Format of Original
Institute of Electrical and Electronics Engineers (IEEE)
2013 IEEE 37th Annual Computer Software and Applications Conference Workshops (COMPSACW)
Original Item ID
doi: 10.1109/COMPSACW.2013.61; PubMed Central: PMCID 3809119
The prevalence of tobacco dependence in the United States (US) remains alarming. Invariably, smoke-related health problems are the leading preventable causes of death in the US. Research has shown that a culturally tailored cessation counseling program can help reduce smoking and other tobacco usage. In this paper, we present a mobile health (mHealth) solution that leverages the Short Message Service (SMS) or text messaging feature of mobile devices to motivate behavior change among tobacco users. Our approach implements the Theory of Planned Behavior (TPB) and a phase-based framework. We make contributions to improving previous mHealth intervention approaches by delivering personalized and evidence-based motivational SMS messages to participants. Our proposed solution implements machine learning algorithms that take the participant's demographic profile and previous smoking behavior into account. We discuss our preliminary evaluation of the system against a couple of pseudo-scenarios and our observation of the system's performance.