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Much evidence suggests e-cigarettes are substantially less harmful than combustible cigarettes. Assuming this is true, we analyze the ethical case for a policy of e-cigarette availability (ECA) as a tobacco harm reduction strategy. ECA involves making e-cigarettes available to allow smokers to switch to them, and informing smokers of the lower risks of e-cigarettes vis-à-vis smoking. After suggesting that utilitarian/consequentialist considerations do not provide an adequate ethical analysis, we analyze ECA using two other ethical frameworks. First, ECA is supported by a public health ethics framework. ECA is a population-level intervention consistent with respecting individual autonomy by using the least restrictive means to accomplish public health goals, and it supports equity and justice. Second, ECA is supported by four principles that form a biomedical ethics framework. By reducing smokers' health risks and not harming them, ECA fulfills principles of beneficence and non-maleficence. Because ECA allows smokers to make informed health decisions for themselves, it fulfills the principle requiring respect for persons and their autonomy. Here, we consider whether nicotine addiction and thus ECA undermine autonomy, and also discuss the ethical warrant for special protections for youth. Finally, ECA can also advance justice by providing a harm reduction alternative for disadvantaged groups that disproportionately bear the devastating consequences of smoking. Policies of differential taxation of cigarettes and e-cigarettes can facilitate adoption of less harmful alternatives by those economically disadvantaged. We conclude that public health and biomedical ethics frameworks are mutually reinforcing and supportive of ECA as a tobacco harm reduction strategy. Implications: Making e-cigarettes and information about them available is supported as ethical from multiple ethical perspectives.

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Researchers are sometimes interested in predicting a distal or external outcome (such as smoking cessation at follow-up) from the trajectory of an intensively recorded longitudinal variable (such as urge to smoke). This can be done in a semiparametric way via scalar-on-function regression. However, the resulting fitted coefficient regression function requires special care for correct interpretation, as it represents the joint relationship of time points to the outcome, rather than a marginal or cross-sectional relationship. We provide practical guidelines, based on experience with scientific applications, for helping practitioners interpret their results and illustrate these ideas using data from a smoking cessation study.

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Introduction: Studies testing novel tobacco products often provide participants with free product and assess consumption. Some, but not all, studies find that providing free cigarettes increases smoking. We tested changes in smoking when free cigarettes were provided to nondaily, intermittent smokers, who constitute one-third of US adult smokers. Methods: Cigarette consumption was assessed by Time-Line Follow-Back in 235 intermittent smokers for two 2-week periods: when providing their own cigarettes and when provided own-brand cigarettes for free. Smoking topography and carbon monoxide boost were assessed for one cigarette at the end of each period. Results: Cigarette consumption increased significantly, by 66% (from 1.98 to 3.28 cigarettes per day), when cigarettes were available for free; both the number of days the subjects smoked and the number of cigarettes on those days increased. The increases were significantly greater among African Americans, those Fagerström Tobacco Nicotine Dependence scores >0, those with incomes less than US $25,000 per year, those who engaged in greater conscious restraint of smoking, and for smokers of menthol cigarettes, or "longs." Smoking intensity (smoke volume, by topography) and carbon monoxide boost decreased significantly when cigarettes were provided for free. Conclusions: Providing intermittent smokers with free cigarettes substantially increased their smoking while decreasing smoking intensity. The increases in smoking varied according to multiple individual and cigarette-type differences. These phenomena may complicate interpretation of studies that compare consumption of a free test product with cigarette consumption or constituent exposure when smokers are providing their own cigarettes. They also suggest that cigarette cost and variations in low-level dependence and in smoking restraint are factors in nondaily smoking. Implications: The study shows that providing nondaily smokers with free cigarettes increases cigarette consumption, but does differentially for different subgroups and cigarette types, while also decreasing smoking intensity. This suggests the value of using free-cigarette baseline data in studies where interventions provide free cigarettes.

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Ecological momentary assessment (EMA) methods, which involve collection of real-time data in subjects' real-world environments, are particularly well suited to studying tobacco use. Analyzing EMA datasets can be challenging, as the datasets include a large and varied number of observations per subject and are relatively unstructured. This paper suggests that time is typically a key organizing principle in EMA data and that conceptualizing the data as a timeline of events, behaviors, and experiences can help define analytic approaches. EMA datasets lend themselves to answering a diverse array of research questions, and the research question must drive how data are arranged for analysis, and the kinds of statistical models that are applied. This is illustrated this with brief examples of diverse analyses applied to answer different questions from an EMA study of tobacco use and relapse.

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