  Dental disease is still one of the most common chronic diseases in the United
States. While dental disease is preventable through healthy oral self-care
behaviors (OSCB), this basic behavior is not consistently practiced. We have
developed Oralytics, an online, reinforcement learning (RL) algorithm that
optimizes the delivery of personalized intervention prompts to improve OSCB. In
this paper, we offer a full overview of algorithm design decisions made using
prior data, domain expertise, and experiments in a simulation test bed. The
finalized RL algorithm was deployed in the Oralytics clinical trial, conducted
from fall 2023 to summer 2024.
