Dynamic Network Analysis of Negative Emotions and DSM‐5 Posttraumatic Stress Disorder Symptom Clusters During Conflict

Abstract Investigating dynamic associations between specific negative emotions and PTSD symptom clusters may provide novel insights into the ways in which PTSD symptoms interact with, emerge from, or are reinforced by negative emotions. The present study estimated the associations among negative emotions and the four DSM‐5 PTSD symptom clusters (intrusions, avoidance, negative alterations in cognitions and mood [NACM], and arousal) in a sample of Israeli civilians ( n = 96) during the Israel–Gaza War of July–August 2014. Data were collected using experience sampling methodology, with participants queried via smartphone about PTSD symptoms and negative emotions twice a day for 30 days. We used a multilevel vector auto‐regression model to estimate temporal and contemporaneous temporal networks. Contrary to our hypothesis, in the temporal network, PTSD symptom clusters were more predictive of negative emotions than vice versa, with arousal emerging as the strongest predictor that negative emotions would be reported at the next measurement point; fear and sadness were also strong predictors of PTSD symptom clusters. In the contemporaneous network, negative emotions exhibited the strongest associations with the NACM and arousal PTSD symptom clusters. The negative emotions of sadness, stress, fear, and loneliness had the strongest associations to the PTSD symptom clusters. Our findings suggest that arousal has strong associations to both PTSD symptoms and negative emotions during ongoing trauma and highlights the potentially relevant role of arousal for future investigations in primary or early interventions.