants (n = 139 PTSD cases, n = 173 trauma-exposed controls). Pro-inflammatory cytokines were measured in serum samples using immunoturbidimetric and multiplex assays. Three network models were assessed, and the decision on which model to use was guided by network stability estimates and denseness. Weak negative associations were observed between interleukin one beta (IL-1β) and detachment (D6) and irritability (E1); tumour necrosis factor alpha (TNFα) and hypervigilance (E3); and C-reactive protein (CRP) and emotional cue reactivity (B4), which could be due to high cortisol levels present in a female-majority cohort. Network models also identified positive associations between CRP and waist circumference, blood pressure, and high-density lipoprotein cholesterol (HDL-C). The strongest association was observed between CRP and waist circumference, providing evidence that central obesity is an important inflammatory component of MetS. Some networks displayed high instability, which could be due to the small pool of participants with viable cytokine data. Overall, this study provides evidence for associations between inflammation, PTS symptoms and components of MetS. Future longitudinal studies measuring pro-inflammatory cytokines in the immediate aftermath of trauma are required to gain better insight into the role of inflammation in trauma-exposure and PTSD.

Toward staging differentiation for posttraumatic stress disorder treatment

OBJECTIVES

Several medical and psychiatric disorders have stage-based treatment decision-making methods. However, international treatment guidelines for posttraumatic stress disorder (PTSD) fail to give specific treatment recommendations based on chronicity or stage of the disorder. There is convincing evidence of a finite range of PTSD symptom trajectories, implying that different phenotypes of the disorder can be distinguished, which are highly relevant for a staging typology of PTSD.

METHODS

State-of-the-art review building on prior work on staging models in other disorders as a mapping tool to identify and synthesize toward PTSD.

RESULTS

We propose a four-stage model of PTSD ranging from stage 0: trauma-exposed asymptomatic but at risk to stage 4: severe unremitting illness of increasing chronicity. We favor a symptom description in various chronological characteristics based on neurobiological markers, information processing systems, stress reactivity, and consciousness dimensions. We also advocate for a separate phenomenology of treatment resistance since this can yield treatment recommendations.

CONCLUSION

A staging perspective in the field of PTSD is highly needed. This can facilitate the selection of interventions that are proportionate to patients' current needs and risk of illness progression and can also contribute to an efficient framework to organize biomarker data and guide service delivery. Therefore, we propose that a neurobiologically driven trajectory-based typology of PTSD can help deduct several treatment recommendations leading to a more personalized and refined grid to strategize, plan and evaluate treatment interventions.

Symptoms of major depressive disorder and post-traumatic stress disorder in veterans with mild traumatic brain injury: A network analysis

Mild Traumatic Brain Injury (mTBI, or concussion) is a debilitating condition that often leads to persistent cognitive and mental health problems post-injury. Post-traumatic Stress Disorder (PTSD) and Major Depressive Disorder (MDD) are two most commonly occurring mental health problems following mTBI and are suggested to be strong contributors to the persistent post-concussion symptoms. Thus, it is important to understand the symptomatology of PTSD and MDD post-mTBI, to better inform targets for behavioral health interventions. Therefore, the current study examined the symptom structure of post-mTBI co-morbid PTSD and MDD through network approaches; we compared the network structure of participants with a positive mTBI screen (N = 753) to the network structure of participants with a negative mTBI screen (N = 2044); lastly, we examined a network of PTSD and MDD symptoms with clinical covariates in a positive mTBI sample. We found that feeling distant/cutoff (P10) and difficulty concentrating (P15) were the most central symptoms in the positive mTBI network and sleep problems were the most prominent bridge nodes across the disorders. No significant difference between the positive and negative mTBI network were found through network comparison tests. Moreover, anxiety and insomnia were strongly associated with sleep symptoms and irritability symptoms, and emotional support and resilience were potential buffers against most of the PTSD and MDD symptoms. The results of this study might be particularly useful for identifying targets (i.e., feeling distant, concentration and sleep problems) for screening, monitoring and treatment after concussion to better inform post-mTBI mental health care and to improve treatment outcomes.

Mapping post-traumatic stress disorder symptoms and quality of life among residents of Wuhan, China after the COVID-19 outbreak: A network perspective

OBJECTIVES

The Coronavirus Disease 2019 (COVID-19) outbreak may have a long-term impact on mental health in the general population. This study examined inter-relationships between post-traumatic stress disorder symptoms (PTSS) and quality of life (QOL) in Wuhan residents after the COVID-19 outbreak using network approach.

METHODS

A cross-sectional survey was conducted between May 25 and June 18, 2020. PTSS and QOL were measured using Chinese versions of the Post -Traumatic Stress Disorder Checklist - Civilian Version and the World Health Organization Quality of Life Questionnaire - brief version, respectively.

