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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.

Authors+Show Affiliations

Department of Community Mental Health, University of Haifa, Haifa, Israel.Department of Community Mental Health, University of Haifa, Haifa, Israel. NATAL, Israel Trauma and Resiliency Center, Tel Aviv, Israel.Department of Psychology, Leiden University, Leiden, the Netherlands. Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands.Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands. Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA.Department of Community Mental Health, University of Haifa, Haifa, Israel. NATAL, Israel Trauma and Resiliency Center, Tel Aviv, Israel.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

31433530

Citation

Greene, Talya, et al. "Dynamic Network Analysis of Negative Emotions and DSM-5 Posttraumatic Stress Disorder Symptom Clusters During Conflict." Journal of Traumatic Stress, 2019.
Greene T, Gelkopf M, Fried EI, et al. Dynamic Network Analysis of Negative Emotions and DSM-5 Posttraumatic Stress Disorder Symptom Clusters During Conflict. J Trauma Stress. 2019.
Greene, T., Gelkopf, M., Fried, E. I., Robinaugh, D. J., & Lapid Pickman, L. (2019). Dynamic Network Analysis of Negative Emotions and DSM-5 Posttraumatic Stress Disorder Symptom Clusters During Conflict. Journal of Traumatic Stress, doi:10.1002/jts.22433.
Greene T, et al. Dynamic Network Analysis of Negative Emotions and DSM-5 Posttraumatic Stress Disorder Symptom Clusters During Conflict. J Trauma Stress. 2019 Aug 21; PubMed PMID: 31433530.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Dynamic Network Analysis of Negative Emotions and DSM-5 Posttraumatic Stress Disorder Symptom Clusters During Conflict. AU - Greene,Talya, AU - Gelkopf,Marc, AU - Fried,Eiko I, AU - Robinaugh,Donald J, AU - Lapid Pickman,Liron, Y1 - 2019/08/21/ PY - 2018/06/28/received PY - 2018/12/10/revised PY - 2018/12/15/accepted PY - 2019/8/22/entrez JF - Journal of traumatic stress JO - J Trauma Stress N2 - 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. SN - 1573-6598 UR - https://www.unboundmedicine.com/medline/citation/31433530/Dynamic_Network_Analysis_of_Negative_Emotions_and_DSM-5_Posttraumatic_Stress_Disorder_Symptom_Clusters_During_Conflict L2 - https://doi.org/10.1002/jts.22433 DB - PRIME DP - Unbound Medicine ER -