scholarly journals Are individuals with loss-of-control eating more prone to dietary lapse in behavioural weight loss treatment? An ecological momentary assessment study

2018 ◽  
Vol 26 (3) ◽  
pp. 259-264 ◽  
Author(s):  
Stephanie M. Manasse ◽  
Leah M. Schumacher ◽  
Stephanie P. Goldstein ◽  
Gerald J. Martin ◽  
Ross D. Crosby ◽  
...  
Keyword(s):  
Weight Loss ◽  
Ecological Momentary Assessment ◽  
Loss Of Control ◽  
Loss Of Control Eating ◽  
Weight Loss Treatment ◽  
Assessment Study ◽  
Ecological Momentary ◽  
Momentary Assessment

Loss of control eating and psychological maintenance in children: An ecological momentary assessment study

2009 ◽  
Vol 47 (1) ◽  
pp. 26-33 ◽  
Author(s):  
Anja Hilbert ◽  
Winfried Rief ◽  
Brunna Tuschen-Caffier ◽  
Martina de Zwaan ◽  
Julia Czaja
Keyword(s):  
Ecological Momentary Assessment ◽  
Loss Of Control ◽  
Loss Of Control Eating ◽  
Assessment Study ◽  
Ecological Momentary ◽  
Momentary Assessment

State emotion modulation and loss-of-control eating in individuals with obesity: A preliminary ecological momentary assessment study

2021 ◽  
Vol 41 ◽  
pp. 101478
Author(s):  
Megan N. Parker ◽  
Megan Michael ◽  
Helen Burton Murray ◽  
Adrienne S. Juarascio ◽  
Stephanie M. Manasse
Keyword(s):  
Ecological Momentary Assessment ◽  
Loss Of Control ◽  
Loss Of Control Eating ◽  
Assessment Study ◽  
Ecological Momentary ◽  
Momentary Assessment

scholarly journals Negative Affect and Loss of Control Eating Among Bariatric Surgery Patients: an Ecological Momentary Assessment Pilot Investigation

2020 ◽  
Vol 30 (6) ◽  
pp. 2382-2387 ◽  
Author(s):  
Gail A. Williams-Kerver ◽  
Kristine J. Steffen ◽  
Kathryn E. Smith ◽  
Li Cao ◽  
Ross D. Crosby ◽  
...  
Keyword(s):  
Bariatric Surgery ◽  
Negative Affect ◽  
Ecological Momentary Assessment ◽  
Loss Of Control ◽  
Loss Of Control Eating ◽  
Pilot Investigation ◽  
Ecological Momentary ◽  
Momentary Assessment

scholarly journals Combining ecological momentary assessment, wrist-based eating detection, and dietary assessment to characterize dietary lapse: A multi-method study protocol

2021 ◽  
Vol 7 ◽  
pp. 205520762098821
Author(s):  
Stephanie P Goldstein ◽  
Adam Hoover ◽  
E Whitney Evans ◽  
J Graham Thomas
Keyword(s):  
Weight Loss ◽  
Eating Behavior ◽  
Ecological Momentary Assessment ◽  
Structured Interview ◽  
Self Report ◽  
Significant Weight Loss ◽  
Clinically Significant ◽  
Ecological Momentary ◽  
Momentary Assessment ◽  
Lapse Behavior

Objectives Behavioral obesity treatment (BOT) produces clinically significant weight loss and health benefits for many individuals with overweight/obesity. Yet, many individuals in BOT do not achieve clinically significant weight loss and/or experience weight regain. Lapses (i.e., eating that deviates from the BOT prescribed diet) could explain poor outcomes, but the behavior is understudied because it can be difficult to assess. We propose to study lapses using a multi-method approach, which allows us to identify objectively-measured characteristics of lapse behavior (e.g., eating rate, duration), examine the association between lapse and weight change, and estimate nutrition composition of lapse. Method We are recruiting participants (n = 40) with overweight/obesity to enroll in a 24-week BOT. Participants complete biweekly 7-day ecological momentary assessment (EMA) to self-report on eating behavior, including dietary lapses. Participants continuously wear the wrist-worn ActiGraph Link to characterize eating behavior. Participants complete 24-hour dietary recalls via structured interview at 6-week intervals to measure the composition of all food and beverages consumed. Results While data collection for this trial is still ongoing, we present data from three pilot participants who completed EMA and wore the ActiGraph to illustrate the feasibility, benefits, and challenges of this work. Conclusion This protocol will be the first multi-method study of dietary lapses in BOT. Upon completion, this will be one of the largest published studies of passive eating detection and EMA-reported lapse. The integration of EMA and passive sensing to characterize eating provides contextually rich data that will ultimately inform a nuanced understanding of lapse behavior and enable novel interventions. Trial registration: Registered clinical trial NCT03739151; URL: https://clinicaltrials.gov/ct2/show/NCT03739151

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