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Using Ecological Momentary Assessment To Characterize Dynamic Patterns of E-Cigarette Use in Adults Planning to Quit Vaping

Using Ecological Momentary Assessment To Characterize Dynamic Patterns of E-Cigarette Use in Adults Planning to Quit Vaping
使用生态瞬时评估来表征计划戒烟的成年人使用电子烟的动态模式
批准号:
10242698
负责人:
Rachel Leni Rosen
金额:
$3.77万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-09-01 至 2022-06-30

项目摘要

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中文摘要
翻译
项目摘要/摘要 据报道,美国约有1080万成年人经常使用电子烟。而电子烟 使用可能有一些潜在的戒烟帮助,它可能会导致持续的,不想要的长期使用。 尽管大多数电子烟用户计划戒除电子烟,但没有经验支持 专门为解决电子烟使用而设计的治疗资源,我们缺乏必要的关键信息来 制定有针对性的干预措施。我们将研究(1)电子烟的使用和戒烟尝试是如何在现实中展开的 时间,(2)哪些因素先于戒烟尝试(例如,戒烟的意图、渴望、电子液体的味道),以及(3)在什么时间 期间,这些因素都是相关的。目前的研究将使用生态瞬时评估(EMA), 独家每日电子烟用户报告计划在未来30天内停止蒸发,以描述动态 在这30天内电子烟的使用和戒烟尝试的模式。 符合资格的参与者包括21岁至60岁之间的人,他们报告当前(过去6个月)每天的电子邮件- 吸烟,有兴趣在未来30天内戒除电子烟,生活在美国,拥有一个智能 电话,以及否认使用香烟或FDA批准的帮助戒烟的戒烟辅助工具的人 在过去的30天里。建议的研究有两个具体目标:(1)描述电子邮件的总体模式 成年电子烟使用者有兴趣在未来30天内戒烟,包括电子烟 戒烟尝试和电子烟戒烟尝试的假定前因(例如,情绪、渴望、戒烟意图, 对戒烟能力的信心)和(2)检查电子烟之前的背景和个人层面的因素 戒烟尝试以及这些因素对近期未来戒烟提供最佳预测的时间段 尝试。 放缓的增长曲线分析将使我们能够检查背景和个人层面的因素在多大程度上 预测未来电子烟的戒烟尝试以及戒烟时间段。这件事的直接预期结果是 建议是完善该领域对电子烟使用模式的知识和以下方面的短期前因 停止使用电子烟。这项提议的长期结果是增加对目标的理解 对电子烟使用者进行干预,这将有助于开发电子烟的新疗法 停止。2018年,近5000万成年人报告使用了任何烟草产品,包括电子烟,其中 造成超过3000亿美元的与吸烟有关的疾病,并成为世界上可预防的死亡的主要原因 美国。从这项提议中获得的知识将加深业界对电子烟使用的理解,并 与戒烟相关的行为,将有助于降低与烟草相关的发病率和死亡率。
英文摘要
PROJECT SUMMARY/ABSTRACT Approximately 10.8 million adults in the United States report regular e-cigarette use (“vaping”). While e-cigarette use may have some potential as a smoking cessation aid, it may lead to continued, unwanted long-term use. Despite the fact that the majority of e-cigarette users plan to quit vaping there are no empirically supported treatment resources specifically designed to address e-cigarette use and we lack crucial information needed to develop targeted interventions. We will examine (1) how e-cigarette use – and attempts to quit – unfold in real time, (2) which factors precede quit attempts (e.g., intent to quit, cravings, e-liquid flavor), and (3) over what time period these factors are relevant. The current study will use ecological momentary assessment (EMA) with 100 exclusive daily e-cigarette users who report plans to quit vaping in the next 30 days to characterize dynamic patterns of e-cigarette use and quit attempts during that 30-day period. Eligible participants include those between the ages of 21 and 60 who report current (past 6 months) daily e- cigarette use, interest in quitting e-cigarettes within the next 30 days, live in the United States, have a smart phone, and who deny use of cigarettes or daily use of an FDA approved cessation aid to help quit e-cigarettes in the past 30 days. The proposed study has two specific aims: (1) To characterize the overall patterns of e- cigarette use in adult e-cigarette users reporting interest in quitting vaping within the next 30 days, including e- cigarette quit attempts and putative antecedents of e-cigarette quit attempts (e.g., mood, craving, intent to quit, confidence in ability to quit) and (2) To examine the contextual and person-level factors that precede e-cigarette quit attempts and the period of time over which these factors provide the best prediction of near-term future quit attempts. Moderated growth curve analyses will allow us to examine the extent to which contextual and person-level factors predict future e-cigarette quit attempts and over what time periods. An immediate expected outcome of this proposal is refinement of the field’s knowledge of e-cigarette use patterns and short-term antecedents of discontinuation of e-cigarette use. The long-term outcome of this proposal is increased understanding of targets for intervention among e-cigarette users which will aid in the development of novel treatments for e-cigarette cessation. In 2018, almost 50 million adults reported use of any tobacco product, including e-cigarettes, which is responsible for over $300 billion in smoking related illness and the leading cause of preventable death in the United States. Knowledge gained from this proposal will refine the field’s understanding of e-cigarette use and cessation-related behavior and will help reduce tobacco-related morbidity and mortality.
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