Socioeconomic status, stress, and smoking cessation

社会经济地位、压力和戒烟

• 批准号: 8965058
• 负责人: David W Wetter
• 金额: $ 66.54万
• 依托单位: RICE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-15 至 2020-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8965058
• 关键词: Abstinence; Acute; Address; Affect; Area; Behavioral; Cellular Phone; Characteristics; Cigarette; Cohort Studies; Crime; Data; Disadvantaged; Discrimination; Ecological momentary assessment; Environment; Environmental Exposure; Environmental Risk Factor; Exposure to; Frequencies; Geographic Information Systems; Health behavior; Individual; Intervention; Lead; Life; Link; Location; Machine Learning; Maps; Measures; Mental Health; Methodology; Methods; Mining; Modeling; Motivation; Nicotine Dependence; Outcome; Participant; Pathway interactions; Patient Self-Report; Pattern; Physiological; Policies; Population; Positioning Attribute; Poverty; Predisposition; Real-Time Systems; Recommendation; Recording of previous events; Reporting; Research; Science; Self Efficacy; Severities; Smoke; Smoker; Smoking; Social Environment; Socioeconomic Status; Stress; System; Technology; Testing; Time; Tobacco; Trust; base; behavior influence; biobehavior; built environment; cohesion; computerized data processing; distress tolerance; experience; health disparity; indexing; interest; low socioeconomic status; mindfulness; novel; primary outcome; psychosocial; public health relevance; smoking cessation; social; social cognitive theory; social health determinants; stressor

 DESCRIPTION (provided by applicant): Smoking is a major cause of health disparities, and socioeconomic status (SES) is strongly associated with lower rates of smoking cessation. Several major conceptual models have been proposed that share a key, common mechanism linking SES to health behaviors such as cessation, noting that the life circumstances associated with low SES lead to greater exposure to stress, which then influences behavior. Unfortunately, the search for effective policies and interventions to reduce smoking among low SES individuals is severely hampered by the paucity of research on the mechanisms underlying cessation in this population. This longitudinal cohort study will examine the influence of SES and social history, contextual and environmental influences, biobehavioral/psychosocial predispositions, and acute momentary precipitants on stress, smoking lapse, and abstinence among 300 smokers attempting to quit. This study is guided by an overarching conceptual framework derived from models of the social determinants of health, social cognitive theories, and prior empirical findings. Participants will be assessed using real-time, field-based, state of the science methodologies consisting of Autosense, ecological momentary assessment (EMA), and geographic positioning system (GPS). Autosense tracks behavioral and physiologic data in real-time and can objectively detect when an individual smokes or encounters a stressor. GPS permits real-time spatial mapping of location patterns, which can be paired with EMA and Autosense data, and with relevant environmental exposures/characteristics (e.g., tobacco outlet exposure; area-level poverty) using geographic information system data. Principal outcomes of interest are lapse and stress ascertained in real time through Autosense, and early and long-term abstinence from smoking. This research would be the first to ever combine objective and dynamic indices of smoking lapse, stress, and key environmental influences in the study of smoking cessation. The comprehensive, multi-method approach is a major advance for the field as it eliminates problems related to an exclusive reliance on self-report for key outcomes and predictors. In addition, this is the first study to include empirically based machine learning approaches to fully mine the voluminous body of data yielded by real time assessment approaches, and to include the framework of dynamic prediction models, a novel statistical approach. The results will inform the tailoring of policies and interventions targeted at reducing the profound smoking-related disparities experienced by low SES individuals.

 描述(由申请人提供)：吸烟是造成健康差距的主要原因，社会经济地位(SES)与较低的戒烟率密切相关。已经提出了几个主要的概念性模型，它们共享一个关键的、共同的机制，将SES与戒烟等健康行为联系起来，指出与SES低相关的生活环境会导致更大的压力暴露，从而影响行为。不幸的是，在低SES人群中寻求有效的政策和干预措施来减少吸烟，严重阻碍了对这一人群中潜在戒烟机制的研究的缺乏。这项纵向队列研究将考察SES和社会历史、背景和环境影响、生物行为/心理社会倾向和急性瞬间沉淀物对300名试图戒烟的吸烟者的压力、吸烟失误和戒烟的影响。这项研究是以一个总体概念框架为指导的，该框架来源于健康的社会决定因素模型、社会认知理论和先前的经验发现。参与者将使用基于现场的实时科学方法进行评估，这些方法包括自动感知、生态瞬时评估(EMA)和地理定位系统(GPS)。Autosense实时跟踪行为和生理数据，并可以客观地检测到个人何时吸烟或遇到应激源。全球定位系统允许使用地理信息系统数据实时绘制位置模式的空间地图，这些模式可以与EMA和Autosense数据配对，并与相关的环境暴露/特征(例如，烟草销售点暴露；地区水平的贫困)配对。感兴趣的主要结果是通过Autosense实时确定错误和压力，以及早期和长期戒烟。这项研究将首次在戒烟研究中结合客观和动态的吸烟失误、压力和关键环境影响指标。综合、多方法方法是该领域的一项重大进步，因为它消除了与完全依赖自我报告获得关键成果和预测因素有关的问题。此外，这是第一次包括基于经验的机器学习方法来充分挖掘实时评估方法产生的海量数据，并包括动态预测模型的框架，这是一种新的统计方法。这一结果将为制定政策和干预措施提供参考，这些政策和干预措施旨在减少低SES个人经历的与吸烟有关的严重差距。