Positive affect dysregulation and its relation to binge eating size and frequency.

Negative affect is an established predictor of binge eating, yet less is known about positive affect. Low positive affect has been theorized to increase binge eating, but a better understanding is needed on the relationship between positive affect and binge eating frequency and size. Participants were 182 treatment-seeking adults (76% self-identified as female; 45% self-identified their race as Black and 40% as White; and 25% self-identified their ethnicity as Hispanic/Latino) with self-reported recurrent binge eating (≥12 binge episodes in the past 3 months). Participants completed the positive and negative affect schedule (PANAS) survey and the eating disorder examination to assess frequency of objective binge episodes (OBEs) and subjective binge episodes (SBEs) over the past 3 months. OBEs and SBEs also were combined to yield total binge episodes over the past 3 months. Independent t-tests and linear regression analyses were used to test associations between positive affect scores and binge episode size and frequencies, and to compare low versus higher positive affect on binge frequency. Additional exploratory models were conducted controlling for negative affect, identity characteristics, and socio-demographic variables. Lower positive affect was significantly associated with more frequent total binge episodes, but not OBEs and SBEs when assessed independently. Findings remained consistent when controlling for covariates and when comparing individuals with the lowest versus higher positive affect levels. Overall, results lend support to the theory that low positive affect is associated with binge eating. Increasing positive affect may be an important treatment consideration for those with recurrent binge eating.

Designing Digital Interventions for Eating Disorders.

PURPOSE OF REVIEW: Digital (i.e., online, mobile) interventions have potential to increase access to care for people with eating disorders, but engagement with digital interventions has been challenging. Human-centered design is a methodology that centralizes the design of technologies on the people who will be using them and the settings in which they will be implemented, to yield solutions with high engagement and clinical impact. The paper presents an overview of the human-centered design process, followed by a review of publications that have applied design methods to digital interventions for eating disorders. RECENT FINDINGS: Design research has been conducted via needs assessments, prototyping and usability studies, and during ongoing delivery of digital eating disorder interventions. There has been growing research applying design methods to digital interventions for eating disorders. Additional opportunities include designing for implementation, designing for equity, and designing for the optimization of digital interventions over time.

Weight Loss Expectations of Adults With Binge Eating: Cross-sectional Study With a Human-Centered Design Approach.

BACKGROUND: People 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. OBJECTIVE: The 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. METHODS: A 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. RESULTS: Weight 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. CONCLUSIONS: In 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.

The role of stress in the association among food insecurity, eating disorder pathology, and binge eating-related appetitive traits.

PURPOSE: Growing literature demonstrates a positive association between food insecurity (FI) and eating disorder pathology. Additionally, FI has been associated with two appetitive traits strongly linked to binge eating, food responsiveness and emotional overeating. However, little research has investigated factors that might help to explain these associations. One hypothesis is that experiencing FI may increase stress, and that eating disorder pathology, particularly binge eating-related phenotypes, may serve as a coping strategy. This study explores stress as a potential mechanism in the association between FI and general eating disorder pathology, as well as two appetitive traits strongly associated with binge eating (food responsiveness and emotional overeating). METHODS: Cis-gender women (N = 634) completed online questionnaires assessing FI, stress, eating disorder pathology (measured via the total score on the Short Eating Disorder Examination Questionnaire), and binge eating-related appetitive traits (measured via the Adult Eating Behavior Questionnaire). Cross-sectional indirect effects analyses with a 1000-sample bootstrap were used to test pathways among FI, stress, and eating-related constructs. RESULTS: FI was significantly associated with eating disorder pathology and associated appetitive traits (ps < 0.001). Stress explained a significant proportion of the correlation between FI and each eating-related construct. CONCLUSIONS: Our findings extend prior research on the relationships between FI, eating disorder pathology, and binge eating-related appetitive traits to provide preliminary evidence that stress may act as an underlying mechanism. Future studies should use longitudinal designs to assess the prospective relationships among these constructs.