The Primary Care Posttraumatic Stress Disorder (PC-PTSD) screen (Prins et al., 2003) is used by the Department of Defense to identify military members who are at increased risk of PTSD. This screen has been offered to all returning deployers since 2005. However, validation studies of PC-PTSD scores from military samples have seldom employed a significant number of female subjects and no published studies have examined it for gender bias. Ruling out bias is important because routine under-identification of PTSD risk in any group could result in hindered access to needed assessment and/or care. With the current proportion of military females historically high (Women’s Research & Education Institute, 2007), it is imperative that the PC-PTSD be analyzed to ensure measurement equivalence across gender. Using a large sample of male and female veterans returning from deployment, the validity of the PC-PTSD scores was first examined by conducting a differential item functioning (DIF) analysis across male and female subgroups. Then, using a clinical diagnosis as the criterion, both logistic regression and diagnostic likelihood ratio methods were employed to assess for differential predictive validity by gender. Finally, confirmatory factor analysis (CFA) was used to examine convergent and divergent validity in a two-factor model containing both PC-PTSD and depression screen responses. Results revealed no statistically significant gender-related DIF or differential prediction of PTSD by PC-PTSD scores. Good convergent and divergent validity were also observed in the CFA analysis. The results generally supported the continued use of the PC-PTSD with both male and female military veterans returning from deployment. Limitations of the study and recommendations for future research were discussed.
Identifer | oai:union.ndltd.org:UTENN/oai:trace.tennessee.edu:utk_graddiss-1892 |
Date | 01 August 2010 |
Creators | Oliver, Mark Allan |
Publisher | Trace: Tennessee Research and Creative Exchange |
Source Sets | University of Tennessee Libraries |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Doctoral Dissertations |
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