This R03 award focuses on FDA CTP interest area 4: electronic cigarette use, and will result in a psychometrically validated e-cigarette purchase task (E-CPT) that can be implemented across varying use patterns and research protocols. Electronic cigarette (e-cig) use has exploded in recent years, and the use of refillable advanced-generation devices is rapidly growing. However, little is yet understood about this behavior, or about the relative reinforcing efficacy of e-cig use across individuals. One powerful tool for assessing reinforcing efficacy is a behavioral economic purchase task. Behavioral economic purchase tasks have been successfully developed and implemented for cocaine, alcohol, opiate, cigarette, and marijuana use, and demand indices derived from them have been used to characterize a sample population with regard to motivation to use a substance, to show changes in the reinforcing efficacy of a drug as a result of an experimental manipulation or treatment effect, and to identify individuals who may be likely to respond to a given treatment. However, to date no such task exists for e-cigarettes. Purchase tasks ask participants to estimate their daily consumption of a substance across escalating prices, from which five indices of demand are derived which are a proxy for aspects of the reinforcing efficacy of the substance. In preliminary work conducted by the PI, two alternative versions of an E-CPT were developed which asked about daily consumption in different ways: one in which the unit of consumption is puffs, and another in which the unit is mLs of nicotine liquid. In the current project, users of advanced-generation e-cigarette devices will be asked to complete both versions of the E-CPT, as well as other self-report measures of e-cigarette use and dependence. Then, participants will use their own e-cigarette in the laboratory during a one hour ad lib self-administration period. Indices of demand derived from the E-CPT will be independently correlated with measures of use, dependence, and behavior during the self-administration period. Then, we will determine which version of the task better characterizes the actual use of these products in our sample. Further exploratory analyses using the validated version of the task will examine whether demand indices predict current cigarette use, traditional cigarette quit status, and other variables. The project outlined in this application represents a small, self-contained research project that will result in measure of the reinforcing efficacy of advanced generation e-cigarette devices that can be easily disseminated and employed in many different settings. Such a measure will provide invaluable evidence about the behavior of current users, and provide insight in to how their behavior might change as a function of changes in e-cigarette prices. In the future, this validated e-CPT can be used in other applications to predict abuse liability of new product designs and to predict those users who are likely to quit smoking successfully. Such a measure will enhance our understanding of e-cig use and contribute to the science base that may inform future policy decisions.