Comparing PTSD symptom networks in type I vs. type II trauma survivors

Research output: Contribution to journalResearch articleContributedpeer-review


  • Mina Stefanovic - , Ludwig Maximilian University of Munich (Author)
  • Thomas Ehring - , Ludwig Maximilian University of Munich (Author)
  • Charlotte E Wittekind - , Ludwig Maximilian University of Munich (Author)
  • Birgit Kleim - , University of Zurich (Author)
  • Judith Rohde - , University Psychiatric Clinics Basel (UPK) (Author)
  • Antje Krüger-Gottschalk - , University of Münster (Author)
  • Christine Knaevelsrud - , Free University of Berlin (Author)
  • Heinrich Rau - , German Federal Armed Forces Hospital Berlin (Author)
  • Ingo Schäfer - , University Hospital Hamburg Eppendorf (Author)
  • Julia Schellong - , Department of Psychotherapy and Psychosomatic Medicine (Author)
  • Anne Dyer - , Heidelberg University  (Author)
  • Keisuke Takano - , Ludwig Maximilian University of Munich (Author)


Background: Network analysis has gained increasing attention as a new framework to study complex associations between symptoms of post-traumatic stress disorder (PTSD). A number of studies have been published to investigate symptom networks on different sets of symptoms in different populations, and the findings have been inconsistent. Objective: We aimed to extend previous research by testing whether differences in PTSD symptom networks can be found in survivors of type I (single event; sudden and unexpected, high levels of acute threat) vs. type II (repeated and/or protracted; anticipated) trauma (with regard to their index trauma). Method: Participants were trauma-exposed individuals with elevated levels of PTSD symptomatology, most of whom (94%) were undergoing assessment in preparation for PTSD treatment in several treatment centres in Germany and Switzerland (n = 286 with type I and n = 187 with type II trauma). We estimated Bayesian Gaussian graphical models for each trauma group and explored group differences in the symptom network. Results: First, for both trauma types, our analyses identified the edges that were repeatedly reported in previous network studies. Second, there was decisive evidence that the two networks were generated from different multivariate normal distributions, i.e. the networks differed on a global level. Third, explorative edge-wise comparisons showed moderate or strong evidence for specific 12 edges. Edges which emerged as especially important in distinguishing the networks were between intrusions and flashbacks, highlighting the stronger positive association in the group of type II trauma survivors compared to type I survivors. Flashbacks showed a similar pattern of results in the associations with detachment and sleep problems (type II > type I). Conclusion: Our findings suggest that trauma type contributes to the heterogeneity in the symptom network. Future research on PTSD symptom networks should include this variable in the analyses to reduce heterogeneity.


Original languageEnglish
Article number2114260
Pages (from-to)2114260
Issue number2
Publication statusPublished - 2022

External IDs

PubMedCentral PMC9518442
Scopus 85138531196
Mendeley 869139a0-5eb9-3de7-b594-56e10cd11419


Sustainable Development Goals


  • Attention, Bayes Theorem, Humans, Problem Behavior, Stress Disorders, Post-Traumatic/complications, Survivors, Bayesian graphical Gaussian models, PTSD, network comparison, trauma type, network analysis