Using Exploratory Structural Equation Modeling (ESEM) to Examine the Internal Structure of Posttraumatic Stress Disorder Symptoms

Several studies have reported the factor structure of posttraumatic stress disorder (PTSD) using confirmatory factor analysis (CFA). The results show models with different number of factors, high correlations between factors, and symptoms that belong to different factors in different models without affecting the fit index. These elements could suppose the existence of considerable item cross-loading, the overlap of different factors or even the presence of a general factor that explains the items common source of variance. The aim is to provide new evidence regarding the factor structure of PTSD using CFA and exploratory structural equation modeling (ESEM). In a sample of 1,372 undergraduate students, we tested six different models using CFA and two models using ESEM and ESEM bifactor analysis. Trauma event and past-month PTSD symptoms were assessed with Life Events Checklist for DSM-5 (LEC–5) and PTSD Checklist for DSM-5 (PCL–5). All six tested CFA models showed good fit indexes (RMSEA = .051–.056, CFI = .969–.977, TLI = .965–.970), with high correlations between factors (M = .77, SD = .09 to M = .80, SD = .09). The ESEM models showed good fit indexes (RMSEA = .027–.036, CFI = .991–.996, TLI = .985–.992). These models confirmed the presence of cross-loadings on several items as well as loads on a general factor that explained 76.3% of the common variance. The results showed that most of the items do not meet the assumption of dimensional exclusivity, showing the need to expand the analysis strategies to study the symptomatic organization of PTSD.