Construal level as a novel pathway for affect regulation and cancer control

7.项目总结/摘要 在美国，肺癌是可预防死亡的主要原因，吸烟是一个重要因素。 在80%-90%的病例中，肺癌的发病率为100%。尽管成年人吸烟率有所下降， 在过去的50年里，在某些群体中，如生活在 贫穷。戒烟是困难的：一个给定的戒烟尝试结果停止在不到10%的情况下，大多数 成年吸烟者曾多次尝试戒烟，但都失败了。目前迫切需要的是 新的干预戒烟，通过不同的机制运作，从那些 现有的干预措施针对的是长期吸烟者，这些干预措施可能不成功。的屏障 进展的一个重要原因是，大多数治疗的作用机制尚不清楚，这使得人们很难了解 哪种治疗方法对谁最有效我们转向情感科学，以确定一个候选技术， 可以作为一个新的干预的基础。关于情感调节的研究通常集中在下- 调节情感状态，如对香烟的渴望，使用有效的策略，如认知 重新评估然而，情感调节的一个新见解是，人们可以理解，或者说主观地理解， 事件具有不同的抽象级别，并且将与健康相关的行为分为高级别和低级别 术语在几个领域促进健康行为。例如，想要戒烟的吸烟者更有可能 当它们经历相同的事件时抵制香烟（例如，“禁欲”）更抽象，更高层次的术语 (e.g.,“成为一个更好的我”）与更具体、更低级的术语（例如，“不抽这支烟”）。那里 有证据表明，高水平联想可能依赖于与传统情感调节不同机制 和减少吸烟的干预措施，但其作用机制尚不清楚。直接比较其 机制的替代影响监管战略和开发工具，以诱导高水平的 结论是开发新干预方法的下一步。此外，建立个人 高水平接触影响的差异将使未来的干预措施有针对性地针对个人 对谁最有效。我们确定了两个候选机制， Conventional可能起作用：渴望的下调和目标的上调（即，动力去 退出）。功能性磁共振成像（fMRI）揭示了参与这些过程的神经系统 要与众不同。因此，我们将使用功能磁共振成像数据的多变量分析来量化高水平联想的相似性， 每个候选人（目标1）。这将在具有4种条件的纵向平移实验中完成：高- 水平依赖，渴望的下调，目标的上调，和治疗照常-在一个 贫困的持续吸烟者的样本，他们最有可能从一种新颖的，基于理论的 治疗样本量（N = 240）提供了高水平的影响的个体差异的检查 与神经活动和渴望相关，以及它们预测吸烟减少的程度（目标2）。

7. Project Summary/Abstract Lung cancer is the leading major cause of preventable death in the United States, and cigarette smoking is a contributor to lung cancer in 80%–90% of cases. Though adult cigarette smoking rates have declined substantially during the past 50 years, they remain as high as 30% in certain groups, such as individuals living in poverty. Quitting is difficult: a given quit attempt results in cessation in fewer than 10% of cases, and most adult cigarette smokers have attempted and failed to quit, and often many times. What is urgently needed are novel interventions for cigarette smoking cessation that operate through different mechanisms from those targeted by existing interventions, which are likely to have been unsuccessful for persistent smokers. A barrier to progress is that the mechanisms of action of most treatments are not known, which makes it difficult to know which treatment will work best for whom. We turn to affective science to identify a candidate technique that could serve as the basis for a novel intervention. Research on affect regulation typically focuses on down- regulation of affective states, such as craving for cigarettes, using effortful strategies such as cognitive reappraisal. However, a new insight in affect regulation is that people can construe, or subjectively understand, events with varying levels of abstraction, and that construing health-related behaviors in high- versus low-level terms promotes health behavior in several domains. For example, smokers who want to quit are more likely to resist a cigarette when they construe the same event (e.g., “abstinence”) in more abstract, high-level terms (e.g., “becoming a better me”) versus more concrete, low-level terms (e.g., “not smoking this cigarette”). There is some evidence that high-level construal might rely on distinct mechanisms from traditional affect regulation and smoking reduction interventions, but its mechanisms of action are unknown. Directly comparing its mechanisms to those of alternative affect regulation strategies and developing tools to induce high-level construal are the next steps on the path toward developing a novel intervention. Also, establishing individual differences in the effects of high-level construal will allow future interventions to be targeted to the individuals for whom they will be maximally effective. We identified two candidate mechanisms through which high-level construal might operate: down-regulation of craving and up-regulation of goal energization (i.e., motivation to quit). Functional magnetic resonance imaging (fMRI) revealed the neural systems engaged by those processes to be distinct. So, we will use multivariate analyses of fMRI data to quantify the similarity of high-level construal to each candidate (Aim 1). This will be done in a longitudinal translational experiment with 4 conditions—high- level construal, down-regulation of craving, up-regulation of goal energization, and treatment-as-usual—in a sample of persistent smokers in poverty, who are the most likely to benefit from a novel, theory-based treatment. The sample size (N = 240) affords an examination of individual differences in the effect of high-level construal on neural activity and craving, and the degree to which they predict smoking reduction (Aim 2).