Neuroimaging approaches to improve prediction of smoking initiation and nicotine use escalation among young adult electronic nicotine delivery systems users

项目总结/摘要 建议的职业发展申请为Jiaying Liu博士提供研究培训， 过渡到独立。这项研究的目的是确定尼古丁的神经行为标志物 年轻成人（YA）电子尼古丁输送使用者中的使用升级和吸烟开始 系统（ENDS）。预计调查结果将为监管政策提供信息，并提高YA对公众的响应能力 卫生宣传运动。鉴于越来越多的证据表明，ENDS的使用传达了5倍的额外 开始吸烟和其他烟草使用升级的风险，最近YA使用的增加令人震惊， 这可能会导致依赖性的重新抬头，从而逆转数十年来烟草控制的成功。因此有 关键是要确定吸烟开始和烟草使用升级的预测标志物， 人口，并提供可采取行动的证据，为监管和预防工作提供信息。功能 磁共振成像（fMRI）产生的信息是对传统行为风险的补充 评估，直接观察的神经基板的基础，已知的主观状态， 使成瘾永久化，以便产生客观和更准确的预测措施。评估 提出了与吸烟开始和烟草使用升级相关的行为和脑标记物。目标 是确定基线神经行为标志物是否能预测吸烟过渡和烟草使用 在3个月、6个月、9个月和12个月时，升级超过传统制造商。为期一年的公益广告（PSA） 还将进行交叉设计的干预，其中两个消息暴露命令和一个 控制条件允许测试新型抗ENDS PSA是否解决与ENDS风味相关的伤害 与现有的常规公益广告相比，将更有效地防止烟草使用的增加。拟议 研究是第一个旨在为调味ENDS营销提供信息的监管，并提供 为预防运动制定有效的公益广告的建议。这些目标直接针对 FDA烟草产品中心的多个优先事项（营销影响、沟通、行为和 成瘾），他们预计将确定有效的监管大门，以解决目前的ENDS流行。 博士刘的长期目标是成为一名独立的研究人员， 研究监管行动，以改善健康运动和干预措施，利用有说服力的 反烟草信息。她的近期目标是准备一个有竞争力的R 01应用程序， PSA的随机对照试验，以最大限度地发挥对吸烟和物质使用的威慑作用 用户之间的过渡。拟议的培训经验旨在培养以下方面的能力： 神经科学，（B）功能性神经成像，（c）烟草监管科学，和（d）资助写作。拟议 研究为培训和初步数据提供重点，以支持竞争性R 01应用。

PROJECT SUMMARY/ABSTRACT The proposed career development application provides research training for Dr. Jiaying Liu to facilitate her transition to independence. The goal of the proposed research is to identify neurobehavioral makers of nicotine use escalation and cigarette smoking initiation among young adult (YA) users of electronic nicotine delivery systems (ENDS). Findings are expected to inform regulatory policy and improve YA responsiveness to public health campaign communications. Given the accumulating evidence that ENDS use conveys 5-fold additional risk for smoking initiation and other tobacco use escalation, recent YA increases in use are alarming, threatening a resurgence of dependence that may reverse decades of tobacco control success. Therefore, it is crucial to identify predictive markers of smoking initiation and tobacco use escalation in this vulnerable population, and to provide actionable evidence that informs regulatory and prevention efforts. Functional magnetic resonance imaging (fMRI) generates information complementary to traditional behavioral risk assessments, with direct observations of the neural substrates that underlie the subjective states known to perpetuate addiction, in order to yield objective and putatively more predictive measures. Assessment of behavioral and brain markers associated with smoking onset and tobacco use escalation is proposed. The goal is to determine whether baseline neurobehavioral markers will predict smoking transition and tobacco use escalation beyond traditional makers at 3, 6, 9 and 12 months. A one-year public service announcement (PSA) intervention with a cross-over design will also be conducted, in which two message exposure orders and one control condition allow testing whether novel anti-ENDS PSAs addressing harms associated with ENDS flavors will more effectively prevent tobacco use escalation compared to the existing regular PSAs. The proposed research is among the first that aims to inform regulation of flavored ENDS marketing, and to provide recommendations for developing effective PSAs for prevention campaigns. These aims directly address multiple priorities of FDA Center for Tobacco Products (Marketing Influences, Communications, Behavior and Addiction), and they are expected to pinpoint effective regulatory gates to address the current ENDS epidemic. Dr. Liu’s long-term goal is to become an independent researcher translating communication neuroscience research to regulatory actions for improvements in health campaigns and interventions utilizing persuasive anti-tobacco messaging. Her near-term goal is to prepare a competitive R01 application to implement randomized controlled trials of PSAs to maximize impact on deterrence of smoking and substance use transition among ENDS users. The proposed training experience is designed to develop competencies in (a) neuroscience, (b) functional neuroimaging, (c) tobacco regulatory science, and (d) grant writing. The proposed research study provides focus for training and preliminary data to support a competitive R01 application.