RESULTS

A total of 2598 participants were included. A network analysis revealed "Avoiding reminders", "Feeling emotionally numb", "Avoiding thoughts", "Hypervigilance", and "Reliving experiences" as the most central (influential) nodes in PTSS network models both before and after controlling for covariates. The connection between "Avoiding thoughts" and "Avoiding reminders" had the strongest edge. Three symptom communities were detected and can be summarized as "re-experiencing and avoidance", "negative changes in thinking and mood", and "hyperarousal". The bridge symptoms connecting PTSS and QOL were "Sleep disturbances", "Irritability", and "Loss of interest".

LIMITATIONS

Limitations included the cross-sectional study design, self-report measures in data collection, and lack of follow-ups beyond the initial phase of the pandemic.

CONCLUSIONS

PTSS were common among Wuhan residents even after the initial COVID-19 outbreak had passed. Attention should be paid to lingering symptoms of avoiding reminders, emotional numbness, avoiding thoughts, hypervigilance, and reliving experiences in treating PTSS related to the COVID-19 outbreak.

Order effects in PTSD network analysis: important implications for diagnostic conceptualization, treatment refinement, and research

BACKGROUND

For decades confirmatory factor analysis (CFA) has been the preeminent method to study the underlying structure of posttraumatic stress disorder (PTSD); however, methodological limitations of CFA have led to the emergence of other analytic approaches. In particular, network analysis has become a gold standard to investigate the structure and relationships between PTSD symptoms. A key methodological limitation, however, which has significant clinical implications, is the lack of data on the potential impact of item order effects on the conclusions reached through network analyses.

METHODS

The current study, involving a large sample (N = 5055) of active duty army soldiers following deployment to Iraq, assessed the vulnerability of network analyses and prevalence rate to item order effects. This was done by comparing symptom networks of the DSM-IV PTSD checklist items to these same items distributed in random order. Half of the participants rated their symptoms on traditionally ordered items and half the participants rated the same items, but in random order and interspersed between items from other validated scales. Differences in prevalence rate and network composition were examined.

RESULTS

The prevalence rate differed between the ordered and random item samples. Network analyses using the ordered survey closely replicated the conclusions reached in the existing network analyses literature. However, in the random item survey, network composition differed considerably.

CONCLUSION

Order effects appear to have a significant impact on conclusions reached from PTSD network analysis. Prevalence rates were also impacted by order effects. These findings have important diagnostic and clinical treatment implications.

Network structure of PTSD symptoms in Chinese male firefighters

The network perspective of mental disorder offers a novel way of understanding the psychopathology of post-traumatic stress disorder (PTSD). In this framework, PTSD may arise from direct interactions between its symptoms. In the present study, we used the Post-Traumatic Stress Disorder Checklist-civilian Version (PCL-C) to investigate the network structure of PTSD symptoms in 994 Chinese male firefighters. We also calculated the micro (i.e., edges weight and node expected influence) and middle (i.e., community) indicators of the final network. Nine strongest edges existed in the final network were from the same dimension of PCL-C, like "avoidance of thoughts" and "avoidance of reminders". Symptoms "emotional reactivity", "avoidance of reminders" and "exaggerated startle response" had the highest expected influence. As for the results of community detection, the spinglass and walktrap algorithm detected the same three communities which are slightly different from the original dimensions of PCL-C (i.e., symptoms "avoidance of thoughts", "avoidance of reminders" and "trauma-related amnesia" of avoidance dimension of PCL-C were added to the intrusion dimension of PCL-C). The present study explored the network structure of PTSD symptoms in Chinese male firefighters and provided several implications for clinical prevention and intervention to address the mental health needs in this special group.

The longitudinal course of posttraumatic stress disorder symptoms in war survivors: Insights from cross-lagged panel network analyses

Many war survivors suffer from chronic posttraumatic stress disorder (PTSD). Unraveling the complexities of PTSD symptoms over time is crucial for understanding this condition. Going beyond a common pathogenic pathway perspective, we applied the network approach to psychopathology to analyze longitudinal data from war survivors with PTSD in five Balkan countries approximately 8 years after war in the region and a follow-up assessment 1 year later (N = 698). PTSD diagnosis was established using the Mini-International Neuropsychiatric Interview, and PTSD symptoms were assessed using the Impact of Events Scale-Revised. Undirected cross-sectional networks for baseline and follow-up revealed no differences in the overall connectivity between these two networks. The intrusion symptom "I had waves of strong feelings about it" had the strongest expected influence centrality. Directed cross-lagged panel network models indicated that hyperarousal symptoms predicted other PTSD symptoms from baseline to follow-up, whereas several avoidance symptoms were predicted by other PTSD symptoms. The findings underscore the importance of emotional reactions and further suggest that hyperarousal symptoms may influence other PTSD symptoms. Future research should investigate causality and associations between between-person and within-person networks.

