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Differential Associations Among PTSD and Complex PTSD Symptoms and Traumatic Experiences and Postmigration Difficulties in a Culturally Diverse Refugee Sample.

Tobias HeckerStephanie HuberThomas MaierAndreas Maercker
Published in: Journal of traumatic stress (2018)
Forced migration is one of the major challenges currently facing the international community. Many refugees have been affected by traumatic experiences at home and during their flight, putting them at a heightened risk of developing trauma-related disorders. The new version of the International Classification of Diseases (ICD-11) introduced two sibling disorders, posttraumatic stress disorder (PTSD) and complex PTSD (CPTSD). So far, little is known about risk and protective factors in refugees that are specifically associated with the disturbances in self-organization (DSO) characteristic of CPTSD. In this study, we aimed to investigate the association between PTSD and DSO symptoms and traumatic experiences, postmigration difficulties, and social support in a culturally diverse sample of refugees who resettled in Switzerland. A total of 94 refugees (85.1% male; M age = 31.60 years, SD = 10.14, range: 18-61 years) participated in this study. Trained assessors performed either guided questionnaire assessments or structured interviews. In our advice- and help-seeking sample, 32.9% of individuals suffered from PTSD and 21.3% from CPTSD. After controlling for potential gender differences, we found positive associations between PTSD symptoms and trauma exposure, β = .22, as well as between DSO symptoms and postmigration living difficulties, β = .42, and lack of social support, β = .22. Our findings support the notion that it is highly important to consider differential associations among PTSD and DSO symptoms and risk and protective factors to gain a deeper understanding of the trauma-related problems refugees face.
Keyphrases
  • social support
  • posttraumatic stress disorder
  • depressive symptoms
  • mental health
  • spinal cord injury
  • sleep quality
  • healthcare
  • machine learning
  • deep learning
  • climate change
  • risk assessment
  • human health