Grant Number:	5R01CA258269-04 Interpret this number
Primary Investigator:	Poghosyan, Hermine
Organization:	Yale University
Project Title:	Longitudinal Mixed Method Investigation of Social Networks and Affective States as Determinants of Smoking Behavior Among Cancer Patient
Fiscal Year:	2023

PROJECT SUMMARY Tobacco use causes at least 12 types of cancer and is responsible for 30% of all cancer deaths in the United States. Quitting smoking is the single most effective approach to protect cancer patients from smoking complications, extend survival, and ensure best health outcomes. Despite the adverse health effects, 10-64% of cancer patients, depending on cancer type, continue to smoke. Cancer diagnosis is emotionally shocking experience and patients often use tobacco to regulate negative emotions. Smoking rates are the highest among patients with tobacco-related cancers who have a long smoking history, high nicotine addiction and difficulty with quitting smoking. Even after quitting they relapse as discontinuation of tobacco leads to negative emotions, which in turn impacts smoking behavior. Smoking behavior is embedded within individual's affective niche and social networks and is influenced by the behaviors of individuals in the network. Yet, to date, no attention has been paid to how social networks and affective states influence smoking behavior of patients with tobacco-related cancer who have high rates of smoking, nicotine dependency, negative emotions and struggle with quitting smoking, nor how patients' cancer diagnosis affects smoking behavior of their network members. Our mixed methods study will fill this gap in the evidence. We will achieve these four specific aims: Aim 1. Determine tobacco-related cancer patients' affective states, social network structures (e.g., connected to other smokers) and functions (e.g., interaction type—emotional support) and identify clusters of current-, former- and non-smokers within those networks. Aim 2. Quantify the influence of tobacco-related cancer patients' affective states, social network structures and functions, and network members' attributes (e.g., sex, smoking behavior, etc.) on patients' smoking behavior. Aim 3. Assess the impact of a patient's tobacco-related cancer diagnosis on the smoking behavior of the patient's network members (i.e., five to ten individuals the patient identifies as close social contacts). Aim 4. Explore the facilitators and barriers (e.g., affective states, encouragement to quit smoking) to smoking cessation in patients with tobacco-related cancer and their significant network member dyads. Using a prospective longitudinal design with an egocentric social network, we will collect data from newly diagnosed patients with tobacco-related cancer from a world-renowned cancer center, Dana-Farber Cancer Institute. Data from 429 patients will be collected at baseline (within 3 months of diagnosis) and then 3- , 6-, and 12-months later. We will also conduct semi-structured dyadic relationship-based qualitative interviews with a cancer patient and a self-identified significant network member to explore the depth and complexity of smoking behaviors. Our study is crucial as it will address the critical importance of affective states and social networks in smoking behavior and findings will lay the groundwork for developing and testing novel, tailored, social network-based smoking cessation interventions to better promote smoking cessation among tobacco- related cancer patients and their social network members—families, friends, and others.





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