Abstract
Background: After the Great East Japan Earthquake [GEJE], approximately 70,000 Japan Ground Self Defense Force [JGSDF] personnel were deployed, risking Post-Traumatic Stress Disorder [PTSD]. The network approach to psychopathology suggests that symptoms may cause and exacerbate each other, resulting in the emergence and maintenance of disorders, including PTSD. It is therefore important to further explore the temporal interplay between symptoms. Most studies assessing the factor structure of the Impact of Event Scale-Revised [IES-R] have used cross-sectional designs. In this study, the structure of the IES-R was re-evaluated while incorporating the temporal interplay between symptoms.Methods: Using Dynamic Time Warping [DTW] the distances between PTSD symptoms on the IES-R were modelled in 1120 JGSDF personnel. Highly correlated symptoms were clustered at the group level using Distatis three-way principal component analyses of the distance matrices. The resulting clusters were compared to the original three subscales of the IES-R using a Confirmatory Factor Analysis (CFA).Results: The DTW analysis yielded four symptom clusters: Intrusion (five items), Hyperarousal (six items), Avoidance (six items), and Dissociation (five items). CFA yielded better fit estimates for this four-factor solution (RMSEA = 0.084, CFI = 0.918, TLI = 0.906), compared to the original three subscales of the IES-R (RMSEA = 0.103, CFI = 0.873, TLI = 0.858).Conclusions: DTW offers a new method of modelling the temporal relationships between symptoms. It yielded four IES-R symptom clusters, which may facilitate understanding of PTSD as a complex dynamic system.