Does electronic cigarette liquid nicotine concentration and user experience influence plasma nicotine concentration

Drug and Alcohol Dependence 156 (2015) e183–e245 e185 Results:Cigarette smokers displayed higher commission errors, indicative of poor impulse control on the IMT, and lower total scores on the IGT compared to controls. However they did not differ from controls on the BIS-11 total scores or sub-scales. Furthermore, among the cigarette smokers, IMT commission errors correlated with net scores on IGT during the second, third, fourth and fifth blocks and between IGT total net score. Conclusions: Consistent with previous studies, these preliminary results suggest that cigarette smokers are more impulsive. In addition, this study found that smokers make poor decisions in laboratory behavioral tasks. Furthermore, there was a correlation between decision making as measured by the IGT and impulsivity measured on the IMT. However, given the small sample size of the cigarette smokers these data should be interpreted cautiously. Financial support: Supported by NIDA Grants P50DA009262, R01 DA034131, U54 DA038999 and P50 DA033935. http://dx.doi.org/10.1016/j.drugalcdep.2015.07.496 Content analysis of cannabis smartphone applications Danielle Ramo1,∗, Lucy Popova2, Shirley Zhao1, Kathryn Chavez4, Rachel Grana Mayne3 1 Psychiatry, UC San Francisco, San Francisco, CA, United States 2 Center for Tobacco Control Research and Education, UC San Francisco, San Francisco, CA, United States 3 Tobacco Control Research Branch, National Cancer Institute, Rockville, MD, United States 4 Semel Institute for Neuroscience & Human Behavior, UCLA, Los Angeles, CA, United States Aims: With a global audience expected to total 1.75 billion in 2014, Smartphone technology is pervasive and widely used to obtain information about drugs such as cannabis. Previous reviews of Smartphone applications (“apps”) about health behavior highlight the wide variety of resources available to users without clear scientific or theoretical basis. There is a need to understand more about the available resources for those searching for Smartphone cannabis apps. We investigated 60 cannabis apps for iPhone and Android phones as of November 26, 2014. Methods: iTunes and GooglePlay app stores were searched using the terms “cannabis” and “marijuana.” Two trained coders classified the top 20 apps for each term and each store, using a coding guide. Apps were examined for presence of 8 categories, 18 subcategories, and features. Results: Total apps available for each search term were 124 (cannabis) and 218 (marijuana) in iTunes, and 250 of each cannabis andmarijuana inGooglePlay. TheTop20apps ineachcategorywere coded for a total of 60 independent apps (31 iTunes, 29GooglePlay). On iTunes, the most popular apps provided cannabis strain classifications (52%), street names for cannabis (39%), or general facts about cannabis (39%). Only one app (3%) provided any information or resources related to cannabis abuse. Most apps were free (74%), all were rated “17+,” and average rating was 4.0/5. On GooglePlay, the most popular app types offered games (28%), phone utilities (e.g., wallpaper, clock; 21%) and cannabis recipes (21%); one app (3%) addressed addiction. Most apps were free (93%), rated “high maturity” (79%), and average rating was 4.1/5. Conclusions: The top cannabis apps for iPhone tend to provide information or education, while top Android apps tend to be primarily entertaining. Apps addressing addiction or cessation were underrepresented in themost popular cannabis Smartphone applications. Financial support: K23DA032578. http://dx.doi.org/10.1016/j.drugalcdep.2015.07.497 Does electronic cigarette liquid nicotine concentration and user experience influence plasma nicotine concentration? Carolina Ramoa ∗, Tory Spindle, Kathleen Osei, Barbara Kilgalen, Alison Breland, Thomas Eissenberg Psychology, VCU, Richmond, VA, United States Aims: Electronic cigarettes (ECIGs) heat a nicotine-containing liquid and the resulting aerosol is inhaled by the user. The nicotine concentration of the liquid and experience of the user may influence plasma nicotine concentration. The purposes of this clinical lab study were to examine the relationship of ECIG liquid nicotine concentration on user nicotine exposure following ECIG use and to compare the plasma nicotine concentration and ECIG use behavior (puff topography) of ECIG-experienced users and ECIG-naive cigarette smokers. Methods: Eleven ECIG-experienced and 13 ECIG-naive cigarette smokers used an “eGO” ECIG battery (3.3V; 1000mAh) attached to a dual-coil (1.5 ohm), 510-cartridge during 4 independent, doubleblind sessions that differed by liquid nicotine concentration (0, 8, 18, or 36mg/ml). Within each session, puff topography was recorded in2, 10-puff ECIG-usebouts (30 s interpuff interval). Blood was sampled periodically for later analysis. Results: Plasma nicotine concentration depended on liquid nicotine content [concentration× time F (27, 513) =6.2; p 6.6; ps <0.05]. Conclusions: ECIGs can deliver nicotine reliably and that delivery is in part dependent on liquid nicotine concentration. Also, ECIG-experienced users are exposed to more nicotine in some cases, perhaps because they take longer and larger puffs. A comprehensive understanding of that factors that influence ECIG nicotine delivery (device characteristics, liquid nicotine concentration, user behavior) is vital to future, empirically-based, ECIG regulation. Financial support: P50DA036105. http://dx.doi.org/10.1016/j.drugalcdep.2015.07.498 Assessing potential abuse and misuse of testosterone and other anabolic steroids among middle-aged and older men prescribed steroids Jovita Randall-Thompson ∗, Alicja Lerner, Joshua Hunt, Michael Klein Controlled Substance Staff (CSS), Food and Drug Administration (FDA), Silver Spring, MD, United