ArticleJMIR formative research2023
Weight Loss Expectations of Adults With Binge Eating: Cross-sectional Study With a Human-Centered Design Approach.
Article in JMIR formative research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Exploring Drivers of Binge Eating in Individuals With Food Insecurity and Recurrent Binge Eating: A Qualitative Analysis.The International journal of eating disorders · 2025Article
- Guided Self-Help for Binge Eating Prior to Weight Management: The Experience of Clients and Guides.Nutrients · 2025Article
- Exploring pathways between internalized weight bias, eating disorder psychopathology, and weight loss expectations in treatment-seeking adults with binge eating and obesity.Eating and weight disorders : EWD · 2025Article
- Exploring Pathways between Internalized Weight Bias, Eating Disorder Psychopathology, and Weight Loss Expectations in Treatment-Seeking Adults with Binge Eating and Obesity.Research square · 2024Article
- Exploring successes, barriers, and enablers in the one-year digital Healthy Weight Coaching.BMC health services research · 2024Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundPeople tend to overestimate their expectations for weight loss relative to what is achievable in a typical evidence-based behavioral weight management program, which can impact treatment satisfaction and outcomes. We are engaged in formative research to design a digital intervention that addresses binge eating and weight management; thus, understanding expectations among this group can inform more engaging intervention designs to produce a digital intervention that can achieve greater clinical success. Studies examining weight loss expectations have primarily focused on people who have overweight or obesity. Only one study has investigated weight loss expectations among people with binge eating disorder, a population that frequently experiences elevated weight and shape concerns and often presents to treatment with the goal of losing weight.
objectiveThe aim of the study is to investigate differences in weight loss expectations among people with varying levels of binge eating to inform the design of a digital intervention for binge eating and weight management. Such an evaluation may be crucial for people presenting for a digital intervention, given that engagement and dropout are notable problems for digital behavior change interventions. We tested the hypotheses that (1) people who endorsed some or recurrent binge eating would expect to lose more weight than those who did not endorse binge eating and (2) people who endorsed a more severe versus a low or moderate overvaluation of weight and shape would have higher weight loss expectations.
methodsA total of 760 adults (n=504, 66% female; n=441, 58% non-Hispanic White) completed a web-based screening questionnaire. One-way ANOVAs were conducted to explore weight loss expectations for binge eating status as well as overvaluation of shape and weight.
resultsWeight loss expectations significantly differed by binge eating status. Those who endorsed some and recurrent binge eating expected to lose more weight than those who endorsed no binge eating. Participants with severe overvaluation of weight or shape expected to lose the most weight compared to those with low or moderate levels of overvaluation of weight and shape.
conclusionsIn the sample, people interested in a study to inform a digital intervention for binge eating and weight management overestimated their expectations for weight loss. Given that weight loss expectations can impact treatment completion and success, it may be important to assess and modify weight loss expectations among people with binge eating prior to enrolling in a digital intervention. Future work should design and test features that can modify these expectations relative to individuals' intended treatment goals to facilitate engagement and successful outcomes in a digital intervention.
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