Quantifying alcohol consumption: Self-report, transdermal assessment, and prediction of dependence symptoms

Research on alcohol use depends heavily on the validity of self-reported drinking. The present paper presents data from 647 days of self-monitoring with a transdermal alcohol sensor by 60 young adults. We utilized a biochemical measure, transdermal alcohol assessment with the WrisTAS, to examine the convergent validity of three approaches to collecting daily self-report drinking data: experience sampling, daily morning reports of the previous night, and 1-week timeline follow-back (TLFB) assessments. We tested associations between three pharmacokinetic indices (peak concentration, area under the curve (AUC), and time to reach peak concentration) derived from the transdermal alcohol signal and within- and between- person variation in alcohol dependence symptoms. The WrisTAS data corroborated 85.74% of self-reported drinking days based on the experience sampling data. The TLFB assessment and combined experience sampling and morning reports agreed on 8727% of drinking days. Drinks per drinking day did not vary as a function of wearing or not wearing the sensor; this indicates that participants provided consistent reports of their drinking regardless of biochemical verification. In respect to self-reported alcohol dependence symptoms, the AUC of the WrisTAS alcohol signal was associated with dependence symptoms at both the within- and between- person level. Furthermore, alcohol dependence symptoms at baseline predicted drinking episodes characterized in biochemical data by both higher peak alcohol concentration and faster time to reach peak concentration. The results support the validity of self-report alcohol data, provide empirical data useful for optimal design of daily process sampling, and provide an initial demonstration of the use of transdermal alcohol assessment to characterize drinking dynamics associated with risk for alcohol dependence. (C) 2015 Elsevier Ltd. All rights reserved.