INTRODUCTION Addressing nicotine dependence is key to effective smoking cessation. While self-report measures of nicotine dependence are often challenged for their reliability and validity, there is a lack of non-invasive and inexpensive objective measures of nicotine dependence. In this study, we aimed to explore the potential of using video-assisted smoking topography to derive objective measures indicative of nicotine dependence with the guidance of nicotine-receptor-based self-titration theory. METHODS Videotaped topography data were collected for one episode of smoking a whole cigarette the first time of the day from 10 cigarette smokers with diverse racial backgrounds (4 males and 6 females, mean age = 27 years, SD = 7.2). Temporal patterns of individual topographic measures (i.e. puff interval, puff speed, puff duration, inhalation duration, and rest duration) were measured and plotted against time. Levels of nicotine dependence were evaluated using three standard scales, including the 14-item DSM-IV scale, the 6-item ICD-10 scale, and the 6-item Fagerström Test of Nicotine Dependence. Both linear and non-linear fold catastrophe dynamic models were used to fit the data. RESULTS Compared with a linear model (R 2 from 0.003 to 0.74), the non-linear model more adequately captured the temporal pattern of topographic measures (R 2 from 0.11 to 0.99), especially puff speed. The indicators derived from the fitted fold catastrophe curve (e.g. average puff speed) were significantly associated with nicotine dependence scores, especially DSM-IV scale scores (r from 0.64 to 0.93). CONCLUSIONS Study findings suggest the potential to objectively and non-invasively measure nicotine dependence using video-assisted smoking topography.
INTRODUCTIONMuch progress has been made in tobacco control since the 1950s, but tobacco use remains the leading preventable cause of disease and premature death 1 . There are more than 1 billion people in the world who smoke 2 . Evidence-based behavioral (e.g. counseling, motivational interviewing) and pharmacological (e.g. nicotine replacement therapy, varenicline, bupropion) interventions are available for clinical, personal, family and community based tobacco cessation, but these interventions achieve only a small to moderate effect if delivered in practice 3 . Even with additional assistance, the majority of smokers still experience difficulties quitting with success rates of self-quit attempts as low as 3%4 . Smokers experience difficult quitting primarily because of nicotine addiction 4 . Measuring nicotine dependence with high reliability and validity is critical to tailor treatment to individual patients and to evaluate treatment progress 5 . However, obtaining good measures has been challenging, in part due to a lack of methods to acquire objective data 6 .
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