Personalized prognostic prediction of treatment outcome for depressed patients in a naturalistic psychiatric hospital setting: A comparison of machine learning approaches.

Journal: Journal of consulting and clinical psychology
Published Date:

Abstract

OBJECTIVE: Research on predictors of treatment outcome in depression has largely derived from randomized clinical trials involving strict standardization of treatments, stringent patient exclusion criteria, and careful selection and supervision of study clinicians. The extent to which findings from such studies generalize to naturalistic psychiatric settings is unclear. This study sought to predict depression outcomes for patients seeking treatment within an intensive psychiatric hospital setting and while comparing the performance of a range of machine learning approaches.

Authors

  • Christian A Webb
    Department of Psychiatry, Harvard Medical School/McLean Hospital.
  • Zachary D Cohen
    University of Pennsylvania.
  • Courtney Beard
    Department of Psychiatry, Harvard Medical School/McLean Hospital.
  • Marie Forgeard
    Department of Clinical Psychology, William James College.
  • Andrew D Peckham
    Department of Psychiatry, Harvard Medical School/McLean Hospital.
  • Thröstur Björgvinsson
    Department of Psychiatry, Harvard Medical School/McLean Hospital.