Abstract

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.

Details

Title
Symptoms of posttraumatic stress disorder in a clinical sample of refugees: a network analysis
Author
Spiller, Tobias R 1   VIAFID ORCID Logo  ; Schick, Matthis 1   VIAFID ORCID Logo  ; Schnyder, Ulrich 1 ; Bryant, Richard A 2 ; Nickerson, Angela 2 ; Morina, Naser 1 

 Department of Psychiatry and Psychotherapy, University Hospital, University of Zurich, Zurich, Switzerland 
 School of Psychology, UNSW Australia, Sydney, Australia 
Publication year
2017
Publication date
2017
Publisher
Taylor & Francis Ltd.
e-ISSN
20008066
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2215232346
Copyright
© 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This work is licensed under the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.