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. 2021 May 10;5(5):e23809.
doi: 10.2196/23809.

Integrating User-Centered Design and Behavioral Science to Design a Mobile Intervention for Obesity and Binge Eating: Mixed Methods Analysis

Affiliations

Integrating User-Centered Design and Behavioral Science to Design a Mobile Intervention for Obesity and Binge Eating: Mixed Methods Analysis

Andrea K Graham et al. JMIR Form Res. .

Abstract

Background: Accounting for how end users engage with technologies is imperative for designing an efficacious mobile behavioral intervention.

Objective: This mixed methods analysis examined the translational potential of user-centered design and basic behavioral science to inform the design of a new mobile intervention for obesity and binge eating.

Methods: A total of 22 adults (7/22, 32% non-Hispanic White; 8/22, 36% male) with self-reported obesity and recurrent binge eating (≥12 episodes in 3 months) who were interested in losing weight and reducing binge eating completed a prototyping design activity over 1 week. Leveraging evidence from behavioral economics on choice architecture, participants chose treatment strategies from 20 options (aligned with treatment targets composing a theoretical model of the relation between binge eating and weight) to demonstrate which strategies and treatment targets are relevant to end users. The process by which participants selected and implemented strategies and their change in outcomes were analyzed.

Results: Although prompted to select one strategy, participants selected between 1 and 3 strategies, citing perceived achievability, helpfulness, or relevance as selection reasons. Over the week, all practiced a strategy at least once; 82% (18/22) struggled with implementation, and 23% (5/22) added a new strategy. Several themes emerged on successes and challenges with implementation, yielding design implications for supporting users in behavior change. In postexperiment reflections, 82% (18/22) indicated the strategy was helpful, and 86% (19/22) planned to continue use. One-week average within-subject changes in weight (-2.2 [SD -5.0] pounds) and binge eating (-1.6 [SD -1.8] episodes) indicated small clinical improvement.

Conclusions: Applying user-centered design and basic behavioral science yielded design insights to incorporate personalization through user choice with guidance, which may enhance engagement with and potential efficacy of digital health interventions.

Keywords: binge eating; engagement; experimental therapeutics; mobile intervention; obesity; user-centered design.

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Conflict of interest statement

Conflicts of Interest: AKG reports a grant from the National Institute of Diabetes and Digestive and Kidney Diseases during the study and personal fees from Actualize Therapy outside the submitted work. SAM reports a grant from the National Institute of Mental Health during the study and personal fees from Apple Inc outside the submitted work. BS reports personal fees from Apple and Actigraph outside the submitted work. DCM reports personal fees from Otsuka Pharmaceuticals, Apple Inc, Pear Therapeutics, One Mind Foundation, and Adaptive Health Inc outside the submitted work. MR, SWN, EAG, AC, and JEW have no disclosures.

Figures

Figure 1
Figure 1
Theoretical model depicting the relation between binge eating and weight gain. The model integrates treatment targets (white boxes) in evidence-based treatments for obesity or binge eating [26-28]. Clinical outcomes are depicted in the gray boxes.
Figure 2
Figure 2
Schematic of participant flow through the study activities, including prototyping, the focus of this analysis, and the three research prompts it comprises. Of the 25 participants who enrolled, 22 began and completed prototyping.

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