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.El enfoque de redes para el trastorno de estrés postraumático: Una revisión sistemática Antecedentes: La literatura empírica los estudios de análisis en redes de síntomas de estrés postraumático (SEPT) ha crecido rápidamente en los últimos años. Objetivos: Nuestro objetivo fue el evaluar las características de estos estudios y, de ser posible, evaluar cuáles eran aquellos síntomas más cardinales y cuáles no, y cuáles eran los enlaces más fuertes en las redes de los SEPT. Métodos: La presente revisión sistemática, realizada en PsycInfo, Medline, y Web of Science, sintetiza los hallazgos de 20 estudios transversales en redes sobre SEPT que se basaron sobre información transversal, y que fueron aceptados para publicación entre enero de 2010 y noviembre de 2018 (PROSPERO ID: CRD42018112825). Resultados: Los resultados indicaron que los estudios en redes investigaron un amplio rango de muestras, y que la mayoría de estudios emplearon enfoques analíticos similares, incluyendo el análisis de estabilidad. Solo la centralidad de la fuerza fue generalmente adecuadamente estable. Se informó consistentemente que la amnesia tenía la fuerza más baja, mientras que había una heterogeneidad sustancial con respecto a qué nodos tenían la centralidad de la fuerza más alta. Los pesos de los enlaces de red más fuertes se encontraban, por lo general, dentro de cada racimo de síntomas para trastorno de estrés postraumático contemplados en el DSM IV/DSM 5. Conclusiones: Se necesitan estudios derivados de hipótesis para determinar si la heterogeneidad de las redes resultó de las diferencias en las muestras, o si resultaron del producto de cuestiones metodológicas subyacentes.

Background: Network analysis is an emerging methodology for investigating psychopathological symptoms. Given the unprecedented number of refugees and the increased prevalence of mental disorders such as posttraumatic stress disorder (PTSD) in this population, new methodologies that help us better to understand psychopathology in refugees are crucial. Objective: The objective of this study was to explore the network structure and centrality indices of DSM-5 PTSD symptoms in a cross-sectional clinical sample of 151 severely traumatized refugees with and without a formal PTSD diagnosis. Method: The R-packages qgraph and bootnet were used to estimate the structure of a PTSD symptom network and its centrality indices. In addition, robustness and significance analyses for the edges weights and the order of centrality were performed. Results: Three pairs of symptoms showed significantly stronger connections than at least half of the other connections: hypervigilance and exaggerated startle response, intrusion and difficulties falling asleep, and irritability or outbursts of anger and self-destructive or reckless behaviour. Emotional cue reactivity had the highest centrality and trauma-related amnesia the lowest. Conclusion: Although only 51.0% of participants fulfilled criteria for a probable PTSD diagnosis, emotional cue reactivity showed the highest centrality, emphasizing the importance of emotional trauma reminders in severely traumatized refugees attending an outpatient clinic. However, due to the small sample size, the results should be interpreted with care.

Background In the network approach to psychopathology, psychiatric disorders are considered networks of causally active symptoms (nodes), with node centrality hypothesized to reflect symptoms’ causal influence within a network. Accordingly, centrality measures have been used in numerous network-based cross-sectional studies to identify specific treatment targets, based on the assumption that deactivating highly central nodes would proliferate to other nodes in the network, thereby collapsing the network structure and alleviating the overall psychopathology (i.e., the centrality hypothesis). Methods Here, we summarize three types of evidence pertaining to the centrality hypothesis in psychopathology. First, we discuss the validity of the theoretical assumptions underlying the centrality hypothesis in psychopathology. We then summarize the methodological aspects of extant studies using centrality measures as predictors of symptom change following treatment, while delineating their main findings and several of their limitations. Finally, using a specific dataset of 710 treatment-seeking patients with posttraumatic stress disorder (PTSD) as an example, we empirically examine node centrality as a predictor of therapeutic change, replicating the approach taken by previous studies, while addressing some of their limitations. Specifically, we investigated whether three pre-treatment centrality indices (strength, predictability, and expected influence) were significantly correlated with the strength of the association between a symptom’s change and the change in the severity of all other symptoms in the network from pre- to post-treatment (Δnode-Δnetwork association). Using similar analyses, we also examine the predictive validity of two simple non-causal node properties (mean symptom severity and infrequency of symptom endorsement). Results Of the three centrality measures, only expected influence successfully predicted how strongly changes in nodes/symptoms were associated with change in the remainder of the nodes/symptoms. Importantly, when excluding the amnesia node, a well-documented outlier in the phenomenology of PTSD, none of the tested centrality measures predicted symptom change. Conversely, both mean symptom severity and infrequency of symptom endorsement, two standard non-network-derived indices, were found to be more predictive than expected influence and remained significantly predictive also after excluding amnesia from the network analyses. Conclusions The centrality hypothesis in its current form is ill-defined, showing no consistent supporting evidence in the context of cross-sectional, between-subject networks.

Objective: The current SARS-CoV-2 pandemic poses various challenges for health care workers (HCWs). This may affect their mental health, which is crucial to maintain high quality medical care during a pandemic. Existing evidence suggests that HCWs, especially women, nurses, frontline staff, and those exposed to COVID-19 patients, are at risk for anxiety and depression. However, a comprehensive overview of risk and protective factors considering their mutual influence is lacking. Therefore, this study aimed at exploring HCWs' mental health during the SARS-CoV-2 pandemic in Switzerland, investigating the independent effect of various demographic, work- and COVID-related factors on HCWs' mental health.Methods: In an exploratory, cross-sectional, nation-wide online survey, we assessed demographics, work characteristics, COVID-19 exposure, and anxiety, depression, and burnout in 1,406 HCWs during the beginning of the SARS-CoV-2 pandemic in Switzerland. Network analysis was used to investigate the associations among the included variables.Results: Women (compared to men), nurses (compared to physicians), frontline staff (compared to non-frontline workers), and HCWs exposed to COVID-19 patients (compared to non-exposed) reported more symptoms than their peers. However, these effects were all small. Perceived support by the employer independently predicted anxiety and burnout after adjustment for other risk factors.Conclusion: Our finding that some HCWs had elevated levels of anxiety, depression, and burnout underscores the importance to systematically monitor HCWs' mental health during this ongoing pandemic. Because perceived support and mental health impairments were negatively related, we encourage the implementation of supportive measures for HCWs' well-being during this crisis.