Behavioral Changes in Preschool- and School-Age Korean Children: A Network Analysis

The relationships between symptoms that comprise behavioral problems in children can be traced longitudinally to provide long-term support. This study identified signs that should be considered important in school age children by tracking changes in the relationships between different symptoms of behavioral problems in preschool and school age children. This study used Gaussian graphical network analysis to clarify the interaction of the overall subscales constituting the K-CBCL (Korean Child Behavior Checklist) and centrality in the network. In the Panel Study on Korean Children (PSKC), the K-CBCL/1.5–5 was used for children up to age six (first grade, elementary school), and the K-CBCL/6–18 was used for older children. In this study, 1323 PSKC samples (boys, n = 671; girls, n = 652) were used to distinguish nonclinical and (sub)clinical groups (T-score ≥ 60) compared to node centrality in each group’s CBCL subscale networks. Depression/anxiety was a persistent core symptom of the behavioral problem network in 5- and 7-year-old children. A new core symptom in 7-year-old children was posttraumatic stress problems added in version CBCL/6-18. Based on these results, it is necessary to consider both anxiety/depression and posttraumatic stress problems in preschool children to support the adaptation of school-age children.

What Happened in the Hippocampal Axon in a Rat Model of Posttraumatic Stress Disorder

Studies from postmortem and animal models have revealed altered synapse morphology and function in the brain of posttraumatic stress disorder (PTSD). And the effects of PTSD on dendrites and spines have been reported, however, the effection on axon include microtubule (MT) and synaptic vesicles of presynaptic elements remains unknown. Hippocampus is involved in abnormal memory in PTSD. In the present study, we used the single prolonged stress (SPS) model to mimic PTSD. Quantitative real-time polymerase chain reaction (RT-qPCR) and high-throughput sequencing (GSE153081) were utilized to analyze differentially expressed genes (DEGs) in the hippocampus of control and SPS rats. Immunofluorescence and western blotting were performed to examine change in axon-related proteins. Synaptic function was evaluated by measuring miniature excitatory postsynaptic currents (mEPSCs). RNA-sequencing analysis revealed 230 significantly DEGs between the control and SPS groups. Gene Ontology analysis revealed upregulation in axonemal assembly, MT formation, or movement, but downregulation in axon initial segment and synaptic vesicles fusion in the hippocampus of SPS rats. Increased expression in tau, β-tubulin MAP1B, KIF9, CCDC40, DNAH12 and decreased expression in p-tau, stathmin suggested SPS induced axon extension. Increased protein expression in VAMP, STX1A, Munc18-1 and decreased expression in synaptotagmin-1 suggested SPS induced more SNARE complex formation but decreased ability in synaptic vesicle fusion to presynaptic active zone membrane in the hippocampus of SPS rats. Further, low mEPSC frequency in SPS rats indicated dysfunction in presynaptic membrane. These results suggest that axon extension and synaptic vesicles fusion abnormality are involved in dysfunction of PTSD.

The structure of PTSD. Development of the Post Traumatic Symptom scale from a clinician-based perspective

BACKGROUND

Nations marked by a Marxist-Leninist ideology have suffered greatly due to a culture of abuse emphasized by the absolute absence of psychology, thus contributing to a diminished ability in recognizing the consequences of traumatic experiences.

OBJECTIVE

To improve the assessment of the presence and severity of posttraumatic stress disorder (PTSD) in such a cultural context, our paper aimed at developing an alternative self-report measure for PTSD - the Post Traumatic Symptom Scale (PTSs), developed by clinicians with wide relevant expertise, based on the natural language people use to describe its subjective experience. This research used multiple samples consistent with the corresponding objectives. Mokken Scale Analysis and the Classical Test Theory were both employed. The proposed scale was tested against five competing PTSD models, whilst also investigating the symptoms' clusters in two different samples by using, to our knowledge, a network analysis approach for the first time.

METHOD

The results indicated excellent psychometric properties regarding internal consistency and temporal reliability, as well as convergent and discriminant validity. The results of MSA showed that the scale fully conforms to the assumptions of the monotone homogeneity model, interpreted as positive evidence for its use in clinical purposes. The factor analyses pointed that the newer models outperformed the standard DSM-5 model, with bifactor models displaying better fit indexes than second-order models. Finally, a distinct pattern of symptom activation in the high-risk group (i.e. first-responders) was found, bringing support for symptoms overlapping between PTSD and affective disorders, thus reinforcing the idea of bridge symptoms which has significant clinical implications.

RESULTS

This study presents an alternative sound instrument for measuring PTSD symptomatology focused on how people naturally describe their subjective experiences. Theoretical and practical implications are discussed alongside limitations.

