Lauren M Schaefer1, Scott G Engel1,2, Stephen A Wonderlich1,2. 1. Sanford Research, Center for Bio-behavioral Research. 2. Department of Psychiatry and Behavioral Science, University of North Dakota School of Medicine and Health Sciences, Fargo, North Dakota, USA.
Abstract
PURPOSE OF REVIEW: Ecological momentary assessment (EMA) is an important tool for clarifying common precipitants and consequences of eating disorder symptoms that might be meaningfully targeted in treatments for these pernicious disorders. This article reviews recent advances in EMA work conducted within clinical eating disorder samples. RECENT FINDINGS: Published studies from the past 2.5 years can broadly be categorized as involving functional analysis of eating disorder behaviors, examining hypothesized predictors of eating disorder symptoms, or applying novel approaches to EMA data. Examples of the latter category include the use of latent profile analysis with EMA data, integration of neurocognitive (e.g., ambulatory inhibitory control task) or biological indicators (e.g., fMRI, plasma leptin), and examining changes in associations between momentary variables over time through multiwave EMA data collection. SUMMARY: EMA studies in eating disorders have advanced significantly in recent years, with findings demonstrating strong support for the emotion regulation function of eating disorder behaviors and momentary predictors of distinct eating disorder symptoms. The use of novel statistical and data collection approaches represent exciting areas of growth, with likely implications for intervention approaches, including those that utilize ambulatory technology to deliver treatment.
PURPOSE OF REVIEW: Ecological momentary assessment (EMA) is an important tool for clarifying common precipitants and consequences of eating disorder symptoms that might be meaningfully targeted in treatments for these pernicious disorders. This article reviews recent advances in EMA work conducted within clinical eating disorder samples. RECENT FINDINGS: Published studies from the past 2.5 years can broadly be categorized as involving functional analysis of eating disorder behaviors, examining hypothesized predictors of eating disorder symptoms, or applying novel approaches to EMA data. Examples of the latter category include the use of latent profile analysis with EMA data, integration of neurocognitive (e.g., ambulatory inhibitory control task) or biological indicators (e.g., fMRI, plasma leptin), and examining changes in associations between momentary variables over time through multiwave EMA data collection. SUMMARY: EMA studies in eating disorders have advanced significantly in recent years, with findings demonstrating strong support for the emotion regulation function of eating disorder behaviors and momentary predictors of distinct eating disorder symptoms. The use of novel statistical and data collection approaches represent exciting areas of growth, with likely implications for intervention approaches, including those that utilize ambulatory technology to deliver treatment.
Authors: Elizabeth W Lampe; Olivia Wons; Lauren C Taylor; Adrienne S Juarascio; Stephanie M Manasse Journal: Eat Weight Disord Date: 2022-01-22 Impact factor: 3.008