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Principal Investigator: Elliot Todd Berkman
Organization: UNIVERSITY OF OREGON
Fiscal Year: 2024
Award: $562,286
Funding agency: National Cancer Institute
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).
Terms: <21+ years old><Abstinence><Adult><Adult Human><Affect><Affective><Behavior><Cancer Control><Cancer Control Science><Cancers><Cigarette><Cigarette Smoker><Data><Decision Making><Disease><Disorder><Down-Regulation><Event><Fire - disasters><Fires><Functional MRI><Functional Magnetic Resonance Imaging><Future><Goals><Health Care Professional><Health Professional><Health Promotion><Health behavior><Healthcare professional><Impoverished><Individual><Individual Differences><Informal Social Control><Intervention><Intervention Strategies><Knowledge><Lateral><Light><Machine Learning><Malignant Neoplasms><Malignant Tumor><Malignant Tumor of the Lung><Malignant neoplasm of lung><Medial><Motivation><Multivariate Analyses><Multivariate Analysis><Neurophysiology - biologic function><Participant><Pathway interactions><Pattern><Personality Traits><Persons><Photoradiation><Poverty><Process><Provider><Psychology><Public Health><Pulmonary Cancer><Pulmonary malignant Neoplasm><Regulation><Reporting><Research><Risk><Salutogenesis><Sample Size><Sampling><Scanning><Science><Self Regulation><Smoke><Smoker><Smoking><Stimulus><System><Techniques><Testing><Theoretic Models><Theoretical model><Time><Training><Triage><United States><Up-Regulation><Upregulation><Work><adulthood><arm><care as usual><cease smoking><cigarette craving><cigarette smoking><cigarette use><cognitive process><cognitive reappraisal><cognitive regulation><cost><craving><efficacy trial><experience><experiment><experimental research><experimental study><experiments><fMRI><fighting><fire><health related behavior><individualized strategies><insight><interventional strategy><lens><lenses><lung cancer><machine based learning><malignancy><neoplasm/cancer><neural><neural function><neural imaging><neural mechanism><neuro-imaging><neuroimaging><neurological imaging><neuromechanism><novel><pathway><personalization of treatment><personalized medicine><personalized strategies><personalized therapy><personalized treatment><preventable death><preventable mortality><promoting health><quit smoking><response><response to therapy><response to treatment><smoking cessation><stop smoking><theories><therapeutic response><therapy response><tobacco control><tool><treatment as usual><treatment response><treatment responsiveness><usual care>