HIGHLIGHTS

The construction of PTSs encompasses cultural trauma and one's subjective experience.PTSs was tested against the five major competing models of PTSD.Network analyses suggest different patterns in a student sample vs. a first-responders one, with the accent on the negative alterations in cognitions and mood (NACM) model.

Network Dynamics in Elemental Assimilation and Metabolism

Metabolism and physiology frequently follow non-linear rhythmic patterns which are reflected in concepts of homeostasis and circadian rhythms, yet few biomarkers are studied as dynamical systems. For instance, healthy human development depends on the assimilation and metabolism of essential elements, often accompanied by exposures to non-essential elements which may be toxic. In this study, we applied laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to reconstruct longitudinal exposure profiles of essential and non-essential elements throughout prenatal and early post-natal development. We applied cross-recurrence quantification analysis (CRQA) to characterize dynamics involved in elemental integration, and to construct a graph-theory based analysis of elemental metabolism. Our findings show how exposure to lead, a well-characterized toxicant, perturbs the metabolism of essential elements. In particular, our findings indicate that high levels of lead exposure dysregulate global aspects of metabolic network connectivity. For example, the magnitude of each element's degree was increased in children exposed to high lead levels. Similarly, high lead exposure yielded discrete effects on specific essential elements, particularly zinc and magnesium, which showed reduced network metrics compared to other elements. In sum, this approach presents a new, systems-based perspective on the dynamics involved in elemental metabolism during critical periods of human development.

The symptom structure of posttraumatic stress disorder and co-morbid depression among college students with childhood abuse experience: A network analysis

BACKGROUND

Posttraumatic stress disorder (PTSD) and depression are highly co-morbid among individuals with childhood abuse history, while the mechanism of the co-morbidity is highly debated. This study sought to extent the work among college students with network analysis, which is a novel method that sees the co-morbidity from a symptom interacting perspective.

METHODS

Data was collected from 476 college students who were assessed to have childhood abuse history, PTSD and depression at the same time, using Childhood Trauma Questionnaire- Short Form, PTSD Checklist for DSM-5 and The Center for Epidemiological Studies Depression. We created a Graphical Gaussian Model (GGM) network to show associations between symptom pairs and a Directed Acyclic Graph (DAG) to estimate potential casual relationships among symptoms.

RESULTS

The GGM network was reliably stable, feeling sad (Depression) and trouble experiencing positive feelings (PTSD) were the most central nodes. Trouble experiencing positive feelings and several negative affect symptoms, sleep problems and difficulty in concentrating were acting as important bridging nodes. The DAG network suggested the key triggering roles of exaggerated startle (PTSD) and several re-experiencing symptoms.

LIMITATIONS

The study used cross-sectional data and self-reported measures. Results from network analysis could be affected by scale factors and contain spurious correlations.

CONCLUSIONS

In the childhood-abuse-related co-morbid structure, several negative affect symptoms both in PTSD and depression have pivotal roles, hyper-arousal symptoms and re-experiencing symptoms could trigger the co-morbid structure. Illustrating the strength and limitations of network analysis, this study help target the potentially influential symptoms for better clinical intervention.

Connecting the dots: A network approach to post‐traumatic stress symptoms in Chinese healthcare workers during the peak of the Coronavirus Disease 2019 outbreak

Healthcare workers are at elevated risk to develop symptoms of post-traumatic stress disorder (PTSD) in response to an outbreak of a highly infectious disease. The current study set-out to model the complex interrelations between PTSD symptoms during the peak of the Coronavirus Disease 2019 outbreak in 291 Chinese healthcare workers and 291 matched control cases that were selected from the general population. For this purpose, we estimated regularized partial correlation networks. Within the network of healthcare workers, we observed a central role for avoidance of reminders of the traumatic event, physiological cue reactivity, anger/irritability, re-experiencing, and startle. We identified three clusters of closely interconnected PTSD symptoms in healthcare workers, consisting of (a) symptoms of re-experiencing and anxious arousal, (b) symptoms of avoidance and amnesia and (c) symptoms of emotional numbing and dysphoric arousal. Respectively, startle, avoidance of reminders and feeling detached emerged as bridging nodes in these communities. Although yielding highly similar network models, the PTSD symptom structure of healthcare workers showed several unique features compared to the matched control sample. This is informative for interventions aimed at targeting PTSD symptoms in healthcare workers in the context of a public health emergency.

Unraveling specifics of mental health symptoms in war survivors who fled versus stayed in the area of conflict using network analysis

BACKGROUND

War survivors often report symptoms of post-traumatic stress disorder (PTSD), depression, anxiety, and somatization. Hence, understanding symptom constellations among different populations of war survivors is critical.

