Predicting responsiveness to a dialectical behaviour therapy skills training app for recurrent binge eating: A machine learning approach.

Journal: Behaviour research and therapy
Published Date: Apr 22, 2025

Abstract

OBJECTIVE: Smartphone applications (apps) show promise as an effective and scalable intervention modality for disordered eating, yet responsiveness varies considerably. The ability to predict user responses to app-based interventions is currently limited. Machine learning (ML) techniques have shown potential to improve prediction of complex clinical outcomes. We applied ML techniques to predict responsiveness to a dialectical behaviour therapy-based smartphone app for recurrent binge eating.

Authors

  • Zoe McClure
    School of Psychology, Deakin University, Geelong, Australia.
  • Christopher J Greenwood
    Centre for Social and Early Emotional Development and School of Psychology, Deakin University, Geelong, Victoria.
  • Matthew Fuller-Tyszkiewicz
    School of Psychology, Deakin University, Geelong, Victoria, Australia.
  • Mariel Messer
    School of Psychology, Deakin University, Geelong, Victoria, Australia.
  • Jake Linardon
    School of Psychology, Deakin University, Geelong, Victoria, Australia.

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