Personalized Smoking Relapse Prevention Delivered in Real-Time via Just-in-time Adaptive Interventions

项目摘要/摘要 候选人： 自2012年以来，我的研究一直得到国家药物滥用研究所(NIDA)的资助，第一 通过F31来支持我的论文工作，确定了吸烟复发的新诱因，然后 通过南卡罗来纳医科大学(MUSC)的T32[和K12]来支持我的检查工作 新的复发预防方法。我的研究通过(地方和国家)奖项得到了认可 以及在影响力较大的期刊上发表文章。我很高兴能在我的职业发展中迈出下一步， K23支持我将能够从事研究和培训经验，我需要成为一名 及时适应干预(JITAI)的新兴领域，并率先在成瘾领域使用它们。 职业发展计划：职业发展活动建立在我的临床心理学培训和12年的基础上 多年专注于成瘾的临床研究经验。K23的培训目标是发展知识， 为成为预防复发领域的领导者所必需的技能和合作，重点是日本国际刑警组织。 培训将通过参加科学会议、方法研讨会、课程作业和 [马修·卡彭特博士、迈克尔·卡明斯博士、大卫·古斯塔夫森博士、安德鲁·劳森博士、 迈克尔·萨拉丁和托马斯·基什内尔，所有这些都将有助于我在]方面的专业知识的发展： 1)烟草控制，2)通过移动健康技术实现的精准医疗，3)生态瞬时评估(EMA)， 4)地理空间统计，5)与联合技术援助和复发有关的预测性分析，以及6)赠款书写。这些 经验将确保实现研究目标，我将准备过渡到研究独立。 [研究计划：我们将测试、改进(目标1)和试点测试(目标2)一个个性化的吉泰，旨在指导 实时提供快速有效的尼古丁替代疗法(NRT；含片)，以防止吸烟复发。 三轮Beta测试(每轮10名参与者)的反馈将指导之前的干预改进 它在小规模随机对照试验(RCT)中进行测试，从而确保可用性、功能性 可接受性和技术可行性]。具体地说，智能手机应用程序(APP)，将集成退出前 吸烟数据和通过全球定位系统(GPS)捕获的客观位置数据，以确定复发风险 (热点)算法。在退出尝试期间，启用GPS的应用程序(MyQuit)将检测热点附近的情况，并 提供NRT提示，所有提示都将在曝光前自动发生。因此，MyQuit将优化NRT 用来防止已知的破坏持续禁欲的暗示引发的渴望，从而改变这一目的 循证戒毒药物促进复发预防。MyQuit将根据标准进行测试 CARE(NRT，附简要说明)。MyQuit的两个版本将进行测试，这两个版本只会在热点方面有所不同 算法是从退出尝试(MyQuit-Recall)开始时调用的位置追溯而来的 基于实时EMA完成的预退出(MyQuit+)。我们无权检查临床疗效[(N=75)]， 但结果将提供初步数据来估计效应大小，并支持R01提交的完全 这些创新方法的动力第二阶段疗效试验。我们假设效应的大小将建议更好 与标准护理相比，两种MyQuit条件下的结果(1周、1个月、3个月禁欲)。我们也 预计MyQuit+会比MyQuit-Recall表现更好，但同时测试两者，因为它们都提供了独特的覆盖潜力。 MyQuit-Recall将推进前吸烟者可用的复发预防工具的有限证据基础。 导师团队：所有5名导师都有外部资助(3名有中心拨款)，总共有900多名导师 出版并指导3000名获奖者。合作每年将产生3-4份同行评审的出版物。 环境与机构承诺：南加州大学的研究环境、设施和资源 非常适合在成瘾研究中指导职业发展。丰富的培训活动包括 可在整个校园内使用(研讨会/研讨会)，30多名教职员工参与了成瘾研究 训练。我将在成瘾科学部担任助理教授，开展K23活动 精神病学和行为科学系。美国许多杰出的成瘾研究人员都是 该部门的成员，包括NIH资助最高的精神病学研究人员。2014财年，该部门 在美国国立卫生研究院精神科研究经费中排名第八。 结论：通过技术加速复发预防方面的进展是至关重要的。 吸烟仍然是全球可预防死亡的主要原因，95%的戒烟尝试都失败了。高 复发率的部分原因是环境因素和NRT的不当使用。MyQuit通过引导将两者最小化 NRT在预期触发器中的使用。与传统干预措施相比，量身定做(具体)和动态(在 -此刻)干预可能会提高有效性。个性化的JITAI为受益提供了巨大的希望 公共卫生，并可被用于治疗广泛的成瘾问题。移动健康技术的使用 提供具体和实时的治疗符合NIDA的战略计划和NIH支持的 精准医学计划。K23指导的职业发展将支持我向独立的过渡，以及 使我成为治疗成瘾的新方法和新方法(即联合戒毒)方面的专家。

PROJECT SUMMARY/ABSTRACT Candidate: My research has been funded by the National Institute of Drug Abuse (NIDA) since 2012, first through a F31 to support my dissertation work that identified novel precipitants of smoking relapse, and then through a T32 [and K12] at the Medical University of South Carolina (MUSC) to support my work examining novel relapse prevention approaches. My research has been recognized through awards (locally and nationally) and publications in high-impact journals. I am excited to take the next step in my career development, and with K23 support I will be able to engage in the research and training experiences I need to become an expert in the emerging area of just-in-time-adaptive interventions (JITAIs) and pioneer their use in the addiction field. Career Development Plan: Career development activities build upon my clinical psychology training and twelve years of addiction-focused clinical research experience. K23 training objectives are to develop the knowledge, skills, and collaborations necessary to become a leader in the field of relapse prevention, with a focus on JITAIs. Training will be obtained through participation in scientific conferences, methods workshops, coursework, and [structured mentorship from Drs. Matthew Carpenter, Michael Cummings, David Gustafson, Andrew Lawson, Michael Saladin, and Thomas Kirchner, all of which will contribute towards the development of my expertise in]: 1) tobacco control, 2) precision medicine via mHealth technologies, 3) ecological momentary assessment (EMA), 4) geospatial statistics, 5) predictive analytics relevant to JITAIs and relapse, and 6) grant writing. These experiences will ensure research aims are met, and I will be prepared to transition to research independence. [Research Plan: We will beta test, refine (Aim 1), and pilot test (Aim 2) a personalized JITAI designed to guide