METHODS

Using the network approach to psychopathology, we examined symptom centrality for these conditions in war survivors from Balkan countries who had stayed in the area of former conflict compared to those individuals from Balkan countries who had fled to Western European countries (N = 4,167) with the Impact of Events Scale-Revised and the Brief Symptom Inventory. We further compared networks for war survivors who met criteria for PTSD-diagnosis (assessed with the MINI-International Neuropsychiatric Interview) to those without PTSD-diagnosis.

RESULTS

Globally, networks were similar across the groups, whereas specific differences emerged in symptom centrality. More consistencies were found between PTSD and Western country networks, which may be partially explained by a higher prevalence of PTSD in those who had fled to Western European than in those who had stayed in the Balkan countries.

LIMITATIONS

Given the cross-sectional nature of our data, the directionality of edges in our networks remains unclear. Further, higher levels of trauma exposure and symptom severity in Western country participants may have confounded results.

CONCLUSIONS

The PTSD findings are in line with previous research on PTSD symptoms. They further provide novel insights into depressive, anxiety, and somatization symptoms in survivors of war. These findings need to be substantiated and call for future intervention studies that test the effects of targeting central symptoms we identified in our study.

Exposure to combat incidents within military and civilian populations as possible correlates of potentially morally injurious events and moral injury outcomes among Israeli combat veterans

OBJECTIVES

Exposure to potentially morally injurious events (PMIEs) is considered a necessary but insufficient determinant of moral injury (MI) outcomes. However, a question remains regarding possible acts and the necessary features of PMIEs that should be considered transgressive and might lead to MI psychopathological outcomes. We aim to examine the links between exposure to combat incidents within civilian Palestinian populations (CPPs), PMIEs and MI-related outcomes of posttraumatic stress disorder (PTSD) symptoms (PTSS), trauma-related guilt and shame. We also aim to explore the mediating roles of subjective perceptions of PMIEs in the relationship between exposure to combat incidents within CPP and MI-related outcomes among combat veterans.

METHOD

A volunteer sample of 716 Israeli combat veterans responded to self-report questionnaires in a cross-sectional design study.

RESULTS

Exposure to combat incidents within CPP has been primarily associated with perpetration based PMIEs and MI-related guilt outcomes. Importantly, betrayal-based PMIEs mediated the association between reports of being the victim of verbal violence by militants and/or civilians and MI outcomes. Moreover, perpetration-based PMIEs mediated associations between reports of personal acts, or witnessing acts, of physical and verbal violence and degradation by militants and/or civilians, and MI outcomes.

CONCLUSIONS

Military incidents within civilian populations are related to subjective perceptions of PMIEs and MI-related psychopathological outcomes. While betrayal-based experiences might serve as a mechanism to being a victim of verbal violence and MI outcomes, perpetration-based experiences might serve as mechanisms to physical, verbal and degradation incidents and MI outcomes.

Mapping the Presence of Anxiety Symptoms in Adults With Major Depressive Disorder

Background: Patients with major depressive disorder (MDD) often present with co-occurring anxiety symptoms. The network method provides a novel view on understanding the co-occurrence of depressive and anxiety symptoms. Thus, the purpose of our study was to explore it by applying network analysis methods. Methods: We used electronic medical records from West China Hospital in China. In total, 3,424 patients who met the criteria for MDD were included. R-studio 3.6 was used to estimate the network structure. First, we estimated the network structure of depression and anxiety symptoms using the graphic LASSO algorithm. Then, we estimated the centrality indices of nodes to determine which symptoms are more central in the network. We then estimated the bridge centrality indices using the bridge function via the R package networktools. Results: Some strong connections were found like "easy to wake up," "wake up early," and "difficulty falling asleep," "suicidal thoughts," and "hopelessness." "Depressed mood," "somatic anxiety," "hopelessness," "anxiety mood," and "tension" have the higher centrality indices. Results revealed eight bridge symptoms (e.g., concentration/memory difficulty, gastrointestinal symptoms) in the co-occurrence network structure. Conclusions: This research suggests that the described approach in mapping the presence of anxiety symptoms in individuals with major depression might potentially increase diagnostic precision and help choose more targeted interventions and potentially reduce the occurrence of treatment resistance.

Evolution of the network pattern of posttraumatic stress symptoms among children and adolescents exposed to a disaster

Growing network approach analyses of posttraumatic stress disorder (PTSD) have enhanced the knowledge of PTSD symptomatology. This study aims to explore changes in network patterns of PTSD symptoms among youth survivors following the Zhouqu debris flow through a network approach. A two-year longitudinal study was conducted to follow 1460 children and adolescents at 3, 15, and 27 months after the disaster. Symptoms with high centrality varied at different time points. Sleep problems and nightmares exhibited high centrality at 3 months, and their centrality decreased over time, while the centrality of physiological cue reactivity and flashbacks increased over time and reached a high level at 27 months. The global connectivity of the network was stronger at 27 months than at 3 and 15 months. These findings provide novel insights into youths' PTSD symptom evolution. Temporal differences in PTSD symptoms merit more attention from researchers. Different core symptoms in acute and chronic PTSD structures should be treated as targets at different stages following trauma in clinical practice.

