Participant Engagement in Microrandomized Trials of mHealth Interventions: Scoping Review
Authors: Leong Utek , Chakraborty Bibhas 
Published: November 2022

Background: Micro-randomized trials (MRTs) have emerged as the gold standard for the development and evaluation of multi-component, adaptive mobile health (mHealth) interventions. However, not much is known about the state of participant engagement measurement in MRTs of mHealth interventions.Objective: In this scoping review, we aimed to quantify the proportion of existing/planned MRTs of mHealth interventions to date that have assessed (or have planned to assess) engagement. For trials that have explicitly assessed (or have planned to assess) engagement, we also aimed to investigate how engagement has been operationalized and to identify what kind of factors have been studied as determinants of engagement in MRTs of mHealth interventions.Methods: We conducted a broad search for MRTs of mHealth interventions in five databases and manually searched preprint servers and trial registries. Study characteristics of each included evidence source were extracted. We coded and categorized this data to identify how engagement has been operationalized and which determinants, moderators, and covariates have been assessed in existing MRTs.Results: Our database and manual searches yielded 22 eligible evidence sources. Most of these studies were designed to evaluate the effect of intervention components (14/22 studies). The median sample size of the included MRTs was 110.5. At least one explicit measure of engagement was included in 90.91% (20/22 studies) of the included MRTs. We found that objective measures like system usage data (16/20; 80%) and sensor data (7/20; 35%) are the most common methods of measuring engagement. All studies included at least one measure of the physical facet of engagement, but the affective and cognitive facets of engagement have largely been neglected (only measured by one study each). Most studies measured engagement with the mHealth intervention (Little e) and not with the health behavior of interest (Big E). Only 6 of the 20 studies to measure engagement (30%) assessed the determinants of engagement in MRTs of mHealth interventions – notification-related variables were the most common determinants of engagement assessed (4/6 studies). Three of these studies also examined the moderators of participant engagement – 2 studies investigated time-related moderators exclusively and 1 study planned to investigate a comprehensive set of physiological and psychosocial moderators in addition to time-related moderators.Conclusions: Although the measurement of participant engagement in MRTs of mHealth interventions is prevalent, there is a need for future trials to diversify the measurement of engagement. There is also a need for researchers to address the lack of attention to how engagement is determined and moderated in MRTs of mHealth interventions. We hope that by mapping the state of engagement measurement in existing MRTs of mHealth interventions, this review will encourage researchers to pay more attention to these issues when planning for engagement measurement in future trials.