Abstract
Evidence is accumulating for the conceptual validity of the ICD-11 proposal for PTSD and CPTSD, but our knowledge of the specificity of trauma-related predictors remain under development. Specifically, studies utilising advanced statistical methods to model the relationship between trauma-exposure and ICD-11 proposals of traumatic stress, as well as differences in profiles of trauma-exposure in the Israeli population are lacking. Additionally, time since trauma and possessing a clear memory of the trauma are yet to be examined as predictors of PTSD and CPTSD. This was consequently the aims of the current study. Trauma-exposure as reported by a general population sample of the Israeli adult population (n=834) was analysed using latent class analysis, and the resultant classes were used in regression models to predict PTSD and CPTSD operationalised both dimensionally and categorically. Four distinct groups were identified: (1) Child and adult interpersonal victimization, (2) Community victimization male, (3) Community victimization female, and (4) Adult victimization. These groups were differentially related to PTSD and CPTSD with only child and adult interpersonal victimization consistently predicting CPTSD and DSO. PTSD was associated with the child and adult interpersonal victimization-group and adult victimization group when modelled dimensionally, whereas only the child and adult interpersonal victimization-group was predictive of PTSD when operationalised categorically. The role of time since trauma and possessing a clear memory for the trauma differed across PTSD and CPTSD. These findings support the use of trauma-typologies for predicting PTSD and CPTSD and provide important insight into the distribution of trauma-exposure in the Israeli population.
Original language | English |
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Journal | Journal of Traumatic Stress |
Publication status | Accepted/In press - 20 May 2019 |
Keywords
- Posttraumatic stress disorder
- , complex posttraumatic stress disorder
- ICD-11
- International Trauma Questionnaire
- mixture modelling