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Dynamic networks of PTSD symptoms during conflict
16 references·6 citing·42 second hop
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References

  • 1969Investigating Causal Relations by Econometric Models and Cross-spectral Methods22,971 cited
  • 2015The Posttraumatic Stress Disorder Checklist for DSM‐5 (PCL‐5): Development and Initial Psychometric Evaluation5,222 cited
  • 2002Diary Methods: Capturing Life as it is Lived3,834 cited
  • 2017A network theory of mental disorders3,456 cited
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  • 2016Can network analysis transform psychopathology?1,070 cited
  • 2016Mental disorders as networks of problems: a review of recent insights1,047 cited
  • 2017Moving Forward: Challenges and Directions for Psychopathological Network Theory and Methodology948 cited
  • 2016Network analysis of depression and anxiety symptom relationships in a psychiatric sample927 cited
  • 2009Experience sampling research in psychopathology: opening the black box of daily life817 cited
  • 2012Ambulatory Assessment754 cited
  • 2015What are 'good' depression symptoms? Comparing the centrality of DSM and non-DSM symptoms of depression in a network analysis751 cited
  • 2014Mental Disorders as Causal Systems591 cited
  • 2009

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Ecological momentary assessment of mood disorders and mood dysregulation.
529 cited
  • 2017No Time Like the Present504 cited
  • Cited by

    • 2021Consolidation/reconsolidation therapies for the prevention and treatment of PTSD and re-experiencing: a systematic review and meta-analysis96 cited
    • 2019A decennial review of psychotraumatology: what did we learn and where are we going?78 cited
    • 2021Posttraumatic stress or posttraumatic growth? Using network analysis to explore the relationships between coping styles and trauma outcomes70 cited
    • 2022Auditing the research practices and statistical analyses of the group-level temporal network approach to psychological constructs: A systematic scoping review59 cited
    • 2021Assessing Change in Intervention Research: The Benefits of Composite Outcomes40 cited
    • 2024The Central Role of Daily Hopeful Feelings in Predicting Well‐Being: A Network Perspective2 cited