ArticleDrug and alcohol dependence2025
A wearable alcohol biosensor: Exploring the accuracy of transdermal drinking detection.
Article in Drug and alcohol dependence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Joint effects of real-world cue exposure and affective states on momentary alcohol craving in adults with alcohol use disorder.Drug and alcohol dependence reports · 2026Article
- Applying Artificial Intelligence to Expand the Measurement Tool Kit in Clinical-Psychological Science: Moving Beyond Self-Reports.Clinical psychological science : a journal of the Association for Psychological Science · 2026Article
- Objective Assessment in Clinical Psychological Science: Progress in Wearable Alcohol Biosensors.Annual review of clinical psychology · 2026Review
- Headset-Type Biofluorometric Gas Sensor with CMOS for Transcutaneous Ethanol from the Ear Canal.Sensors (Basel, Switzerland) · 2026Article
- Alcohol approach-avoidance task behavior and brain potentials differentially predict ecologically assessed alcohol craving and consumption in early emerging adulthood.Addiction (Abingdon, England) · 2026Article
- Acceptability and feasibility of a new-generation alcohol biosensor: A mixed methods evaluation in a large community sample.Experimental and clinical psychopharmacology · 2026Article
- Using Mobile Technology to Study Episodes of Alcohol Self-Administration in Daily Life: A Narrative Review.Current addiction reports · 2026Review
- Leveraging Machine Learning to Advance Alcohol Research: Current Applications, Challenges, and Opportunities.Alcohol research : current reviews · 2026Review
- Development of an alcohol biosensor non-wear algorithm: laboratory-based machine learning and field-based deployment.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundTrace amounts of consumed alcohol are detectable within sweat and insensible perspiration. However, the relationship between ingested and transdermally emitted alcohol is complex, varying across environmental conditions and involving a degree of lag. As such, the feasibility of real-time drinking detection across diverse environments has been unclear. In the current research we revisit sensor performance using new tools, exploring the accuracy of a new generation of rapid-sampling transdermal biosensor for contemporaneous drinking detection across diverse environments via machine learning.
methodsRegular drinkers (N = 100) attended three laboratory sessions involving the experimental manipulation of alcohol dose, rate of consumption, and environmental dosing conditions. Participants further supplied breath alcohol concentration (BAC) readings in the field over 14 days. Participants wore compact wrist sensors capable of rapid sampling (20sec intervals). Transdermal sensor data was translated into alcohol use estimates using machine learning, integrating only transdermal data collected prior to the point of BAC assessment.
resultsA total of 5.39 million transdermal readings (28,615hours) and 12,699 BAC readings were collected for this research. Models indicated strong transdermal sensor accuracy for real-time drinking detection across both laboratory and field contexts (AUROC, 0.966, 95 % CI, 0.956-0.972; Sensitivity, 89.8 %; Specificity, 90.6 %). Models aimed at differentiating high-risk (≥0.08 %) drinking levels yielded intermediate (AUROC, 0.738; 95 % CI, 0.698-0.777; only drinking episodes) to strong (AUROC, 0.941, 95 % CI, 0.929-0.954; all data) accuracy levels.
conclusionsResults indicate a range of useful future applications for transdermal alcohol sensors including long-term health tracking, medical monitoring, and just-in-time relapse prevention.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.