Predictors of detection of alcohol use episodes using a transdermal alcohol sensor

Nancy P Barnett, E B Meade, Tiffany R Glynn, Nancy P Barnett, E B Meade, Tiffany R Glynn

Abstract

The objective of this investigation was to establish the ability of the Secure Continuous Remote Alcohol Monitoring (SCRAM) alcohol sensor to detect different levels of self-reported alcohol consumption, and to determine whether gender and body mass index, alcohol dependence, bracelet version, and age of bracelet influenced detection of alcohol use. Heavy drinking adults (N = 66, 46% female) wore the SCRAM for 1-28 days and reported their alcohol use in daily Web-based surveys. Participant reports of alcohol use were matched with drinking episodes identified from bracelet readings. On days when bracelets were functional, 690 drinking episodes were reported and 502 of those episodes (72.8%) were detected using sensor data. Using generalized estimating equations, we found no gender differences in detection of reported drinking episodes (77% for women, 69% for men). In univariate analyses, at the level of fewer than 5 drinks, women's episodes were more likely to be detected, likely because of the significantly higher transdermal alcohol concentration levels of these episodes, whereas at the level of 5 or more drinks, there was no gender difference in detection (92.6% for women, 93.4% for men). In multivariable analyses, no variables other than number of drinks significantly predicted alcohol detection. In summary, the SCRAM sensor is very good at detecting 5 or more drinks; performance of the monitor below this level was better among women because of their higher transdermal alcohol concentration levels. Individual person characteristics and bracelet features were not related to detection after number of drinks was included. Minimal bracelet malfunctions were noted.

Conflict of interest statement

Disclosures

All authors declare that they have no conflicts of interest.

Figures

Figure 1
Figure 1
Flow chart of alcohol use episodes and detection.
Figure 2
Figure 2
Percent of 690 Self-Reported Drinking Episodes (N = 66) Detected Using TAC at Different Numbers of Drinks by Gender. t = the number of episodes at each level of drinking.
Figure 3
Figure 3
Peak TAC Levels of 690 Self-Reported Drinking Episodes at Different Numbers of Self-Reported Drinks by Gender. t = the number of episodes at each level of drinking. All self-reported episodes are included, regardless of whether they were detected using TAC criteria. Self-reported episodes that were not detected using TAC criteria were assigned TAC = .000 g/dL. This allows for the gender comparison on TAC across all self-reported episodes, and reflects the lower TAC of men’s episodes.

Source: PubMed

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