Powered by OpenAIRE graph
Found an issue? Give us feedback
addClaim

Psychopathology and resilience following traumatic injury: A latent growth mixture model analysis.

Authors: Terri A, deRoon-Cassini; Anthony D, Mancini; Mark D, Rusch; George A, Bonanno;

Psychopathology and resilience following traumatic injury: A latent growth mixture model analysis.

Abstract

To investigate trajectories of PTSD and depression following traumatic injury using latent class growth curve modeling.A longitudinal study of 330 injured trauma survivors was conducted and participants were assessed during hospitalization, and at 1, 3, and 6 months follow-up. Acute Stress Disorder (ASD) was assessed during hospitalization using the Acute Stress Disorder Interview (ASD-I), PTSD was measured at all follow-up with the Post-Traumatic Stress Diagnostic Scale (PDS) and depression was measured at hospitalization with the (BSI) and at follow-up with the Center for Epidemiologic Studies Depression Scale (CESDS). Covariates were explored, including coping self-efficacy, anger, education level, and mechanism of injury.Four latent classes were identified for PTSD and Depression symptoms: chronic distress, delayed distress, recovered, and resilience. When compared to the resilient group, individuals with chronic distress were more likely to have been assaulted, had higher levels of anger, and had less coping self-efficacy. The delayed distress group had lower education levels, higher levels of coping self-efficacy, and higher levels of anger. Individuals in the recovered group had fewer years of education, and higher levels of anger.The majority of the injured trauma sample demonstrated resiliency, with those exhibiting distress doing so as a delayed, chronic, or recovered trajectory. Coping self efficacy, education, assaultive trauma type, and anger were important covariates of depression and PTSD trajectories. These results are similar to studies of individuals who experienced a major health threat and with survivors from the World Trade Center attacks in the U.S.

Related Organizations
Keywords

Adult, Aged, 80 and over, Male, Adolescent, Major Depressive Disorder, Health Status, Middle Aged, Severity of Illness Index, Self Efficacy, Life Change Events, Stress Disorders, Post-Traumatic, Young Adult, Surveys and Questionnaires, Adaptation, Psychological, Humans, Psychology, Female, September 11 Terrorist Attacks, Aged, Follow-Up Studies

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    335
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
335
Top 1%
Top 1%
Top 1%
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!