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.
