Social-Ecological Framework to Improve Youth Smoking Outcomes

描述（由申请人提供）：拟议的研究由社会生态模型指导，目标是快速发现美国肺脏协会的非烟草青少年戒烟计划（美国最广泛使用的青少年戒烟计划）的有效性、覆盖范围和采用的最佳条件。我们的建议利用现有的数据从多个来源，形成一个独特的N-O-T社会生态关系数据库。关系数据库的核心是我们新形成的N-O-T主数据集，该数据集汇总了12年（1998-2010）的N-O-T疗效和有效性试验，样本来自CO，FL，NC，NJ，WI和WV，样本数为N= 11，000名青少年。压倒一切的研究问题是：什么因素有利于缓和宏观层面的经济，政治和人口条件和N-O-T的有效性，覆盖面和采用结果之间的关系确定在RE-AIM框架？作为一个理论驱动的，成本有效的计划N-O-T已收到多个联邦模型指定的有效性和可扩展性。然而，该计划的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。举例来说，N-O-T在西弗吉尼亚州的青少年吸烟者中占不到1%，那里的青少年吸烟率是全国最高的。解决这一差距需要研究，以确定政策和系统战略，将提高戒烟计划的覆盖面，采用率和有效性。因此，我们建议进行一项为期3年的密集研究，旨在迅速提高广泛的N-O-T使用，从而降低美国青少年吸烟率。我们的模型建立在与烟草使用相关的基于药物的因素上。应用分层线性模型（HLM）和结构方程模型（SEM），并从具有最令人信服的科学证据（例如，烟草税，中情局，访问，规范，并准备戒烟），我们建议表征的影响主持人（例如，烟草税、烟草价格、清洁的室内空气和学校环境），研究政治、经济和人口因素与N-O-T计划有效性之间的关系;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策略，以大幅增加接受N-O-T并实现戒烟的美国青少年数量。

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.