Saul Shiffman - US grants

The aim of the study is to explore host factors in tobacco dependence by studying non-dependent smokers ("chippers"). Theories of tobacco dependence predict that chronic use of tobacco should lead to dependence. Preliminary data collected by the investigator characterizes a population of aberrant smokers who regularly smoke a small number of cigarettes without any apparent dependence. The pilot data establishes that chippers inhale and absorb nicotine, but differ from dependent smokers in many respects, including smoking motives, smoking history, and family history of smoking. A series of studies is proposed to examine smoking behavior and the behavioral pharmacology of tobacco in this population. The studies focus on the role of nicotine in chippers smoking, comparing them with a group of regular smokers. One study explores how nicotine pharamcodynamics, pharmcokinetics, and metabolism may differ in chippers (compared to regular smokers). A nicotine titration study examines whether chippers attempt to regulate blood nicotine levels, while a companion study examines chippers' nicotine preference under neutral, stressful, and relaxing conditions. The development of a tobacco withdrawal syndrome is also examined and a self-monitoring study investigates the stimulus antecedents of smoking in chippers and regular smokers. Finally, chippers are compared to regular smokers on a battery of self-report measures of smoking history and psychosocial factors. Chippers' smoking behavior challenges simple theories of tobacco dependence; a systematic investigation of their smoking behavior may provide insight into the nature and development of tobacco dependence in the majority of smokers.

The proposed study examines the role of stress in smoking relapse, focussing on interactions between stress and individual differences in reactivity to stress. The central hypothesis is that stress promotes relapse primarily among smokers who are emotionally or physiologically hyperresponsive to stress. It is also hypothesized that tobacco withdrawal enhances stress reactivity, making dependent smokers especially vulnerable to stress-induced relapse. A sample of 200 quitters, including both unaided quitters and clinic participants, will be drawn from a diverse HMO population. Baseline measures include smoking history and biochemical and psychometric measures of dependence. Stress reactivity is assessed via laboratory exposure to multiple stressors and monitoring of multiple response modalities. Stressors include (1) noise, which elicits emotional, but not physiological, responses; (2) public speaking, which elicits marked emotional and physiological arousal; (3) mental arithmetic, which elicits very consistent cardiovascular responses; and (4) isometric exercise, which elicits cardiovascular responses without emotional arousal. Stressors 1-3 also have apparent relevance to smoking or relapse. Multiple response modalities are assessed before and after each stressor: emotional response, cardiovascular response, and desire to smoke. Reactivity assessments are repeated 3-5 days after cessation to assess the effects of withdrawal, and 1 month later to study the effects of protracted abstinence (among abstainers) and of renewed smoking (among recidivists). Intensive assessment of stress during maintenance is implemented by a series of structured telephone interviews extending from baseline through 6-month follow-up. Claims of abstinence will be biochemically verified at 1, 3, and 6 months. Multiple regression analyses will focus on the joint and interactive effects of reactivity and stress experienced at various times in maintenance. Structural modeling will be used to derive appropriate measurement models for the reactivity and stress data and to test substantive models of their interactions in relapse.

Relapse is the greatest challenge in the treatment of addictions, including cigarette smoking. Research on relapse episodes has relied solely on retrospective recall; furthermore, relapse research has failed to integrate data on proximal antecedents of relapse episodes with data on individual differences and on contextual variables that predispose people to relapse. The proposed study uses an innovative method of computerized self-monitoring to study smoking relapse. A hand-held self-monitoring computer (SMC) will be used to characterize the baseline smoking patterns of 252 subjects recruited for smoking cessation treatment. Subjects carry the SMC for 2 weeks and record the situational and affective antecedents of smoking. The SMC also prompts subjects randomly to record data when they are not smoking, thus measuring the base-rates of relevant behaviors outside of smoking situations, and estimating the association between these stimuli and smoking. The computer also obtains daily measures of stress and withdrawal (both subjective and objective [cognitive performance]). Once subjects quit smoking, they use the SMC for 4 weeks to record the antecedents and sequelae of episodes of smoking ("lapses") and strong temptations; the SMC continues to randomly sample situations and to assess stress and withdrawal. Statistical methods include logistic regression and survival analysis. We will examine proximal antecedents of lapses and temptations in comparison to base-rates in randomly-sampled situations. Other analyses will consider the role of background stress and withdrawal in promoting relapse, and their interactions with proximal precipitating stimuli. The prospective design will assess whether the after-effects of relapse crises ("Abstinence Violation Effects") promote progression towards relapse. Finally, using data collected at baseline, we will examine whether (as conditioning theories predict) individual differences in smoking patterns are mirrored in individual differences in relapse patterns. The study includes methodological analyses: The effects of prolonged monitoring will be measured in a comparison group that undergoes self-monitoring but does not quit smoking. The validity of retrospective relapse interviews, widely-used to collect relapse data, will be assessed relative to real-time self-monitoring data. The findings of the study are expected to be highly relevant for the design of more effective interventions to prevent relapse to cigarette smoking and other drug addictions.