Bayesian Network Structure and Predictability of Autistic Traits

The aim of this work is to explore the construct of autistic traits through the lens of network analysis with recently introduced Bayesian methods. A conditional dependence network structure was estimated from a data set composed of 649 university students that completed an autistic traits questionnaire. The connectedness of the network is also explored, as well as sex differences among female and male subjects in regard to network connectivity. The strongest connections in the network are found between items that measure similar autistic traits. Traits related to social skills are the most interconnected items in the network. Sex differences are found between female and male subjects. The Bayesian network analysis offers new insight on the connectivity of autistic traits as well as confirms several findings in the autism literature.

PTSD networks of veterans with combat versus non-combat types of index trauma

BACKGROUND

Network analysis has become popular among PTSD researchers for studying causal structure or interrelationships among symptoms. However, some have noted that results do not seem to be consistent across studies. Preliminary evidence suggests that trauma type may be one source of variability.

METHODS

The current study sought to examine the PTSD networks of veterans with combat versus non-combat index trauma. Participants included 944 veterans who completed the PTSD Checklist for DSM-5 at intake at two VA PTSD clinics.

RESULTS

There were many similarities between the combat and non-combat trauma networks, including strong edges between symptoms that were theoretically related or similar (e.g., avoidance) and negative emotion being a highly central symptom. However, correlations of edge weights (0.509) and node centrality (0.418) across networks suggested moderate correspondence, and there appeared to be some differences associated with certain symptoms. Detachment was relatively more central and the connections of negative emotion with blame and lack of positive emotion with reckless behavior were stronger for veterans with combat-related index trauma.

LIMITATIONS

The data were cross-sectional, which limits the ability to infer directional relationships between symptoms. In addition, the sample was likely not large enough to directly test for differences between networks via network comparison tests.

CONCLUSIONS

Although there were many similarities, results also suggested some variability in PTSD networks associated with combat versus non-combat index trauma that could have implications for conceptualizing and treating PTSD among veterans.

Symptom structure of PTSD and co-morbid depressive symptoms - a network analysis of combat veteran patients

BACKGROUND

Despite extensive research, symptom structure of posttraumatic stress disorder (PTSD) is highly debated. The network approach to psychopathology offers a novel method for understanding and conceptualizing PTSD. However, extant studies have mainly used small samples and self-report measures among sub-clinical populations, while also overlooking co-morbid depressive symptoms.

METHODS

PTSD symptom network topology was estimated in a sample of 1489 treatment-seeking veteran patients based on a clinician-rated PTSD measure. Next, clinician-rated depressive symptoms were incorporated into the network to assess their influence on PTSD network structure. The PTSD-symptom network was then contrasted with the network of 306 trauma-exposed (TE) treatment-seeking patients not meeting full criteria for PTSD to assess corresponding network differences. Finally, a directed acyclic graph (DAG) was computed to estimate potential directionality among symptoms, including depressive symptoms and daily functioning.

RESULTS

The PTSD symptom network evidenced robust reliability. Flashbacks and getting emotionally upset by trauma reminders emerged as the most central nodes in the PTSD network, regardless of the inclusion of depressive symptoms. Distinct clustering emerged for PTSD and depressive symptoms within the comorbidity network. DAG analysis suggested a key triggering role for re-experiencing symptoms. Network topology in the PTSD sample was significantly distinct from that of the TE sample.

CONCLUSIONS

Flashbacks and psychological reactions to trauma reminders, along with their strong connections to other re-experiencing symptoms, have a pivotal role in the clinical presentation of combat-related PTSD among veterans. Depressive and posttraumatic symptoms constitute two separate diagnostic entities, but with meaningful between-disorder connections, suggesting two mutually-influential systems.

