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Examining the Factor Structure of the Connor–Davidson Resilience Scale (CD-RISC) in a Post-9/11 U.S. Military Veteran Sample
Open accessAbstract
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.
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“Resilience has been identified as an important factor that enables individuals adapt to and recover from emotionally, physically, and psychologically distressing situations and trauma [17,20].”
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Metadata
- Authors
- Green, K. T., Hayward, L. C., Williams, A. M., Dennis, P. A., Bryan, B. C., Taber, K. H., Mid-Atlantic Mental Illness Research, E. A. C. C. W., Davidson, J. R. T., Beckham, J. C., Calhoun, P. S., Ingle, S. J., Miller-Mumford, M., McDonald, S. D., Pickett, T. C., Yoash-Gantz, R. E., Brancu, M., Morey, R. A., Strauss, J. J., Tupler, L. A., & Dennis, M. F.
- Affiliations
- Duke University (US)
- Syracuse VA Medical Center (US)
- Atrium Health Wake Forest Baptist (US)
- United States Department of Veterans Affairs (US)
- Veterans Health Administration (US)
- Baylor College of Medicine (US)
- Duke Medical Center (US)
- Durham VA Medical Center (US)
- ORCID
- Venue
- Assessment
- Publisher
- SAGE Publications
- Published
- 2014-02-27
- Volume
- 21
- Issue
- 4
- Pages
- 443-451
- ISSN
- 1073-1911 (ISSN-L)
- 1552-3489
- PMC
- PMC4147024
- OpenAlex
- W1990014824
- Cited by
- 111
- References
- 58
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 11 · 2023: 7 · 2022: 11 · 2021: 10 · 2020: 9 · 2019: 18 · 2018: 12 · 2017: 9 · 2016: 14 · 2015: 3
- FWCI
- 10.65
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Assessment (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- DukeSpace (Duke University) (submittedVersion, cc-by-nc-nd)
- Funders
- U.S. Department of Veterans Affairs
- National Institute of Mental Health (R01MH062482)
- Topics
- Social Sciences › Psychology › Clinical Psychology › Resilience and Mental Health
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Psychology › Clinical Psychology › Posttraumatic Stress Disorder Research
- Keywords
- Connor-Davidson Resilience Scale, resilience, factor structure, military veterans, post-9/11 veterans, adaptability, self-efficacy, psychopathology, trauma exposure, psychiatric symptoms, structural validity
- MeSH terms
- Adaptation, Psychological, Adult, Depressive Disorder, Major, Major Depressive Disorder, Factor Analysis, Statistical, Female, Humans, Interview, Psychological, Male, Psychometrics, Surveys and Questionnaires, Stress Disorders, Post-Traumatic, United States, Veterans, Reproducibility of Results, Terrorism, Resilience, Psychological
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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