Person-specific dynamic networks of nicotine withdrawal: implications for smoking cessation

尼古丁戒断的个体动态网络：对戒烟的影响

• 批准号: 10427293
• 负责人: David Martin Lydon
• 金额: $ 16.15万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10427293
• 关键词: Address; Anxiety; Coupling; Data; Data Analyses; Data Collection; Development; Ecological momentary assessment; Equation; Failure; Future; Goals; Heterogeneity; Individual; Influentials; Interdisciplinary Study; Intervention; Knowledge; Literature; Mathematics; Measurement; Measures; Mentors; Methods; Modeling; Morbidity - disease rate; Nicotine Withdrawal; Participant; Pattern; Persons; Predictive Value; Psychology; Psychopathology; Relapse; Reporting; Research; Research Project Grants; Risk Factors; Role; Sampling; Satiation; Science; Smoker; Smoking; Smoking Cessation Intervention; Structure; Symptoms; Techniques; Technology; Testing; Theory of Change; Time; Training; Withdrawal; Withdrawal Symptom; Work; addiction; behavior change; career; cigarette smoking; density; design; experience; feasibility testing; graph theory; indexing; mortality; negative affect; novel; personalized medicine; reuptake; skills; sleep difficulty; smoking abstinence; smoking cessation; smoking intervention; smoking relapse; theories; tool

PROJECT SUMMARY The overall aim of this K01 submission is to provide Dr. David Lydon with the knowledge and skills to achieve his long-term goal of establishing an independent research career that will inform cigarette-smoking cessation interventions. Cigarette-smoking remains a leading cause of morbidity and mortality worldwide. Upon smoking cessation, withdrawal symptoms emerge that are primary determinants of smoking reuptake. The majority of intervention-guided cessation attempts fail, despite showing the ability to target withdrawal symptoms. This proposal consists of a training and research plan that will lead to the development and testing of a novel, network conceptualization of smoking withdrawal that focuses on person-specific patterns of moment-to-moment interplay among withdrawal symptoms. The proposed training plan under the guidance of Dr. Danielle Bassett (Mentor), Dr. Emily Falk (Co-Mentor), Dr. Robert Schnoll (Co-Mentor), Dr. Ian Barnett (Consultant), and Dr. Michael Rovine (Consultant) will build on Dr. Lydon's training to date, leading to the acquisition of expertise in 1) network science analysis of ecological momentary assessment data, 2) the science of behavior change in addiction , and 3) the use of ecological momentary assessment in behavior-change interventions. The proposed research project entails an ecological momentary assessment study during which smokers (n=250) will undergo 2 counterbalanced ecological momentary assessment bursts during which they will report on the intensity of withdrawal symptoms multiple times a day for 10 days. Smokers will undergo one burst while smoking as usual and one burst while abstaining from smoking. In Aim 1, withdrawal experiences will be modeled as person- specific, dynamic networks that indicate the interplay among symptoms across time. Graph theory will be applied to the constructed networks to demonstrate the ability to combine a dynamic network perspective of withdrawal and network science techniques to identify person-specific leverage points for intervention in the form of individual withdrawal symptoms that exert the most effects on other withdrawal symptoms. Aim 2 will test the extent to which self-perpetuating symptom networks act as a risk factor for smoking cessation failure. Aim 3 will examine changes in withdrawal symptom networks across levels of smoking satiety to test the feasibility of using pre-cessation experience-sampling data to tailor smoking cessation interventions. The unique project capitalizes on a multidisciplinary research team to develop a novel perspective of withdrawal that will culminate in an R01 submission to examine the use of person-specific withdrawal networks as smoking intervention tools. The project will provide Dr. Lydon with skills necessary to become a leader in research on the coupling of sophisticated graph theory techniques, ecological momentary assessment data, and behavior change theories to inform the personalization of smoking cessation interventions.

项目摘要 本次K 01提交的总体目标是为大卫莱登博士提供知识和技能， 他的长期目标是建立一个独立的研究生涯，将告知戒烟 干预措施。吸烟仍然是全世界发病率和死亡率的主要原因。抽吸后 戒烟后，出现戒断症状，这是吸烟再吸收的主要决定因素。大多数 干预引导的戒烟尝试失败，尽管显示出针对戒断症状的能力。这 该提案包括一项培训和研究计划，将导致开发和测试一个新的网络， 戒烟的概念化，重点是个人特定的模式的时刻到时刻 戒断症状之间的相互作用。Danielle Bassett博士指导下的拟议培训计划 （导师），艾米丽福尔克博士（共同导师），罗伯特施诺尔博士（共同导师），伊恩巴内特博士（顾问）， 和dr. Michael Rovine（顾问） Lydon博士迄今为止的培训，导致获得专业知识1） 生态瞬时评估数据的网络科学分析，2） 行为改变的科学 成瘾 3）在行为改变干预中使用生态瞬时评估。拟议 研究项目需要进行一项生态瞬时评估研究，在此期间，吸烟者（n=250）将接受 2次平衡生态瞬时评估突发，期间将报告 戒断症状，每天多次，持续10天。吸烟者在正常吸烟时会经历一次爆发 还有一个在戒烟时爆了在目标1中，戒断体验将被建模为人- 特定的、动态的网络，表明症状之间的相互作用。将应用图论 构建的网络，以证明有能力联合收割机的动态网络的角度撤出 和网络科学技术，以确定个人特定的杠杆点， 对其他戒断症状影响最大的个体戒断症状。目标2将测试 自我延续的症状网络作为戒烟失败的风险因素的程度。目标3将 检查不同吸烟饱腹感水平的戒断症状网络的变化，以测试使用 戒烟前经验----抽样数据，以定制戒烟干预措施。独一无二的项目 在一个多学科的研究小组，以开发一个新的角度撤出，将最终在R 01 研究使用个人特定戒断网络作为吸烟干预工具的意见书。项目 将为莱登博士提供必要的技能，成为一个领导者的研究耦合复杂的 图论技术，生态瞬时评估数据和行为改变理论，以告知 个性化戒烟干预。