期刊
EXPERIMENTAL AND CLINICAL PSYCHOPHARMACOLOGY
卷 25, 期 5, 页码 380-392出版社
AMER PSYCHOLOGICAL ASSOC
DOI: 10.1037/pha0000140
关键词
electronic cigarettes; e-cigarettes; plasma nicotine; puff topography; subjective effects
资金
- National Institute on Drug Abuse of the National Institutes of Health [P50DA036105]
Electronic cigarette (ECIG) nicotine delivery and other effects may depend on liquid nicotine concentration and user experience. This study is the first to systematically examine the influence of ECIG liquid nicotine concentration and user experience on nicotine delivery, heart rate, puff topography, and subjective effects. Thirty-three ECIG-experienced individuals and 31 ECIG-naive cigarette smokers completed 4 laboratory conditions consisting of 2, 10-puff bouts (30-sec interpuff interval) with a 3.3-V ECIG battery attached to a 1.5-Omega cartomizer (7.3 W) filled with 1 ml ECIG liquid. Conditions differed by liquid nicotine concentration: 0, 8, 18, or 36 mg/ml. Participants' plasma nicotine concentration was directly related to liquid nicotine concentration and dependent on user experience, with significantly higher mean plasma nicotine increases observed in ECIG-experienced individuals relative to ECIG-naive smokers in each active nicotine condition. When using 36 mg/ml, mean plasma nicotine increase for ECIG-experienced individuals was 17.9 ng/ml (SD = 17.2) and 6.9 (SD = 7.1; p <.05) for ECIG-naive individuals. Between-group differences were likely due to longer puffs taken by experienced ECIG users: collapsed across condition, mean puff duration was 5.6 sec (SD = 3.0) for ECIG-experienced and 2.9 (SD = 1.5) for ECIG-naive individuals. ECIG use also suppressed nicotine/tobacco abstinence symptoms in both groups; the magnitude of abstinence symptom suppression depended on liquid nicotine concentration and user experience. These and other recent results suggest that policies intended to limit ECIG nicotine delivery will need to account for factors in addition to liquid nicotine concentration (e.g., device power and user behavior).
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