Omar Ortega Jr
Research Mentor: Lizbeth Benson
Mentor Department: Survey Research Center, Data Science for Dynamic Intervention Decision-Making Center, ISR
Author(s): Omar Ortega , Lizbeth Benson
Session: Session 7 (4:00 PM – 4:50 PM)
Presentation Type: Poster 131
Abstract
Background: Tobacco use is the leading cause of preventable disease and death. Interventions delivered by smartphone applications are an accessible way to deliver smoking cessation support in moments when it is most needed. Existing interventions have been shown to improve short-term cessation, but sustained user engagement remains an issue that limits overall intervention effectiveness. One method for increasing engagement is to provide individuals with visualizations of their self-monitoring data during a quit attempt (e.g., money saved on cigarettes or days abstinent). Personalized feedback data visualizations may help users track their abstinence progress, recognize patterns in cessation attempts, and stay motivated. The goal of this study is to examine which elements of personalized feedback data visualizations are perceived as useful for inclusion in a smoking cessation app by individuals who have recently quit smoking. Methods: Participants (N=8 individuals who recently successfully quit smoking) will engage in a mixed methods study involving an initial needs assessment interview and survey to determine smoking history. This is followed by an in-person co-design workshop focused on introducing and creating visualizations. Lastly, a final quantitative survey will determine preference in visualizations. Results: The IRB application for this study is currently under review. Data collection is anticipated to occur in spring and summer of 2026. Discussion: Findings of this study will contribute to future development of effective smoking cessation applications. Individuals who have recently quit smoking provide a unique perspective on which types of personalized feedback would have been useful during their own quit process, thereby informing strategies likely to benefit future individuals attempting to quit smoking. Knowledge gained from this study will also be used to inform the development of personalized feedback data visualizations, which will be examined in future research for their potential to increase user engagement and sustained abstinence.
