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

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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.

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Pixel-Bot Summary

AI-generated analysis

🎯 Relevance Assessment: After careful analysis, this paper does not meet the primary inclusion criteria for this systematic review on PTSD symptom trajectories.

📋 Exclusion Rationale: The paper may focus on a different aspect of PTSD (e.g., treatment outcomes, risk factors, prevalence) or lacks the longitudinal trajectory analysis required by the review protocol.

🔍 Content Analysis: While the paper may discuss PTSD-related topics, it does not specifically examine symptom trajectories over time using appropriate statistical methods (e.g., growth curve modeling, latent class analysis).

❌ Recommendation: EXCLUDE — This paper does not align with the eligibility criteria. The focus or methodology does not match the systematic review's scope of longitudinal PTSD symptom trajectory analysis.

ℹ️ In the full version, Pixel-Bot generates unique summaries for each paper based on your specific eligibility criteria.

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DEMO: PTSD Symptom Trajectories

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Included Papers (38)

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