delivery of fast acting nicotine replacement therapy (NRT; lozenge) in real-time, to prevent smoking relapse. Feedback from three rounds of beta testing (10 participants per round) will guide intervention refinement before it is tested in a small-scale randomized controlled trial (RCT), thereby ensuring usability, functionality, acceptability, and technical feasibility]. Specifically, a smartphone application (app), will integrate pre-quit smoking data with objective location data captured via global positioning system (GPS) to establish relapse risk (hotspot) algorithms. During a quit attempt, the GPS-enabled app (MyQuit) will detect proximity to hotspots and deliver NRT prompts, all of which will occur automatically and prior to exposure. Thus, MyQuit will optimize NRT use to prevent cue-provoked cravings known to undermine sustained abstinence, thereby repurposing this evidence-based cessation medication to promote relapse prevention. MyQuit will be tested against standard care (NRT with brief instructions). Two versions of MyQuit will be tested, which will differ only in how hotspot algorithms are derived: retrospectively from locations recalled at the onset of a quit attempt (MyQuit-Recall) or based on real-time EMA completed pre-quit (MyQuit+). We are not powered to examine clinical efficacy [(N=75)], but results will provide preliminary data to estimate effect sizes, and support a R01 submission, for a fully powered Stage II efficacy trial of these innovative approaches. We hypothesize effect sizes will suggest better outcomes (1 week, 1 month, 3 month abstinence) in both MyQuit conditions relative to standard care. We also expect MyQuit+ will outperform MyQuit-Recall, but test both because they each offer unique reach potential. MyQuit-Recall will advance the limited evidence-base for relapse prevention tools available to former smokers. Mentorship Team: All 5 mentors have external funding (3 with center grants), and collectively have over 900 publications and mentored 3 K awardees. Collaborations will result in 3-4 peer-reviewed publications per year. Environment and Institutional Commitment: The research environment, facilities, and resources at the MUSC are ideally suited for mentored career development in addiction research. An abundance of training activities are available across campus (workshops/seminars), and over 30 faculty are involved with addiction research training. I will carry out K23 activities as an Assistant Professor in the Addiction Sciences Division, within the Department of Psychiatry and Behavioral Sciences. Many of the nation's preeminent addiction researchers are members of the department, including NIH's highest funded psychiatric researcher. In FY2014 the department was ranked 8th in NIH research funding among domestic psychiatry departments. Conclusions: The need to accelerate advances in relapse prevention through technology is paramount. Smoking remains the leading cause of preventable death worldwide, and 95% of cessation attempts fail. High relapse rates are, in part, due to environmental triggers and improper NRT use. MyQuit minimizes both by guiding NRT use in anticipation of triggers. Compared to traditional interventions, tailored (idiographic) and dynamic (in- the-moment) interventions may improve effectiveness. Personalized JITAIs offer great promise for benefiting public health, and could be adopted to treat a wide range of addictive problems. The use of mHealth technology to provide idiographic and real-time treatment is consistent with NIDA's Strategic Plan and the NIH-supported Precision Medicine Initiative. K23 mentored career development will support my transition to independence, and position me to become an expert in emerging and novel approaches to addiction treatment (i.e., JITAIs).