Abstract

Background: Cigarette smoking is the leading cause of preventable disease in the U.S. Despite decades of slowly declining cigarette use, many older adults still actively smoke. Among Veterans, 22% overall and 17% of those over 50 years old actively smoked in 2015. It is notoriously difficult to quit, despite widespread knowledge among adults about the health hazards of persistent smoking and a frequent desire to quit. Given the prevalence and persistence of tobacco addiction, the U.S. Preventive Services Task Force (USPSTF) recommends that health care professionals offer cessation interventions at every health care encounter. Significance/Impact: The TeaM OUT intervention is specifically designed to increase motivation to quit, reduce roadblocks, and increase access to smoking cessation resources. It is especially focused connecting older active smokers not yet ready to quit to smoking cessation services. TeaM OUT has the potential to result in more frequent and longer periods of abstinence from smoking in this hard-to-reach population. Innovation: TeaM OUT combines a teachable moment with an opt-out, proactive approach to connect patients to existing cessation services using interactive voice response (IVR) technology. IVR is a proactive and affordable way to reach more older active smokers more frequently. Specific Aims: Aim 1: Among patients recently diagnosed with a pulmonary nodule, evaluate the effect of a proactive, teachable moment-based, smoking cessation outreach intervention (TeaM OUT) on increasing engagement with smoking cessation resources compared to Enhanced Usual Care. Aim 2: Evaluate the association of receipt of TeaM OUT with patient-reported seven-day point prevalence nicotine abstinence and quit motivation compared to Enhanced Usual Care. Aim 3: Qualitatively elicit perspectives from key stakeholders to inform acceptability and utility, implementation barriers and facilitators, and scalability of TeaM OUT. Methodology: In aim 1, we use pulmonary nodule registries to identify participants from three VA facilities (VA Portland, Minneapolis VA, Charleston VA). Patients with pulmonary nodules will be contacted after a stepped- wedged randomization at the clinical level. Participants in the intervention arm are called by the IVR Quitline, whereas participants the control arm must proactively choose to call the quitline. Options selected on the quitline will be recorded and analyzed using logistic regression to test if the quitline increases engagement with smoking cessation services. For aim 2, a subsample of participants in aim 1 will be contacted to complete additional surveys for 12 months after exposure to either arm of the study. We will measure nicotine abstinence, quit motivation, and communication and analyze the measures using multivariable, multi-level hierarchical logistic regression. In aim 3, we will qualitatively assess TeaM OUT by interviewing patient participants twice during the study – first at the time of the initial Proactive IVR contact and second at 13 months after enrollment. Clinical stakeholders will also be interviewed, with a focus on current and desired smoking cessations and experiences with the TeaM OUT intervention. Codes will be derived without preconceived categories. Next Steps/Implementation: We have purposely designed the intervention and overall study to maximize generalizability, feasibility, adoption, and sustainability of the intervention. We plan multiple scientific presentations and publications. Investigators will attend annual American Thoracic Society and HSRD conferences to present the research findings. We will place all de-identified data in our IRB-approved Health Services Research Repository (IRB #3535) at the conclusion of the study. We are creating a detailed toolkit as part of the study’s implementation process so that the IVR system can be easily replicated in multiple settings.

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DRA: Substance Use Disorders

DRE: Treatment - Efficacy/Effectiveness Clinical Trial, TRL - Applied/Translational

Keywords: Addictive Disorders, Comparative Effectiveness

MeSH Terms: None at this time.