# Randomized Controlled Trial of a Novel Smoking Cessation Application Tailored to Individuals with Serious Mental Illness. > **NIH NIH R01** · WAKE FOREST UNIVERSITY HEALTH SCIENCES · 2024 · $465,465 ## Abstract PROJECT SUMMARY/ABSTRACT Tobacco use remains at alarming high rates amongst individuals with serious mental illness, such as schizophrenia spectrum, bipolar, and recurring depressive disorders. Smoking tobacco is the number one preventable cause of death in this population, shortening the lifespan of adults with serious mental illness by 25 years and contributing to $317 billion in healthcare expenditures and indirect loss of earnings and disability benefits. Novel and effective models to deliver wider-reaching smoking cessation interventions to individuals with serious mental illness are highly needed and indicated as a priority for NIH. Mobile apps are a promising method to deliver smoking cessation treatments to people with serious mental illness. Despite numerous apps available to use for people with serious mental illness, our feasibility research has demonstrated that using these apps presents daunting challenges for this population. Based on this work, we developed Learn to Quit, a user-centered smoking cessation app tailored to the needs of individuals with serious mental illness. The app’s main active ingredient is a novel behavioral treatment that has shown promise as a smoking cessation intervention -- Acceptance and Commitment Therapy. The app provides education about the use of nicotine replacement therapy and recommendations from US Clinical Practice Guidelines to ensure alignment with best clinical practices. In a recent pilot randomized controlled trial (R00 DA037276), comparing Learn to Quit versus NCI’s QuitGuide, we demonstrated: (1) high recruitment and retention rates, (2) high levels of user engagement with Learn to Quit, (3) an effective method to conduct a large multi-site randomized controlled trial, and (4) promising cessation outcomes. While this developmental work provides initial evidence of Learn to Quit’s usability, feasibility, and preliminary efficacy, a large scale randomized controlled trial is needed to test its efficacy in a representative sample of patients with serious mental illness. Therefore, the proposed study will: (1) employ a randomized parallel arm design to compare the efficacy of Learn to Quit vs. NCI’s QuitGuide, (2) use rigorous methods to evaluate mediators of app engagement and app efficacy, and (3) examine the cost-effectiveness of Learn to Quit compared to a non-tailored app designed for the general population. The study addresses a serious problem -- high smoking rates among people with serious mental illness -- and proposes to test the efficacy of an easily-accessible smoking cessation intervention, using technology with the potential for high population-level reach. ## Key facts - **NIH application ID:** 11066934 - **Project number:** 7R01DA047301-06 - **Recipient organization:** WAKE FOREST UNIVERSITY HEALTH SCIENCES - **Principal Investigator:** Roger Vilardaga - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $465,465 - **Award type:** 7 - **Project period:** 2020-03-15 → 2025-12-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/11066934 ## Citation > US National Institutes of Health, RePORTER application 11066934, Randomized Controlled Trial of a Novel Smoking Cessation Application Tailored to Individuals with Serious Mental Illness. (7R01DA047301-06). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/11066934. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*