[unreadable] DESCRIPTION (provided by applicant): US smoking behavior is undergoing dramatic change: According to BRFSS, 25% of all adult smokers are now intermittent smokers (ITS) who do not smoke daily - an increase of 40% over 5 years (1996-2001). Understanding ITS is important for several reasons: ITS smoking patterns challenge current models of smoking behavior, ITS smokers incur substantial health risk, some ITS smokers have trouble quitting, and we lack knowledge of how to intervene in ITS. Estimates suggest that ITS is growing and will continue to grow, becoming a prominent smoking pattern that theory and interventions must be able to address. Although epidemiological surveys have characterized the demographics of ITS, the field lacks substantive information about ITS: why they smoke; how they smoke, and when they smoke. It is essential to fill these gaps in knowledge to more fully understand factors that control smoking behavior, to refine theories of nicotine dependence and smoking, and to develop more precisely directed interventions that will assist this growing segment of the smoking population. To fill these gaps, we propose an intensive case-control study contrasting 300 ITS and 300 daily smokers (DS) recruited from the community via random-digit dialing. We hypothesize that stimulus control - the association of smoking to particular stimulus contexts - is a key distinguishing feature of ITS compared to DS. We propose to study stimulus control in ITS and DS in two ways: (1) In a naturalistic field study, subjects will track the stimuli associated with smoking and non-smoking occasions for two weeks using electronic diaries and Ecological Momentary Assessment methods. (2) In a randomized laboratory experiment using cue-exposure methods, we will assess craving responses to a panel of cues (e.g., negative affect, positive affect, alcohol). Additional analyses will compare groups on smoking history and dependence and use baseline data to predict prospectively ITS transitions to daily smoking and to abstinence over a follow-up of up to 4 years. Thus, our study focuses on individual differences in stimulus control of smoking as an important process that may be associated with patterns of regular and addictive smoking. These studies have the potential to shed some much needed light on ITS as an important emerging smoking pattern, inform theories of nicotine dependence, and suggest directions for intervention both with ITS and with regular daily smokers. [unreadable] [unreadable] [unreadable]

DESCRIPTION (provided by applicant): Relapse is a central problem in smoking cessation and other areas of behavior change. Although our conceptual models of relapse and our methods of measuring behavior and its antecedents in real-time have grown in sophistication over the past 20 years, our analytical models have not followed suit. The gap between the richness of dynamic conceptual models of change, and the relatively simple, linear statistical models of change typically adopted has slowed progress in understanding and preventing relapse. Although research has identified individual differences that predict increased relapse risk, we know little about how (i.e., by what proximal mechanisms) such factors influence momentary smoking decisions. As a result, we do not know which proximal processes to monitor or target in smoking cessation interventions. In addition, we do not yet know how to identify smokers most vulnerable to unfavorable experiences when they quit smoking, in terms of subjective distress and demoralization. As such, we do not yet know how to improve the process of quitting while also effectively promoting abstinence. Reducing distress and demoralization during the process of quitting may have important implications for late relapse and recycling (or returning to abstinence following relapse). In the proposed project, the research team will bridge the gap between conceptual and analytic models of relapse and address these important, unanswered questions about the relapse process. To achieve these aims, the team will apply state-of-the-art statistical modeling paradigms to real-time data on smoking and its antecedents collected via ecological momentary assessment (EMA) from four samples of smokers engaged in assisted smoking cessation attempts. First, the team will conduct latent transition analyses to identify both distal and proximal predictors of key transitions in the smoking cessation process (i.e., a first lapse, relapse to regular smoking, and recycling). Second, the team will fit nonlinear dynamical systems models to the data to identify the combinations of distal, proximal, and contextual influences that predict non-linear increases in lapse and relapse risk. Third, the team will use latent growth mixture modeling to identify classes of trajectories in smoking and subjective distress or demoralization during the first 2-6 weeks of a quit attempt in an effort to identify predictors of unfavorable experiences that could be ameliorated with future treatments. Results of these analyses will extend knowledge of critical, distal determinants of important smoking and subjective outcomes, and will illuminate how these influences affect key transitions or trajectories in the smoking cessation process. Such information could suggest new treatment targets and new strategies for matching smokers to treatments or delivering just-in-time treatments during periods of elevated risk. Results from the proposed analyses may have implications for other addictive or health behavior changes, as well. In addition, the proposed application of state-of-the-art analytic modeling to behavior change data may serve as a model to other researchers, and thus may spur advances and innovations in diverse research areas.