Micro-Randomized Trial to Optimize Digital Oral Health Behavior Change Interventions

The goal of the MRT is to investigate whether delivering (vs. not delivering) a prompt that contains engagement strategies grounded in decision science is beneficial in terms of promoting proximal oral health behavior (OHB) score, which reflects adherence to the 2x2x4 brushing protocol (Primary Aim) and also mobile health engagement (mHealth; Secondary Aim). Additionally, Exploratory Aims will concern (a) comparing different types of prompts in terms of proximal OHB score and mHealth engagement, (b) investigating the conditions in which prompts should be delivered to most effectively promote proximal OHB and mHealth engagement; and (c) investigating whether the effect of the engagement prompts (vs. no prompt) on OHB score varies across components of the 2x2x4 brushing regimen (i.e., frequency, duration, or coverage). Participants will receive an electronic toothbrush (eBrush) and a mobile app (Oralytics) that contains well-established behavior change strategies (e.g., goal setting, monitoring adherence, and feedback). Participants will be randomized twice per day - in the morning and the evening - to receive either (a) a push notification containing one of three (randomly selected) engagement strategies or (b) no notification. During the 10 weeks of the study, a Bayesian algorithm will iteratively adjust the probability of receiving a prompt or no prompt in any given randomization window, using prior behavioral data collected through the eBrush and mobile app. Data patterns suggesting positive effects of the prompts on adherence to brushing protocol, especially duration, will result in higher subsequent probabilities of receiving the prompts, whereas patterns suggesting null or negative effects will result in lower probabilities of receiving the prompts. Study results will inform the implementation of a smartphone-delivered behavior change intervention that further adapts the delivery of engagement prompts based on passively collected information from an eBrush and the mobile app.