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    Does highly symptomatic class membership in the acute phase predict highly symptomatic classification in victims 6 months after traumatic exposure?


    Hansen, Maj and Hyland, Philip and Armour, Cherie (2016) Does highly symptomatic class membership in the acute phase predict highly symptomatic classification in victims 6 months after traumatic exposure? Journal of Anxiety Disorders, 40. pp. 44-51. ISSN 0887-6185

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    Abstract

    Recently studies have indicated the existence of both posttraumatic stress disorder (PTSD) and acute stress disorder (ASD) subtypes but no studies have investigated their mutual association. Although ASD may not be a precursor of PTSD per se, there are potential benefits associated with early identification of victims at risk of developing PTSD subtypes. The present study investigates ASD and PTSD subtypes using latent class analysis (LCA) following bank robbery (N = 371). Moreover, we assessed if highly symptomatic ASD and selected risk factors increased the probability of highly symptomatic PTSD. The results of LCA revealed a three class solution for ASD and a two class solution for PTSD. Negative cognitions about self (OR = 1.08), neuroticism (OR = 1.09) and membership of the ‘High symptomatic ASD’ class (OR = 20.41) significantly increased the probability of ‘symptomatic PTSD’ class membership. Future studies are needed to investigate the existence of ASD and PTSD subtypes and their mutual relationship.

    Item Type: Article
    Keywords: ASD subtypes; PTSD subtypes; Latent class analysis; Risk factors;
    Academic Unit: Assisting Living & Learning,ALL institute
    Faculty of Science and Engineering > Psychology
    Item ID: 19202
    Identification Number: https://doi.org/10.1016/j.janxdis.2016.04.008
    Depositing User: Philip Hyland
    Date Deposited: 19 Nov 2024 16:36
    Journal or Publication Title: Journal of Anxiety Disorders
    Publisher: Elsevier
    Refereed: Yes
    URI:
      Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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