Social-Ecological Framework to Improve Youth Smoking Outcomes

描述(由申请人提供)：这项拟议的研究以社会-生态模型为指导，旨在迅速发现美国肺脏协会的Not On烟草青少年戒烟计划的有效性、覆盖范围和采用的最佳条件，该计划是美国使用最广泛的青少年戒烟计划。我们的建议充分利用了来自多个来源的现有数据，形成了一个独特的N-O-T社会生态关系数据库。关系数据库的中心是我们新形成的N-O-T主数据集，它汇总了12年(1998-2010)的N-O-T疗效和有效性试验，样本包括来自CO、FL、NC、NJ、WI和WV的N=11,000名青少年。压倒一切的研究问题是：哪些因素有利于缓和宏观经济、政治和人口状况与RE-AIM框架中确定的N-O-T有效性、覆盖范围和采用结果之间的关系？作为一个理论驱动的、具有成本效益的N-O-T计划，N-O-T因其有效性和可扩展性而获得了多个联邦模式称号。然而，项目覆盖范围是一个重大问题，数十万青少年吸烟者得不到服务。举个例子，N-O-T覆盖了西弗吉尼亚州1%的青少年吸烟者，那里的青少年吸烟率是全国最高的之一。解决这一差距需要进行研究，以确定将增强戒烟计划的覆盖范围、采用率和有效性的政策和系统战略。因此，我们建议进行一项为期3年的密集研究，旨在迅速增加N-O-T的广泛使用，从而降低美国年轻人的吸烟流行率。我们的模型建立在与烟草使用相关的经验性因素之上。应用分层线性模型和结构方程模型，从具有最具说服力的科学证据(例如烟草税、中央情报局、准入、规范和戒烟准备)开始，我们建议表征调节因素(例如烟草税、烟草价格、室内清洁空气和学校环境)对政治、经济和人口因素与N-O-T计划有效性之间的关系的影响；确定N-O-T覆盖和采用的最佳条件；并将调查结果转化为一套可以立即实施的实际行动战略，以大幅增加接受N-O-T并实现戒烟的美国青年人数。

DESCRIPTION (provided by applicant): The proposed study is guided by a Social-Ecological Model, with the goal to rapidly uncover optimal conditions for effectiveness, reach, and adoption of the American Lung Association's Not On Tobacco teen smoking cessation program, the most widely used teen cessation program in the US. Our proposal capitalizes on existing data from multiple sources, forming a unique N-O-T Social Ecological Relational Database. Central to the relational database is our newly-formed N-O-T Master Dataset that aggregates 12 years (1998-2010) of N-O-T efficacy and effectiveness trials with a heterogeneous sample of N=11,000 teens from CO, FL, NC, NJ, WI, and WV. The overriding research question is: What factors favorably moderate the relationship between macro-level economic, political, and demographic conditions and N-O-T effectiveness, reach, and adoption outcomes as identified in the RE-AIM framework? As a theory-driven, cost effective program N-O-T has received multiple federal model designations for effectiveness and scalability. Yet, program reach is a significant problem, with hundreds of thousands of teen smokers left unserved. To illustrate, N-O-T reaches <1% of teen smokers in WV, where teen smoking rates are among the nation's highest. Addressing this gap requires research to identify policy and systems strategies that will enhance the reach, adoption, and effectiveness of cessation programs. Accordingly, we propose an intensive 3-year study intended to rapidly enhance widespread N-O-T use and thereby reduce US youth smoking prevalence. Our model builds on empirically-based factors associated with tobacco use. Applying Hierarchical Linear Modeling (HLM) and Structural Equation Modeling (SEM) and beginning with moderators having the most compelling scientific evidence (e.g., tobacco tax, CIA, access, norms, and readiness to quit), we propose to characterize the effects of moderators (e.g., tobacco tax, tobacco price, clean indoor air, and school environment) on the relation between political, economic, and demographic factors and N-O-T program effectiveness; to determine optimal conditions for N-O-T reach and adoption; and to translate findings into a set of practical action strategies that can be implemented immediately to substantially increase the number of US youths who receive N-O-T and achieve cessation.