A machine learning personalized treatment rule to optimize assignment to psychotherapies for grief among veterans.

Journal: Journal of affective disorders
PMID: 38718947

Abstract

BACKGROUND: Complex grief patterns are associated with significant suffering, functional impairments, health and mental health problems, and increased healthcare use. This burden may be even more pronounced among veterans. Behavioral Activation and Therapeutic Exposure (BATE-G) and Cognitive Therapy for Grief (CT-G) are two evidence-based interventions for grief. The goal of this study was to use a precision medicine approach to develop a personalized treatment rule to optimize assignment among these psychotherapies.

Authors

  • Evangelia Argyriou
    Department of Psychiatry & Behavioral Sciences, Medical University of South Carolina, United States; Department of Psychology, Indiana University Indianapolis, United States.
  • Daniel Gros
    Department of Psychiatry & Behavioral Sciences, Medical University of South Carolina, United States; Mental Health Service, Ralph H. Johnson VA Healthcare System, United States. Electronic address: grosd@musc.edu.
  • Melba A Hernandez Tejada
    Faillace Department of Psychiatry, University of Texas Health Science Center at Houston, United States.
  • Wendy A Muzzy
    Department of Psychiatry & Behavioral Sciences, Medical University of South Carolina, United States; Mental Health Service, Ralph H. Johnson VA Healthcare System, United States.
  • Ronald Acierno
    Faillace Department of Psychiatry, University of Texas Health Science Center at Houston, United States.

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