Equitable Smoking Relapse Prevention

Overview

The goal of this clinical trial is to test a GPS (Global Positioning System)-enabled smartphone app (QuitBuddy) in current smokers. The main questions it aims to answer are: * Is Quitbuddy a good treatment for quitting smoking and "staying quit"? * Will a second treatment that connects people to help for their social and financial needs improve Quitbuddy? Participants will: * get nicotine lozenges in the mail * check in with the study team to report on their quitting progress after 1 day, 1 week, 1 month, 2 months, 3 months, and 6 months Researchers will compare Quitbuddy to an app made by the National Cancer Institute to see if Quitbuddy is better for helping people stay quit.

Tobacco smoking is a primary preventable trans-diagnostic risk factor that if targeted more effectively, could reduce a wide range of health disparities in prevalence, severity, treatment efficacy, and mortality across many chronic health conditions (e.g., diabetes, obstructive sleep apnea), reduce treatment complexity/multi-morbidity, and reduce healthcare costs up to 80%. The Southeast, in particular, has an urgent need to disrupt the status quo of tobacco control (\<2% The Centers for Disease Control and Prevention (CDC) recommended tobacco control appropriations; highest smoking and mortality) driven in large part through neglected patterns of social determinants of health (SDoH; poverty, access to care) that disproportionately impact racial and ethnic minorities in the form of greater smoking and chronic disease rates, and ultimately nearly a decade of life lost. Unfortunately, only 5% of smoking cessation attempts last at least one year, with lower success among Black smokers even though they smoke at similar rates and intensity, and make more quit attempts. Accordingly, mobile health (mHealth) may have particular utility in addressing racial disparities. Black smokers show high engagement rates with smartphones to access healthcare and greater adherence to digital interventions, which may facilitate tailoring to meet distinct needs. There is an urgent need to overcome equity gaps, which will require diversity and inclusion of individuals from underrepresented races/ethnicities to identify effective treatments. There is a need for just-in-time adaptive interventions (JITAIs) that 1) can be deployed rapidly (ideally before craving occurs), 2) effectively prevent or attenuate cravings quickly, and 3) are amenable to personalized treatment. Quitbuddy, the automated, yet personalized, JITAI app developed by the investigators, allows patients to prepare for high-risk situations before they arise, effectively promoting abstinence and preventing relapse. The overall goals are to optimize smart algorithms, identify personalized relapse risk, and automatically prompt NRT delivery in a real-time, preemptive manner, upon approaching personalized high-risk locations. Results from a National Institute on Drug abuse (NIDA)-funded (K23) pilot randomized controlled trial demonstrated outstanding usability (top 10% of over 500 apps), acceptability (\>80% compliance), and technical feasibility (\<10% GPS data loss). The investigators will build upon these promising data by testing effectiveness in a fully powered and rigorous SMART design with diverse representation of underserved populations and meeting community needs for SDoH interventions. Specific Aims Aims 1 \& 2: Evaluate QuitBuddy and SDoH augmentation intervention effectiveness for smoking cessation and relapse prevention via pragmatic remote SMART design (N=2,090). Expected Outcome: Superior 6-month biochemically verified abstinence rates for the QuitBuddy and SDoH augmentation interventions, relative to controls. Exploratory Aims: Test potential moderators/mediators of the effectiveness of the interventions. This approach integrates for the first time established theories of relapse risk, evidence-based treatment, smartphone/GPS technology, and SDoH. This project offers high-impact solutions to address health disparities across a wide range of chronic diseases that disproportionately affect under-served populations.

Conditions

Interventions

Eligibility

Locations (1)

Outcomes