Predictors of remission from body dysmorphic disorder after internet-delivered cognitive behavior therapy: a machine learning approach.

Journal: BMC psychiatry
PMID: 32429939

Abstract

BACKGROUND: Previous attempts to identify predictors of treatment outcomes in body dysmorphic disorder (BDD) have yielded inconsistent findings. One way to increase precision and clinical utility could be to use machine learning methods, which can incorporate multiple non-linear associations in prediction models.

Authors

  • Oskar Flygare
    Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska University Hospital, Karolinska Institutet, M46, SE-141 86, Huddinge, Sweden. oskar.flygare@ki.se.
  • Jesper Enander
    Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska University Hospital, Karolinska Institutet, M46, SE-141 86, Huddinge, Sweden.
  • Erik Andersson
    Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
  • Brjánn Ljótsson
    Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska University Hospital, Karolinska Institutet, M46, SE-141 86, Huddinge, Sweden.
  • Volen Z Ivanov
    Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska University Hospital, Karolinska Institutet, M46, SE-141 86, Huddinge, Sweden.
  • David Mataix-Cols
    Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
  • Christian Rück
    Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.

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