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Toward Individualized Prediction of Binge-Eating Episodes Based on Ecological Momentary Assessment Data: Item Development and Pilot Study in Patients With Bulimia Nervosa and Binge-Eating Disorder.

Ann-Kathrin ArendTim KaiserBjörn PannickeJulia ReichenbergerSilke NaabUlrich VoderholzerJens Blechert
Published in: JMIR medical informatics (2023)
Predicting binge-eating episodes from psychological and contextual states seems feasible and accurate, but the predictor sets are highly idiographic. This has practical implications for mobile health and just-in-time adaptive interventions. Furthermore, current theories around binge eating need to account for this high between-person variability and broaden the scope of potential antecedent factors. Ultimately, a radical shift from purely nomothetic models to idiographic prediction models and theories is required.
Keyphrases
  • physical activity
  • weight loss
  • anorexia nervosa
  • human health
  • climate change
  • risk assessment
  • mass spectrometry
  • deep learning
  • psychometric properties