Patterns of eating behavior in people with severe obesity seeking weight loss treatment: An exploratory study

Abstract Evidence-based behavioral weight loss treatment is under-utilized. To increase initiation of treatment, we developed a single-session, online, primary care-based intervention (“mobilization tool”). We evaluated the mobilization tool's acceptability for primary care patients with obesity, trial design feasibility, and signal of an effect of the tool on treatment initiation. In this cluster randomized feasibility trial, primary care providers (PCPs) were randomized to a mobilization tool or comparator tool arm. Patients with obesity and a scheduled appointment with a randomized PCP were assigned to complete the mobilization or comparator tool prior to their appointment. The online mobilization tool asks patients to answer questions about a variety of weight-related topics and then provides automated, tailored feedback that addresses psychosocial determinants of weight loss treatment initiation. The comparator tool provided a nontailored description of treatments. All participants were offered free enrollment in behavioral weight loss treatments. Six PCPs were randomized. Sixty patients (57% female; 66% white; aged 55 ± 13 years) participated in this study of 296 contacted for eligibility evaluation (20.2%). Six-month follow-up assessments were completed by 65% (22/34) of the mobilization and 73% (19/26) of comparator tool participants. Participants completing the acceptability survey reported that the mobilization tool was usable, enjoyable, informative, and useful. Weight loss treatment was initiated by 59% (n = 19) of mobilization and 33% (n = 8) of comparator tool participants. The mobilization tool shows promise for increasing treatment initiation among primary care patients, which may increase population weight loss. Trial Registration: Clinicaltrials.gov identifier: NCT02708121.

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

Digital Health ◽

10.1177/2055207620988212 ◽

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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