Examining the factor structure of the Connor-Davidson Resilience Scale (CD-RISC) in a post-9/11 U.S. military veteran sample.
Abstract
The present study examined the structural validity of the 25-item Connor-Davidson
Resilience Scale (CD-RISC) in a large sample of U.S. veterans with military service
since September 11, 2001. Participants (N = 1,981) completed the 25-item CD-RISC,
a structured clinical interview and a self-report questionnaire assessing psychiatric
symptoms. The study sample was randomly divided into two subsamples: an initial sample
(Sample 1: n = 990) and a replication sample (Sample 2: n = 991). Findings derived
from exploratory factor analysis (EFA) did not support the five-factor analytic structure
as initially suggested in Connor and Davidson's instrument validation study. Although
parallel analyses indicated a two-factor structural model, we tested one to six factor
solutions for best model fit using confirmatory factor analysis. Results supported
a two-factor model of resilience, composed of adaptability- (8 items) and self-efficacy-themed
(6 items) items; however, only the adaptability-themed factor was found to be consistent
with our view of resilience-a factor of protection against the development of psychopathology
following trauma exposure. The adaptability-themed factor may be a useful measure
of resilience for post-9/11 U.S. military veterans.
Type
Journal articleSubject
Connor–Davidson Resilience Scaleexploratory factor analysis
military
psychometric testing
Adaptation, Psychological
Adult
Depressive Disorder, Major
Factor Analysis, Statistical
Female
Humans
Interview, Psychological
Male
Psychometrics
Reproducibility of Results
Resilience, Psychological
Stress Disorders, Post-Traumatic
Surveys and Questionnaires
Terrorism
United States
Veterans
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https://hdl.handle.net/10161/13044Published Version (Please cite this version)
10.1177/1073191114524014Publication Info
Green, Kimberly T; Hayward, Laura C; Williams, Ann M; Dennis, Paul A; Bryan, Brandon
C; Taber, Katherine H; ... Calhoun, Patrick S (2014). Examining the factor structure of the Connor-Davidson Resilience Scale (CD-RISC) in
a post-9/11 U.S. military veteran sample. Assessment, 21(4). pp. 443-451. 10.1177/1073191114524014. Retrieved from https://hdl.handle.net/10161/13044.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Jean Crowell Beckham
Professor in Psychiatry and Behavioral Sciences
Interest in assessment and treatment of trauma, particularly as occurs for both women
and men during military service; focus in treatment outcome of differential and collective
contribution for psychopharmacological and behavioral interventions in PTSD populations;
long term physical health effects of chronic posttraumatic stress disorder.
Patrick Shields Calhoun
Professor in Psychiatry and Behavioral Sciences
I specialize in the assessment and treatment of the psychological and behavioral sequelae
of posttraumatic stress disorder (PTSD) including the use of cognitive-behavioral
interventions to reduce PTSD symptoms, aggression, and substance misuse.
Research interests
The psychological, behavioral, and health consequences of traumatic stress
Health services research related to PTSD and associated behavioral difficulties
Identification of innova
Jonathan R.T. Davidson
Professor Emeritus of Psychiatry and Behavioral Sciences
Currently, my research focuses upon the theoretical aspects of homeopathy and its
clinical utilization, as well as the broader field of alternative (complementary)
medicine. this is a field which has traditionally been overlooked as a legitimate
scientific discipline. Other areas of activity are as in the past, i.e., clinical
treatment, epidemiology, risk factors, pathogenesis of posttraumatic stress, social
phobia, other anxiety status, and depression. These are illustrated by recent pu
Paul Anthony Dennis
Associate Professor in Population Health Sciences
Developmental psychologist, statistician, and data scientist. Research focused on
cardiovascular risk associated with psychiatric illness and trauma exposure, intraindivdiual
variability in symptoms and affect, and the use of mobile apps and devices for health
and behavior monitoring and interventions. Interest in longitudinal and repeated-measures
analyses, mediation analyses, machine learning, and applications to administrative
healthcare data.
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