Reduced awareness of surroundings is the most central domain in the network structure of posttraumatic stress disorder symptoms

Backgroud: Network models suggest that co-occurring symptoms are conceptualized as a syndrome due to interactions, rather than a categorical entity with an underlying common cause.Aim: Our study aimed to examine the network structure and centrality of Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV posttraumatic stress disorder (PTSD) symptoms, including essential and associated features.Methods: We constructed a network structure of 21 intertwined symptoms, evaluated with the Clinician-Administered PTSD Scale (CAPS), in 249 PTSD patients who have been exposed to various types of traumatic events (73% being traffic or other accidents) and were beginning psychiatric treatment. In addition, we estimated the centrality of the 21 symptoms through network analysis. Each of the symptoms was defined as ordered-categorical variables.Results: The network, with 21 symptoms, demonstrated a strong correlation among difficulty concentrating, reduced awareness of surroundings, and derealization. In addition, reduced awareness of surroundings was estimated as the most central symptom, whereas inability to recall important aspects of trauma was estimated as the least central symptom in the subjects. A community-detection analysis estimated that the 21 PTSD symptoms were organized into three clinically meaning clusters.Conclusion: Although dissociative features have been defined as associative symptoms rather than essential symptoms for the DSM diagnostic criteria, reduced awareness of surroundings may be regarded as the most central symptom in patients in the early phase of PTSD. Thus, evaluation and intervention for dissociative features may be needed in clinical practice and studies on PTSD.

Exploring network structure and central items of the Narcissistic Personality Inventory

OBJECTIVES

The aim of this work is to explore the Narcissistic Personality Inventory (NPI) using network analysis in a dataset of 942 university students from the French-speaking part of Belgium.

METHODS

We estimated an Ising Model for the forty items in the questionnaire and explored item interconnectedness with strength centrality. We provide in the supplementary materials the dataset used for the analyses as well as the full code to ensure the reproducibility of our results.

RESULTS

The NPI is presented as an overall positively connected network with items from entitlement, authority and superiority reporting the highest centrality estimates.

CONCLUSIONS

Network analysis highlights new properties of items from the NPI. Future studies should endeavor to replicate our findings in other samples, both clinical and non-clinical.

The network approach to posttraumatic stress disorder: a systematic review

Background: The empirical literature of network analysis studies of posttraumatic stress symptoms (PTSS) has grown rapidly over the last years. Objective: We aimed to assess the characteristics of these studies, and if possible, the most and least central symptoms and the strongest edges in the networks of PTSS. Method: The present systematic review, conducted in PsycInfo, Medline, and Web of Science, synthesizes findings from 20 cross-sectional PTSS network studies that were accepted for publication between January 2010 and November 2018 (PROSPERO ID: CRD42018112825). Results: Results indicated that the network studies investigated a broad range of samples and that most studies used similar analytic approaches including stability analysis. Only strength centrality was generally adequately stable. Amnesia was consistently reported to have lowest strength, while there was substantial heterogeneity regarding which nodes had highest strength centrality. The strongest edge weights were typically within each DSM-IV/DSM-5 PTSD symptom cluster. Conclusions: Hypothesis-driven studies are needed to determine whether the heterogeneity in networks resulted from differences in samples or whether they are the product of underlying methodological reasons.

Associations between moral injury, PTSD clusters, and depression among Israeli veterans: a network approach

Background: Moral Injury (MI) is one of the adverse consequences of combat. Following exposure to potentially morally injurious events (PMIEs)--events perceived as violations of deep moral beliefs by oneself or trusted individuals--a significant minority of veterans could develop posttraumatic stress disorder (PTSD) and depression. Objective: The current study represents the first attempt to apply a network analysis model to examine an exploratory empirical conceptualization of a network of PMIEs during military service, post-traumatic stress disorder (PTSD) symptom clusters, depression, and combat exposure among Israel Defence Forces veterans. Method: A volunteer sample of 191 Israeli combat veterans were recruited during 2017, and completed validated self-report questionnaires tapping PMIEs, PTSD, and depression in a cross-sectional design study. A regularized Gaussian graphical model was estimated. Results: Network analysis revealed strong bridge associations between the PTSD nodes and most of the PMIEs nodes. The nodes of PMIE-betrayal and PTSD negative alterations in cognitions and mood (NACM) symptom cluster were found to have a bridging function between other PMIEs and PTSD. Depression was found to be connected to most of the PMIEs and PTSD nodes. Conclusions: The study's findings offer an overview of the complex relationships between PMIEs and PTSD clusters among Israeli veterans. PMIEs--notably, betrayal-based experiences--are related to PTSD clusters directly and through depressive symptoms. Some possible mechanisms for the links between PMIEs and PTSD and the clinical implications related to specific interventions are discussed.

Changes in the network structure of posttraumatic stress disorder symptoms at different time points among youth survivors: A network analysis

BACKGROUND

Despite considerable studies focused on the symptoms of posttraumatic stress disorder (PTSD), little is understood about how symptoms of PTSD change over time. The study aimed to use a network analysis approach to understand the nature of the association between PTSD symptoms at different time points among children and adolescents who experience an earthquake.

METHODS

A longitudinal study enrolled 1623 youth survivors who completed 3 assessments with the Children's Revised Impact of Event Scale at 2 weeks, 3 months and 6 months after the Lushan earthquake. The epicentre was Baoxing Country that located in the Ya'an city (Sichuan Province in China). A network analysis approach was used to investigate how symptom networks change at different time points.

