Video-assisted topographical measurement of cigarette smoking: Exploration of an objective approach to evaluate nicotine dependence
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University of Florida, Florida, United States
Wuhan Centers for Disease Prevention and Control, Wuhan, China
Publish date: 2018-05-22
Submission date: 2018-03-12
Final revision date: 2018-05-03
Acceptance date: 2018-05-07
Tob. Prev. Cessation 2018;4(May):21
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.

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.

Compared with a linear model (R2 from 0.003 to 0.74), the non-linear model more adequately captured the temporal pattern of topographic measures (R2 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).

Study findings suggest the potential to objectively and non-invasively measure nicotine dependence using video-assisted smoking topography.

Yan Wang   
University of Florida, 2004 Mowry Rd, 32608 Gainesville, United States
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