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（由适用提供）：吸烟是造成健康差异的主要原因，社会经济地位（SES）与较低的戒烟率密切相关。已经提出了几种主要的概念模型，它们共享一种关键的，共同的机制，将SES与戒烟等健康行为联系起来，并指出与SES低相关的生活环境会导致更大的压力，从而影响行为。不幸的是，由于缺乏研究该人群中停止的机制的研究，寻找有效的政策和干预措施以减少低SES人群的吸烟。这项纵向队列研究将研究SES和社会历史，情境和环境影响，生物行为/社会心理倾向以及300名试图退出的烟民的压力，吸烟失误以及戒酒者对压力，吸烟失误以及戒酒的急性降水剂的影响。这项研究的指导是由健康，社会认知理论和先前的经验发现的社会决定者的模型得出的总体概念框架的指导。参与者将使用由自动志，生态瞬时评估（EMA）和地理定位系统（GPS）组成的实时，基于现场的科学方法进行评估。 AutoSense实时跟踪行为和生理数据，可以客观地检测单个烟熏或遇到压力源。 GPS允许对位置模式进行实时空间映射，可以与EMA和自动固定数据配对，并使用地理信息系统数据与相关的环境暴露/特征（例如，烟草出口暴露；区域水平贫困）。感兴趣的主要结果是通过自动张开的，以及早期和长期戒烟的实时确定。这项研究将是有史以来第一个结合吸烟，压力和关键环境影响的目标和动态指标。全面的多方法方法是该领域的重大进步，因为它消除了与关键结果和预测因素的自我报告相关的问题。此外，这是首次包括迫切基于机器学习方法的研究，以完全挖掘实时评估方法产生的大量数据，并包括一种动态预测模型的框架，这是一种新型的统计方法。结果将为您的政策和干预措施的裁缝提供信息，该政策和干预措施旨在减少低SES个人经历的与吸烟相关的分布。