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Ecological Momentary Assessment (EMA) and Laboratory Assessment of Nicotine Dependence among Dual ENDS Users

Principal Investigator: Jennifer Lynn Pearson

Funding Mechanism:  National Institutes of Health- Grant

ID Number: 1K01DA037950-01

Award Date: 8/15/2014

Institution:  American Legacy Foundation 

Electronic cigarettes (e-cigarettes) are available in two types: “ciga-like” models that resemble cigarettes and “pen-like” models, which may be preferred by exclusive e-cigarette users because they can deliver more nicotine per puff, are customizable, and offer a better “throat hit” than ciga-like models. More information about how e-cigarette characteristics affect whether cigarette smokers transition from e-cigarette experimentation to habitual exclusive use, use both e-cigarettes and regular cigarettes, try and abandon e-cigarettes in favor of continued cigarette smoking, or stop using all tobacco products including e-cigarettes would enhance our knowledge about these products. Specific aims are: (1) to compare how measures of abuse liability (i.e., plasma nicotine concentration, subjective effects including craving and satisfaction, behavioral reinforcement) and measures of product appeal (i.e., perceived norms and liking, design, packaging) vary by e-cigarette device type; (2) to contrast the differences in abuse liability and measures of product appeal between usual cigarette brand and e-cigarette device; and (3) to examine the extent to which measures of abuse liability predict e-cigarette use at one, three, and six months. Researchers will randomize 128 current smokers aged 18-65 who have never used e-cigarettes but are curious about them to use either ciga-like or pen-like e-cigarettes during four laboratory visits over 8-12 days; visits will include assessment of plasma nicotine concentration and subjective ratings linked to abuse liability and product appeal. Research findings related to the differential effects of ciga-like and pen-like e-cigarettes on e-cigarette experimentation and subsequent use patterns may inform future regulatory actions.

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