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

项目总结 此K01意见书的总体目标是为David Lydon博士提供实现以下目标的知识和技能 他的长期目标是建立一个独立的研究生涯，为戒烟提供信息 干预措施。吸烟仍然是全世界发病率和死亡率的主要原因。在吸烟之后 戒烟、戒断症状的出现是吸烟重新上瘾的主要决定因素。大多数人 尽管有能力针对戒断症状，但干预引导的戒断尝试失败了。这 提案包括一项培训和研究计划，该计划将导致开发和测试一个新的、 戒烟的概念化，侧重于个人特定的时刻到时刻的模式 戒断症状之间的相互作用。丹妮尔·巴西特博士指导下的拟议培训计划 (导师)，Emily Falk博士(共同导师)，Robert Schnoll博士(共同导师)，Ian Barnett博士(顾问)， 和Dr。 迈克尔·罗文(顾问) 将以莱顿博士迄今的培训为基础，导致在1) 生态瞬时评价数据的网络科学分析，2) 关于行为变化的科学 上瘾 3)在行为改变干预中使用生态瞬时评估。建议数 研究项目需要一项生态瞬时评估研究，在此期间吸烟者(n=250)将接受 2个平衡的生态瞬间评估突发事件，在此期间，他们将报告 连续10天每天多次出现戒断症状。吸烟者在像往常一样吸烟时会经历一次爆发 还有一例是在戒烟时爆裂的。在目标1中，戒断体验将被建模为人- 特定的、动态的网络，表明症状之间随时间的相互作用。将应用图论 以展示所构建的网络结合动态网络撤退的能力 和网络科学技术，以确定针对特定人的杠杆点进行干预 对其他戒断症状影响最大的个体戒断症状。目标2将测试 自我延续症状网络在多大程度上是戒烟失败的风险因素。目标3将 检查戒烟症状网络在不同程度的吸烟饱腹感中的变化，以测试使用 戒烟前体验-抽样数据以量身定做戒烟干预措施。这个独特的项目充分利用了 关于一个多学科研究团队，以开发一种新的撤退视角，最终将在R01 提交意见书，审查特定人戒烟网络作为吸烟干预工具的使用。该项目 将为莱登博士提供必要的技能，使其成为研究复杂的 图论技术、生态瞬时评估数据和行为变化理论为 戒烟干预的个人化。

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.