Smoking is responsible for over 40% of premature deaths and disability in the US CDC. Although over 40% of the 48 million Americans that still smoke make a serious quit attempt each year, either on their own (i.e., self-guided quit) or with assistance from formal treatment, less than 5% are able to abstain from smoking for greater than 3 months. The selection hypothesis of smoking prevalence posits that smokers who are not able to quit successfully are ?burdened? by specific characteristics that make it more challenging to quit. For example, those less successful in quitting smoking may be more likely to suffer from cognitive or affective vulnerabilities associated with psychiatric or other disorders. Smokers who suffer from anxiety are among the largest of these high-risk groups. Anxiety, however, is a broad construct that encompasses many mechanisms. New strategies targeting specific vulnerabilities (and not just general self-reported anxiety) are therefore needed to identify, understand, and ultimately, intervene with anxiety-prone smokers. One vulnerability for anxiety that is likely to play a role in smoking lapse behavior is sensitivity to unpredictable threat (SUT), an individual difference factor that is central to many anxiety disorders. SUT may be particularly predictive of smoking lapse as it has been proposed to be a manifestation of neuroadaptations of the stress response that has been observed across addictions. This project is therefore devoted to understanding the role of SUT in smoking lapse behavior and smoking topography (e.g., greater puff velocity, and shorter inter-puff intervals) using an innovative, multimethod assessment of sensitivity to unpredictable threat (i.e., EMG startle, evoked potentials, and self-report). The proposed project is significant from a public health standpoint because it can directly guide the development of novel psychosocial or pharmacologic smoking cessation interventions to help this and similar high-risk populations of smokers quit by targeting unique biologic vulnerability processes that result in poorer cessation outcomes. Meeting the specific aims will help validate the importance of the innovative laboratory assessment, demonstrate the importance of specific targets for assessment for at-risk smokers, and will contribute to the treatment development for smokers with anxiety and related disorders. Hence, the present project will significantly expand knowledge about the process and outcomes of smoking cessation as a function of a core biologic mechanism of dysfunction of anxiety, including the identification of specific mechanisms that impede quitting. In addition, this project will help expand the scope and usefulness of a lab assessment of relapse behavior to speed psychosocial/pharmacologic treatment development. Clinically, this approach will represent highly innovative and significant progress toward precision medicine where the selection of a smoking cessation program is tailored to the individual patient based on their attributes.
This project is devoted to understanding the role of sensitivity to unpredictable threat, a core, trait-like mechanism of dysfunction in anxiety disorders, in smoking lapse behavior using an innovative, multimethod laboratory lapse model involving smoking topography. The study adopts the NIMH's Research Domain Criteria (RDoC) ?lens? as it seeks to move beyond studies of single categorical diagnoses (e.g., DSM defined Panic Disorder) and identify transdiagnostic dimensional constructs reflecting core mechanisms of psychopathology that can be studied across multiple units of analysis (e.g., physiology, behavior). The proposed project has a great deal of public health significance because it can guide the development of novel smoking cessation interventions by targeting unique biologic vulnerability processes that result in poorer cessation outcomes ? ultimately, leading towards greater precision medicine in which the selection of a smoking cessation program is tailored to this high-risk population of smokers.