Network analysis of comorbid posttraumatic stress disorder and depression in adolescents across COVID-19 epidemic and Typhoon Lekima

2021 ◽  
Vol 295 ◽  
pp. 594-603
Author(s):  
Junjun Qi ◽  
Rui Sun ◽  
Xiao Zhou
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Network Analysis ◽  
Posttraumatic Stress ◽  
Stress Disorder

Examining unique and prospective relationships among self-injurious thoughts and behaviors and posttraumatic stress disorder: a network analysis in two trauma-exposed samples

2020 ◽  
pp. 1-11
Author(s):  
Elizabeth G. Spitzer ◽  
Natasha Benfer ◽  
Kelly L. Zuromski ◽  
Brian P. Marx ◽  
Tracy K. Witte
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Network Analysis ◽  
Posttraumatic Stress ◽  
Stress Disorder ◽  
Risky Behaviors ◽  
Ptsd Symptoms ◽  
Cross Sectional ◽  
Negative Beliefs ◽  
Two Samples ◽  
And Behaviors

Abstract Background As self-injurious thoughts and behaviors (SITB) remain a pressing public health concern, research continues to focus on risk factors, such as posttraumatic stress disorder (PTSD). Network analysis provides a novel approach to examining the PTSD-SITB relationship. This study utilized the network approach to elucidate how individual PTSD symptoms may drive and maintain SITB. Methods We estimated cross-sectional networks in two samples of trauma-exposed adults (Sample 1: N = 349 adults; Sample 2: N = 1307 Veterans) to identify PTSD symptoms that may act as bridges to SITB. Additionally, we conducted a cross-lagged panel network in Sample 2 to further clarify the temporal relationship between PTSD symptoms and SITB during a 2-year follow-up. Finally, in both samples, we conducted logistic regressions to examine the utility of PTSD symptoms in prospectively predicting SITB, over a 15-day period (Sample 1) and over a 2-year period (Sample 2), allowing us to examine both short- and long-term prediction. Results Two PTSD symptoms (i.e. negative beliefs and risky behaviors) emerged as highly influential on SITB in both cross-sectional networks. In the cross-lagged panel network, distorted blame emerged as highly influential on SITB over time. Finally, risky behaviors, unwanted memories, and psychological distress served as the strongest predictors of SITB across the two samples. Conclusions Overall, our results suggest that treatments targeting negative beliefs and risky behaviors may prevent SITB in community and Veteran populations, whereas treatments targeting distorted blame and unwanted memories may help reduce SITB for individuals with a history of combat trauma.

scholarly journals The symptom representation of posttraumatic stress disorder in a sample of unaccompanied and accompanied refugee minors in Germany: a network analysis

2019 ◽  
Vol 10 (1) ◽  
pp. 1675990 ◽  
Author(s):  
Elisa Pfeiffer ◽  
Thorsten Sukale ◽  
Lauritz Rudolf Floribert Müller ◽  
Paul Lukas Plener ◽  
Rita Rosner ◽  
...  
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Network Analysis ◽  
Posttraumatic Stress ◽  
Stress Disorder ◽  
Refugee Minors

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

2019 ◽  
Vol 33 (1) ◽  
pp. 72-83 ◽  
Author(s):  
Talya Greene ◽  
Marc Gelkopf ◽  
Eiko I. Fried ◽  
Donald J. Robinaugh ◽  
Liron Lapid Pickman
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Network Analysis ◽  
Posttraumatic Stress ◽  
Stress Disorder ◽  
Negative Emotions ◽  
Dynamic Network ◽  
Symptom Clusters ◽  
Dynamic Network Analysis ◽  
Dsm 5 ◽  
Disorder Symptom
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