Developing Methodology to examine causal mediation of Time-Varying Effects in Smoking Cessation Treatments

开发方法来检查戒烟治疗中时变效应的因果调节

• 批准号: 9754035
• 负责人: Donna Lynn Coffman
• 金额: $ 31.98万
• 依托单位: TEMPLE UNIV OF THE COMMONWEALTH
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9754035
• 关键词: Address; Affect; Behavior; Behavior Therapy; Behavioral; Behavioral Mechanisms; Cerebrovascular Disorders; Cessation of life; Computer software; Coronary heart disease; Data; Development; Diabetes Mellitus; Ecological momentary assessment; Educational workshop; Enrollment; Event; Health; Health behavior; Individual; Intervention; Intervention Studies; Knowledge; Maintenance; Malignant Neoplasms; Malignant neoplasm of lung; Measurement; Mediating; Mediation; Mediator of activation protein; Medical; Methodology; Methods; Modeling; Moods; Outcome; Pharmaceutical Preparations; Pharmacotherapy; Physical activity; Process; Publications; Randomized; Randomized Controlled Trials; Research; Research Personnel; Risk Factors; Smoke; Smoking; Smoking Behavior; Smoking Cessation Intervention; Statistical Methods; Technology Assessment; Testing; Time; Time Study; Tobacco use; Work; base; behavior change; behavioral health intervention; cost effective; craving; design; effective intervention; improved; journal article; nicotine patch; nicotine replacement; pedometer; physical inactivity; public health intervention; smoking abstinence; smoking cessation; symposium; tool; treatment response; user friendly software; varenicline

This project will examine new methods for understanding time-varying causal mediation effects in smoking cessation interventions. Mediation occurs when an independent variable (e.g., smoking cessation intervention) has an effect on an outcome (e.g., smoking abstinence) through a third variable (e.g., reduction in craving). In other words, we will develop new ways to understand the mechanisms by which smoking cessation interventions cause changes in people's smoking behavior, and how these effects vary over time. Understanding how interventions have their effect is key to designing more powerful, efficient interventions. To improve smoking cessation interventions, this proposal focuses on improving methods for the understanding of how people stop smoking and continue to abstain from smoking following a smoking cessation intervention. More broadly, the methods that we propose to develop will help us understand what causes behavioral interventions to affect people's engagement in and maintenance of healthy behaviors. We will develop and extend methods for analyzing intensive longitudinal data and conducting mediation analysis to better study time-varying effects, which refer to effects of one variable on another that change (i.e., strengthen or diminish) over time. We will extend methods, based on the potential outcomes framework for causal inference, to draw more valid causal inferences about time-varying effects in mediation and then apply these methods to two smoking cessation intervention studies. First, we will use ecological momentary assessment (EMA) data that asked people about their craving, mood, and smoking abstinence while they were enrolled in a randomized controlled trial of combination nicotine replacement therapy, the nicotine patch alone, and varenicline to develop mediation models in which the effect of the various study drugs on smoking abstinence is mediated by cravings or mood. These effects may vary over time. For example, a study drug may be very effective at reducing cravings shortly after the quit day, but the effect may weaken over time. Second, using data from pedometers, we will assess the effect of a physical activity/ smoking cessation intervention on daily step count and whether increases in daily step counts in turn have an effect on smoking cessation. We will disseminate the methods we develop in user-friendly software (e.g., R packages), journal articles, and conference presentations and workshops that are accessible to behavioral intervention researchers. Methods and findings will ultimately allow researchers to understand how their interventions work. With this knowledge, they will be able to design more efficacious and cost-effective interventions for smoking cessation by targeting the most relevant mediator(s) at the most relevant time.

该项目将检查新方法，以了解吸烟时变化的因果关系效应 停止干预措施。当独立变量（例如，戒烟干预）时发生调解 通过第三个变量（例如，渴望减少）对结果（例如，戒烟）产生影响。在 换句话说，我们将开发新的方法来了解戒烟的机制 干预措施会导致人们的吸烟行为发生变化，以及这些影响如何随着时间而变化。 了解干预措施的作用是设计更强大，有效的干预措施的关键。到 改善戒烟干预措施，该提案着重于改进理解的方法 人们如何停止吸烟，并在戒烟干预后继续戒烟。 更广泛地，我们建议开发的方法将有助于我们了解导致行为的原因 影响人们参与和维持健康行为的干预措施。 我们将开发和扩展用于分析密集纵向数据和进行调解的方法 分析以更好地研究时变效应，这是指一个变量对另一个变化的影响（即 随着时间的流逝，加强或减少）。我们将根据潜在结果框架扩展方法 因果推断，以提出有关调解时变化效应的更有效的因果推断，然后应用 这些方法是两项戒烟干预研究。首先，我们将使用生态瞬间 评估（EMA）数据，询问人们在他们的渴望，情绪和戒烟时 参加了尼古丁替代疗法的随机对照试验，仅尼古丁斑块， 以及开发调解模型的变元线，其中各种研究药物对吸烟的影响 禁欲是由渴望或情绪介导的。这些影响可能会随着时间而变化。例如，研究药物 退出一天后不久，可能会非常有效地减少渴望，但是随着时间的流逝，效果可能会减弱。 其次，使用来自计步器的数据，我们将评估体育锻炼/戒烟的效果 每日步骤计数的干预以及每日步数的增加是否反过来对吸烟产生影响 停止。我们将传播我们在用户友好的软件（例如R软件包）中开发的方法，日记 行为干预可以访问的文章，会议演讲和研讨会 研究人员。方法和发现最终将使研究人员能够了解其干预措施的工作方式。 有了这些知识，他们将能够为吸烟设计更有效和成本效益的干预措施 在最相关的时间以最相关的调解人为目标来停止。