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      Making connections: exploring the centrality of posttraumatic stress symptoms and covariates after a terrorist attack

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          ABSTRACT

          Background: Posttraumatic stress symptoms are interconnected. Knowledge about which symptoms of posttraumatic stress are more strongly interconnected or central than others may have implications for the targeting of clinical interventions. Exploring whether symptoms of posttraumatic stress may be differentially related to covariates can contribute to our knowledge on how posttraumatic stress symptoms arise and are maintained.

          Objective: This study aimed to identify the most central symptoms of posttraumatic stress and their interconnections, and to explore how covariates such as exposure, sex, neuroticism, and social support are related to the network of symptoms of posttraumatic stress.

          Method: This study used survey data from ministerial employees collected approximately 10 months after the 2011 Oslo bombing that targeted the governmental quarters ( n = 190). We conducted network analyses using Gaussian graphical models and the lasso regularization.

          Results: The network analysis revealed reliably strong connections between intrusive thoughts and nightmares, feeling easily startled and overly alert, and between feeling detached and emotionally numb. The most central symptom in the symptom network was feeling emotionally numb. The covariates were generally not found to have high centrality in the symptom network. An exception was that being female was connected to a high physiological reactivity to reminders of the trauma.

          Conclusions: Ten months after a workplace terror attack emotional numbness appears to be of high centrality in the symptom network of posttraumatic stress. Fear circuitry and dysphoric symptoms may constitute two functional entities in chronic posttraumatic stress. Clinical interventions targeting numbness may be beneficial in the treatment of posttraumatic stress, at least after workplace terrorism.

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          Most cited references32

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          Sparse inverse covariance estimation with the graphical lasso.

          We consider the problem of estimating sparse graphs by a lasso penalty applied to the inverse covariance matrix. Using a coordinate descent procedure for the lasso, we develop a simple algorithm--the graphical lasso--that is remarkably fast: It solves a 1000-node problem ( approximately 500,000 parameters) in at most a minute and is 30-4000 times faster than competing methods. It also provides a conceptual link between the exact problem and the approximation suggested by Meinshausen and Bühlmann (2006). We illustrate the method on some cell-signaling data from proteomics.
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            Community detection in graphs

            The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of the same cluster and comparatively few edges joining vertices of different clusters. Such clusters, or communities, can be considered as fairly independent compartments of a graph, playing a similar role like, e. g., the tissues or the organs in the human body. Detecting communities is of great importance in sociology, biology and computer science, disciplines where systems are often represented as graphs. This problem is very hard and not yet satisfactorily solved, despite the huge effort of a large interdisciplinary community of scientists working on it over the past few years. We will attempt a thorough exposition of the topic, from the definition of the main elements of the problem, to the presentation of most methods developed, with a special focus on techniques designed by statistical physicists, from the discussion of crucial issues like the significance of clustering and how methods should be tested and compared against each other, to the description of applications to real networks.
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              Predictors of posttraumatic stress disorder and symptoms in adults: a meta-analysis.

              A review of 2,647 studies of posttraumatic stress disorder (PTSD) yielded 476 potential candidates for a meta-analysis of predictors of PTSD or of its symptoms. From these, 68 studies met criteria for inclusion in a meta-analysis of 7 predictors: (a) prior trauma, (b) prior psychological adjustment, (c) family history of psychopathology, (d) perceived life threat during the trauma, (e) posttrauma social support, (f) peritraumatic emotional responses, and (g) peritraumatic dissociation. All yielded significant effect sizes, with family history, prior trauma, and prior adjustment the smallest (weighted r = .17) and peritraumatic dissociation the largest (weighted r = .35). The results suggest that peritraumatic psychological processes, not prior characteristics, are the strongest predictors of PTSD.
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                Author and article information

                Journal
                Eur J Psychotraumatol
                Eur J Psychotraumatol
                ZEPT
                zept20
                European Journal of Psychotraumatology
                Taylor & Francis
                2000-8066
                2017
                02 June 2017
                : 8
                : sup3 , PTSD Symptomics
                : 1333387
                Affiliations
                [ a ] Norwegian Centre for Violence and Traumatic Stress Studies , Oslo, Norway
                [ b ] Institute of Clinical Medicine, Faculty of Medicine, University of Oslo , Oslo, Norway
                Author notes
                CONTACT Marianne Skogbrott Birkeland marianne.s.birkeland@ 123456gmail.com Norwegian Centre for Violence and Traumatic Stress Studies , 181 Nydalen, Oslo 0409, Norway
                Article
                1333387
                10.1080/20008198.2017.1333387
                5632769
                29038689
                0dfa1149-dca6-473e-8670-7bab5ca7ef83
                © 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 21 December 2016
                : 11 May 2017
                Page count
                Figures: 4, Tables: 2, References: 45, Pages: 11
                Funding
                Funded by: The Norwegian Council of Mental Health and the Norwegian Extra Foundation for Health and Rehabilitation through EXTRAfounds
                Award ID: 2.13/2/0021
                This work was supported by the Norwegian Council of Mental Health and the Norwegian Extra Foundation for Health and Rehabilitation through EXTRAfounds [2.13/2/0021].
                Categories
                Article
                Research Article

                Clinical Psychology & Psychiatry
                ptsd,network analysis,psychopathology,terrorism,aetiology
                Clinical Psychology & Psychiatry
                ptsd, network analysis, psychopathology, terrorism, aetiology

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