Optimizing a Just-in-Time Adaptive Intervention to Improve Dietary Adherence in Behavioral Obesity Treatment: Protocol for a Microrandomized Trial

Abstract

Background Behavioral obesity treatment (BOT) is a gold standard approach to weight loss and reduces the risk of cardiovascular disease. However, frequent lapses from the recommended diet stymie weight loss and prevent individuals from actualizing the health benefits of BOT. There is a need for innovative treatment solutions to improve adherence to the prescribed diet in BOT. Objective The aim of this study is to optimize a smartphone-based just-in-time adaptive intervention (JITAI) that uses daily surveys to assess triggers for dietary lapses and deliver interventions when the risk of lapse is high. A microrandomized trial design will evaluate the efficacy of any interventions (ie, theory-driven or a generic alert to risk) on the proximal outcome of lapses during BOT, compare the effects of theory-driven interventions with generic risk alerts on the proximal outcome of lapse, and examine contextual moderators of interventions. Methods Adults with overweight or obesity and cardiovascular disease risk (n=159) will participate in a 6-month web-based BOT while using the JITAI to prevent dietary lapses. Each time the JITAI detects elevated lapse risk, the participant will be randomized to no intervention, a generic risk alert, or 1 of 4 theory-driven interventions (ie, enhanced education, building self-efficacy, fostering motivation, and improving self-regulation). The primary outcome will be the occurrence of lapse in the 2.5 hours following randomization. Contextual moderators of intervention efficacy will also be explored (eg, location and time of day). The data will inform an optimized JITAI that selects the theory-driven approach most likely to prevent lapses in a given moment. Results The recruitment for the microrandomized trial began on April 19, 2021, and is ongoing. Conclusions This study will optimize a JITAI for dietary lapses so that it empirically tailors the provision of evidence-based intervention to the individual and context. The finalized JITAI will be evaluated for efficacy in a future randomized controlled trial of distal health outcomes (eg, weight loss). Trial Registration ClinicalTrials.gov NCT04784585; http://clinicaltrials.gov/ct2/show/NCT04784585 International Registered Report Identifier (IRRID) DERR1-10.2196/33568

The Potential Role of Digital Health in Obesity Care

“…They aim to provide the right type/amount of support, at the right time, by adapting to an individual’s changing behaviour—they utilise technology that dynamically adjusts the intervention approach based on an individual’s changing behaviour in real time [ 50 ]. JITAIs have been shown to diminish sedentary behaviours and increase physical activity in individuals with obesity [ 51 , 52 ], and a trial is underway to test a JITAI aimed at preventing lapses in healthy eating behaviour [ 53 ].…”

Participant Engagement in Microrandomized Trials of mHealth Interventions: Scoping Review

“…16 out of the 20 studies (80%) to measure engagement included at least one measure of this category. Generally, researchers measured usage in three domains: (1) usage of a mobile application [17,21,28,35,38], (2) participant retention [18,25,30,31],…”

“…Two studies measured usage as the access/viewing of intervention application content. In Goldstein et al [21], researchers planned to use the percentage of in-app interventions accessed as an indicator of usage. Valle et al [38] on the other hand, measured usage as the proportion of intervention messages viewed daily.…”

“…11 out of the 20 studies (55%) to measure engagement included at least one measure of this category. 10 out of 11 studies measured responsiveness in terms of survey completion (completion of single items, logs, diaries, or ecological momentary assessments) [18,19,21,22,25,28,30,31,36,37]. Aguilera et al [18] for example, measured engagement as response rates to daily text messages tasking participants to rate their mood.…”

“…Aguilera et al [18] for example, measured engagement as response rates to daily text messages tasking participants to rate their mood. Goldstein et al [21] on the other hand, included the percentage of ecological momentary assessments (EMAs) completed as an indicator of engagement.…”