Interactions between different eating patterns on recurrent binge-eating behavior: A machine learning approach.

Journal: The International journal of eating disorders
PMID: 31998997

Abstract

OBJECTIVE: Previous research has shown that certain eating patterns (rigid restraint, flexible restraint, intuitive eating) are differentially related to binge eating. However, despite the distinctiveness of these eating patterns, evidence suggests that they are not mutually exclusive. Using a machine learning-based decision tree classification analysis, we examined the interactions between different eating patterns in distinguishing recurrent (defined as ≥4 episodes the past month) from nonrecurrent binge eating.

Authors

  • Jake Linardon
    School of Psychology, Deakin University, Geelong, Victoria, Australia.
  • Mariel Messer
    School of Psychology, Deakin University, Geelong, Victoria, Australia.
  • Eric R Helms
    Sports Performance Research Institute New Zealand (SPRINZ), Faculty of Health and Environmental Science, Auckland University of Technology, Auckland, New Zealand.
  • Courtney McLean
    School of Psychology, Deakin University, Geelong, Victoria, Australia.
  • Lisa Incerti
    School of Psychology, Deakin University, Geelong, Victoria, Australia.
  • Matthew Fuller-Tyszkiewicz
    School of Psychology, Deakin University, Geelong, Victoria, Australia.

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