Unhealthy behaviors such as smoking is the major cause for premature deaths and changing behaviors by oneself can be difficult. That is where eHealth applications come into rescue. One of the recent research explored the possibility of using a Reinforcement Learning model to choose persuasive types for a virtual coach to adopt to persuade people to prepare for smoke-quitting and it has shown advantages. However, there are still more aspects to investigate in this context except the persuasive types of the messages, and this paper intended to further look into using reinforcement learning to choose activities for preparing the users to quit smoking, To be more specific, we implemented and evaluated a reinforcement learning model to choose activities to optimize both the effort spent by the users and also the likelihood of them staying for the next session. The result suggests that reinforcement learning is a promising approach to choose activities for people to prepare for quitting smoking and it can move the users to states that they are more likely to spend a good effort on the activities and are more likely to come back to the next session.
This work is part of the multidisciplinary research project Perfect Fit, which is supported by several funders organized by the Netherlands Organization for Scientific Research (NWO), program Commit2Data - Big Data \& Health (project number 628.011.211). Besides NWO, the funders include the Netherlands Organisation for Health Research and Development (ZonMw), Hartstichting, the Ministry of Health, Welfare, and Sport (VWS), Health Holland, and the Netherlands eScience Center.