Longitudinal mixed method investigation of social networks and affective states as determinants of smoking behavior among cancer patient

项目总结 吸烟导致至少12种癌症，占美国所有癌症死亡人数的30% 各州。戒烟是保护癌症患者远离吸烟的唯一最有效的方法 并发症，延长存活期，并确保最佳的健康结果。尽管对健康有不利影响，10%- 癌症患者中，根据癌症类型的不同，会继续吸烟。癌症的诊断在情感上令人震惊 经验和患者经常使用烟草来调节负面情绪。吸烟率是最高的 在长期吸烟史、高尼古丁成瘾和吸烟相关癌症患者中 戒烟有困难。即使在戒烟后，他们也会复发，因为停止吸烟会导致负面影响 情绪，进而影响吸烟行为。吸烟行为根植于个人的情感之中 利基和社交网络，并受网络中个人行为的影响。然而，到目前为止，没有 社会网络和情感状态如何影响患者的吸烟行为受到了关注 吸烟、尼古丁依赖、消极情绪和挣扎的高吸烟率的烟草相关癌症患者 戒烟，也不知道患者的癌症诊断如何影响其网络成员的吸烟行为。 我们的混合方法研究将填补证据中的这一空白。我们将实现这四个具体目标：目标1。 确定与烟草相关的癌症患者的情感状态、社交网络结构(例如，与其他 吸烟者)和功能(例如，互动类型-情感支持)，并识别当前、以前和 这些网络中的非吸烟者。目的2.量化烟草相关癌症患者情绪的影响 状态、社交网络结构和功能以及网络成员的属性(例如，性，吸烟行为， 等)对病人吸烟行为的影响。目的3.评估患者与烟草相关的癌症诊断的影响 关于患者网络成员的吸烟行为(即患者识别的五到十个人 密切的社会联系)。目标4.探索促进者和障碍(例如，情感状态、鼓励戒烟 烟草相关癌症患者及其重要网络成员的戒烟 双子星。使用带有自我中心社交网络的前瞻性纵向设计，我们将从以下方面收集数据 来自世界著名癌症中心Dana-Farber的新诊断的烟草相关癌症患者 癌症研究所。429名患者的数据将在基线(诊断后3个月内)收集，然后3- 、6个月和12个月后。我们还将进行半结构化的基于关系的二元关系定性访谈 与一名癌症患者和一名自认为重要的网络成员一起探索 吸烟行为。我们的研究是至关重要的，因为它将解决情感状态和社交的关键重要性 吸烟行为网络和研究结果将为开发和测试新的、量身定做的、 基于社交网络的戒烟干预措施，以更好地在烟草中促进戒烟- 相关癌症患者及其社交网络成员--家人、朋友和其他人。

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.