RESULTS

A total of 1623 youth survivors (768 male and 855 female) completed three assessments. Different centrality symptoms existed at different time points. Flashback and upset by reminders were centrality symptoms at 2 weeks, 3 months and 6 months. The overall network connectivity was significantly stronger at 3 months than at 2 weeks (5.663 vs. 5.140, s = 0.523, p = 0.000), and significantly stronger at 6 months than at 2 weeks (6.094 vs. 5.663, s = 0.432, p = 0.020).

LIMITATIONS

Participants from a specific region might limit the generalizability of our results. A self-report questionnaire was used to assess PTSD symptoms.

CONCLUSIONS

Re-experience cluster (flashback and upset by reminders) and their interactions might play a key role in PTSD symptom evolution. Over time, the global connectivity becomes stronger, suggesting that youth survivors are more vulnerable in the chronic phases.

Network Approach to Items and Domains From the Toronto Alexithymia Scale

The aim of this study is to explore network structures of the Toronto Alexithymia Scale in a large sample of 1925 French-speaking Belgian university students and compare results with previous studies from different samples and tools to identify potential targets for clinical intervention. We estimated network models for the 20 items of the Toronto Alexithymia Scale and for its three domains difficulty identifying feelings, difficulty describing feelings, and externally oriented thinking. We explored item connectivity through node predictability (shared variance with other network components). We performed an exploratory graph analysis to explore the dimensionality of our data set and compare results with the original three-factor model; because a different model was proposed, we estimated an additional network structure on the new structure. Items from the Toronto Alexithymia Scale connect both within and between domains. The three-domain network identifies difficulty describing feelings as the most connected domain. The exploratory graph analysis reported that three items from externally oriented thinking form a new domain, distraction. In the new four-domain network, difficulty describing feelings remains the most interconnected domain; however, two negative connections are found. Our findings support the relative importance of identifying and describing feelings as a meaningful target for intervention.

Network Analysis and Precision Rehabilitation for the Post-concussion Syndrome

Some people experience persistent symptoms following a mild traumatic brain injury (MTBI), and the etiology of those symptoms has been debated for generations. Post-concussion-like symptoms are caused by many factors both before and after MTBI, and this non-specificity is the bedrock of the conundrum regarding the existence of the post-concussion syndrome. A latent model or common cause theory for the syndrome is inconsistent with the prevailing biopsychosocial conceptualization. It is the thesis of this paper that adopting a network perspective for persistent symptoms following MTBI, including the post-concussion syndrome, could lead to new insights and targeted treatment and rehabilitation strategies. The network perspective posits that symptoms co-occur because they are strongly inter-related, activating, amplifying, and mutually reinforcing, not because they arise from a common latent disease entity. This approach requires a conceptual shift away from thinking that symptoms reflect an underlying disease or disorder toward viewing inter-related symptoms as constituting the syndrome or disorder. The symptoms do not arise from an underlying syndrome—the symptoms are the syndrome. A network analysis approach allows us to embrace heterogeneity and comorbidity, and it might lead to the identification of new approaches to sequenced care. The promise of precision rehabilitation requires us to better understand the interconnections among symptoms and problems so that we can produce more individualized and effective treatment and rehabilitation.

Item and domain network structures of the Resilience Scale for Adults in 675 university students

AIMS

The Resilience Scale for Adults (RSA) is a questionnaire that measures protective factors of mental health. The aim of this paper is to perform a network analysis of the RSA in a dataset composed of 675 French-speaking Belgian university students, to identify potential targets for intervention to improve protective factors in individuals.

METHODS

We estimated a network structure for the 33-item questionnaire and for the six domains of resilience: perception of self, planned future, social competence, structured style, family cohesion and social competence. Node predictability (shared variance with surrounding nodes in the network) was used to assess the connectivity of items. An exploratory graph analysis (EGA) was performed to detect communities in the network: the number of communities detected being different than the original number of factors proposed in the scale, we estimated a new network with the resulting structure and verified the validity of the new construct which was proposed. We provide the anonymised dataset and code in external online materials (10.17632/64db36w8kf.2) to ensure complete reproducibility of the results.

RESULTS

The network composed of items from the RSA is overall positively connected with strongest connections arising among items from the same domain. The domain network reports several connections, both positive and negative. The EGA reported the existence of four communities that we propose as an additional network structure. Node predictability estimates show that connectedness varies among the items and domains of the RSA.

CONCLUSIONS

Network analysis is a useful tool to explore resilience and identify targets for clinical intervention. In this study, the four domains acting as components of the additional four-domain network structure may be potential targets to improve an individual's resilience. Further studies may endeavour to replicate our findings in different samples.