Factor mixture modeling reveals three distinct symptom subgroups in trauma-exposed medical patients, highlighting clinical heterogeneity in posttraumatic stress disorder.
The present study used factor mixture modeling to explore empirically defined subgroups of psychological trauma victims based on confirmatory factor analysis (CFA) and latent class analysis of posttraumatic stress disorder (PTSD) symptoms. We sampled 310 medical patients with a history of trauma exposure. Confirmatory factor analysis revealed that the 4-factor emotional numbing PTSD model yielded the best model fit. Using latent factor means derived from this model and the 4-factor dysphoria PTSD model (indexing severity on PTSD factors), 3 latent classes of participants were identified using factor mixture modeling. The 3-class model fit the data very well and was validated against external measures of anxiety and rumination.
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Elhai et al. (2011) studied this question.
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