The role of trauma, social support, and demography on veteran resilience. Issue 1 (31st December 2022)

• Record Type: Journal Article
• Authors: Rakesh, Gopalkumar; Clausen, Ashley N.; Buckley, Mary Nicole; Clarke-Rubright, Emily; Fairbank, John A.; Wagner, Henry Ryan; Morey, Rajendra A.
• Is Part Of: European journal of psychotraumatology. Volume 13:Issue 1(2022)
• Publication Date: 2022-12-31
• Subjects: Post-traumatic stress disorder -- resilience -- regression analyses -- structural equation models; Trastorno de estrés postraumático -- resiliencia -- análisis de regresión y modelos de ecuaciones estructurales; 创伤后应激障碍 -- 心理韧性 -- 回归分析 -- 结构方程模型; Post-traumatic stress disorder -- Periodicals; Stress Disorders, Post-Traumatic; Post-traumatic stress disorder; Electronic journals; Periodicals; Periodicals; Fulltext; Internet Resources; Periodicals; 616.8521
• DOI: 10.1080/20008198.2022.2058267
• Languages: English
• ISSNs: 2000-8198

Abstract

ABSTRACT: Background: Historically, resilience has often been conceptualized as the sustained lack of symptoms following trauma exposure. In line with a novel conceptualization of resilience as being dynamic over lifespan, determined by interacting biological and environmental factors, we examined the VA Mid-Atlantic Post Deployment Mental Health Repository (PDMH) comprised of 3876 US Military Veterans with and without PTSD diagnoses. Methods: We performed regression modelling to study the relationship between resilience (measured with Connor Davidson Resilience Scale; CD-RISC), posttraumatic stress disorder (PTSD) severity (Davidson Trauma Scale; DTS), social support (Medical Outcome Study Social Support Survey; MOSSS), combat exposure (Combat Exposure Scale; CES), childhood trauma (Trauma Life Events Questionnaire; TLEQ), and demographic factors. CD-RISC was positively correlated with years of education and negatively correlated with DTS, CES and TLEQ scores. Results: We found an interaction between CD-RISC and CES in predicting PTSD severity (Davidson Trauma Scale). Specifically, high resilience predicted lower PTSD symptom severity than low resilience, this relationship was amplified with increasing levels of combat exposure. Structural equation modelling (SEM) identified an optimal latent variable that represents resilience and relationships between latent variables for resilience, trauma, and illness. We derived a resilience latent variable composed of age, education level, MOSSS and race. Conclusions: Our results support a conceptualization of resilience as a multifactorial determinant that coexists with PTSD, a state rather than trait variable, and can be quantified by biological and behavioural metrics. HIGHLIGHTS: Historically, resilience has often been conceptualized as the sustained lack of symptoms following trauma exposure. We examined the VA Mid-Atlantic Post Deployment Mental Health Repository (PDMH) comprised of 3876 US Military Veterans. We found an interaction effect between CD-RISC and CES in predicting PTSD severity (Davidson Trauma Scale)