Real-Time Patterns of Smoking and Alcohol Use: A Daily Data Analysis

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DESCRIPTION (provided by applicant): Real-time patterns of smoking and alcohol use: A daily data analysis Cigarette smoking is the leading cause of preventable death and disability in the United States1-3. Despite the strong relationship between smoking and cancer-related morbidity and mortality and the noted health benefits of quitting 4-7, very few smokers quit every year 8, and between 70%-95% of those who do quit relapse within the first year 9. Heavy drinking, which is highly co-morbid with cigarette smoking 10, also represents a significant risk factor for cancer-related illness and mortality11-13, and is also implicated in persistent smoking, and less success (or attempts) at quitting smoking. Nearly half of all problem drinkers are nicotine dependent 14, and the combined influence of alcohol and tobacco has a multiplicative effect on increasing cancer-related risk.12,15 Self-efficacy (SE) to abstain from smoking is one of the most important determinants of smoking cessation outcomes. However, the mechanism of how SE changes is not well understood. One reason is that studies have failed to take into account other factors that may influence associations between SE and smoking that are particularly relevant to smoking behavior, such as heavy drinking. The proposed application will address this gap in the research by identifying daily changing factors that impede or promote SE and future smoking cessation efforts in a sample of 84 heavy drinking smokers. Participants will track their smoking, alcohol consumption, and SE related to smoking twice a day for 28 days using innovative interactive voice response (IVR) telephone surveys. We will predict the likelihood of future smoking cessation outcomes (e.g., reduced cigarettes per day, cessation attempts, and complete abstinence) at 1- and 6-months follow-up from these daily factors. Research to date has not taken advantage of innovative methods that capture the impact of daily factors on smoking cessation outcomes, nor have they focused specifically on high-risk heavy drinking smokers, despite their elevated cancer-related risk. An empirically supported model describing how daily SE mediates the association between daily drinking and smoking to future cessation outcomes is crucial for developing effective smoking cessation interventions. This R03 is consistent with recent initiatives at the National Cancer Institute to: (a) use innovative approaches to identify behaviors that impact cancer-related risk that could be targeted in new treatments; (b) reduce tobacco use and the prevalence of cigarette smoking; (c) understand the impact of co-morbid conditions on cancer-related risk; and (c) prepare a new generation of investigators for cancer research16-19. This R03 would provide a strong basis for moving the field forward in these areas and to begin to answer many of the questions that remain about how high-risk groups initiate and maintain changes in cancer-related risk behaviors. Findings from this study will have important long-term clinical and public health significance in decreasing the overall prevalence of cancer-related risk and illness by developing targeted cessation interventions for the unique needs of heavy drinking smokers.