A Bayesian network analysis of posttraumatic stress disorder symptoms in adults reporting childhood sexual abuse
Background: The network approach to mental disorders offers a novel framework for conceptualizing posttraumatic stress disorder (PTSD) as a causal system of interacting symptoms. Objective: In this study, we extended this work by estimating the structure of relations among PTSD symptoms in adults re...
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Online Access: | http://dx.doi.org/10.1080/20008198.2017.1341276 |
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doaj-b2b3936cfbd142f8a251f4f832b382a02020-11-25T01:25:29ZengTaylor & Francis GroupEuropean Journal of Psychotraumatology2000-81982000-80662017-11-018010.1080/20008198.2017.13412761341276A Bayesian network analysis of posttraumatic stress disorder symptoms in adults reporting childhood sexual abuseRichard J. McNally0Alexandre Heeren1Donald J. Robinaugh2Harvard UniversityHarvard UniversityMassachusetts General Hospital and Harvard Medical SchoolBackground: The network approach to mental disorders offers a novel framework for conceptualizing posttraumatic stress disorder (PTSD) as a causal system of interacting symptoms. Objective: In this study, we extended this work by estimating the structure of relations among PTSD symptoms in adults reporting personal histories of childhood sexual abuse (CSA; N = 179). Method: We employed two complementary methods. First, using the graphical LASSO, we computed a sparse, regularized partial correlation network revealing associations (edges) between pairs of PTSD symptoms (nodes). Next, using a Bayesian approach, we computed a directed acyclic graph (DAG) to estimate a directed, potentially causal model of the relations among symptoms. Results: For the first network, we found that physiological reactivity to reminders of trauma, dreams about the trauma, and lost of interest in previously enjoyed activities were highly central nodes. However, stability analyses suggest that these findings were unstable across subsets of our sample. The DAG suggests that becoming physiologically reactive and upset in response to reminders of the trauma may be key drivers of other symptoms in adult survivors of CSA. Conclusions: Our study illustrates the strengths and limitations of these network analytic approaches to PTSD.http://dx.doi.org/10.1080/20008198.2017.1341276Network analysisdirected acyclic graphPTSDchildhood sexual abuse |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Richard J. McNally Alexandre Heeren Donald J. Robinaugh |
spellingShingle |
Richard J. McNally Alexandre Heeren Donald J. Robinaugh A Bayesian network analysis of posttraumatic stress disorder symptoms in adults reporting childhood sexual abuse European Journal of Psychotraumatology Network analysis directed acyclic graph PTSD childhood sexual abuse |
author_facet |
Richard J. McNally Alexandre Heeren Donald J. Robinaugh |
author_sort |
Richard J. McNally |
title |
A Bayesian network analysis of posttraumatic stress disorder symptoms in adults reporting childhood sexual abuse |
title_short |
A Bayesian network analysis of posttraumatic stress disorder symptoms in adults reporting childhood sexual abuse |
title_full |
A Bayesian network analysis of posttraumatic stress disorder symptoms in adults reporting childhood sexual abuse |
title_fullStr |
A Bayesian network analysis of posttraumatic stress disorder symptoms in adults reporting childhood sexual abuse |
title_full_unstemmed |
A Bayesian network analysis of posttraumatic stress disorder symptoms in adults reporting childhood sexual abuse |
title_sort |
bayesian network analysis of posttraumatic stress disorder symptoms in adults reporting childhood sexual abuse |
publisher |
Taylor & Francis Group |
series |
European Journal of Psychotraumatology |
issn |
2000-8198 2000-8066 |
publishDate |
2017-11-01 |
description |
Background: The network approach to mental disorders offers a novel framework for conceptualizing posttraumatic stress disorder (PTSD) as a causal system of interacting symptoms. Objective: In this study, we extended this work by estimating the structure of relations among PTSD symptoms in adults reporting personal histories of childhood sexual abuse (CSA; N = 179). Method: We employed two complementary methods. First, using the graphical LASSO, we computed a sparse, regularized partial correlation network revealing associations (edges) between pairs of PTSD symptoms (nodes). Next, using a Bayesian approach, we computed a directed acyclic graph (DAG) to estimate a directed, potentially causal model of the relations among symptoms. Results: For the first network, we found that physiological reactivity to reminders of trauma, dreams about the trauma, and lost of interest in previously enjoyed activities were highly central nodes. However, stability analyses suggest that these findings were unstable across subsets of our sample. The DAG suggests that becoming physiologically reactive and upset in response to reminders of the trauma may be key drivers of other symptoms in adult survivors of CSA. Conclusions: Our study illustrates the strengths and limitations of these network analytic approaches to PTSD. |
topic |
Network analysis directed acyclic graph PTSD childhood sexual abuse |
url |
http://dx.doi.org/10.1080/20008198.2017.1341276 |
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