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Use of the BACtrack Skyn alcohol biosensor: Practical applications for data collection and analysis.
- Source :
- Addiction; Aug2023, Vol. 118 Issue 8, p1586-1595, 10p, 1 Chart, 3 Graphs
- Publication Year :
- 2023
-
Abstract
- Aims: Alcohol biosensors, including the BACtrack Skyn, provide an objective and passive method of continuously assessing alcohol consumption in the natural environment. Despite the many strengths of the Skyn, six key challenges in the collection and processing of data include (1) identifying consumed alcohol; (2) identifying environmental alcohol; (3) identifying and determining the source of missing or invalid data; (4) achieving high participant adherence; (5) integrating Skyn and self‐report data; and (6) implications for statistical inference. In this report we outline these challenges, provide recommendations to address them and identify future needs. Design and settings: Procedures from several laboratory and field‐based pilot studies are presented to demonstrate practical recommendations for Skyn use. Data from a pilot study including a 7‐day ecological momentary assessment period are also presented to evaluate effects of environmental alcohol on BACtrack Skyn readings. Conclusions: To address challenges in the collection and processing of data from the BACtrack Skyn alcohol biosensor, researchers should identify goals in advance of data collection to anticipate the processing necessary to interpret Skyn data. The Transdermal Alcohol Sensor Data Macro (TASMAC) version 2.0 software can help to process data rapidly; identify drinking events, missing data and environmental alcohol; and integrate the sensor with self‐report data. Thorough participant orientation and regular contact in field studies can reduce missing data and enhance adherence. Many recommended methods for Skyn use are applicable to other alcohol sensors and wearable devices. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09652140
- Volume :
- 118
- Issue :
- 8
- Database :
- Complementary Index
- Journal :
- Addiction
- Publication Type :
- Academic Journal
- Accession number :
- 164656280
- Full Text :
- https://doi.org/10.1111/add.16207