Use of Wearable Transdermal Alcohol Sensors for Monitoring Alcohol Consumption After Detoxification With Contingency Management: Pilot Randomized Feasibility Trial
Bibliographic record
Abstract
BACKGROUND: Wearable transdermal alcohol sensor (TAS) devices generate continuous data on alcohol consumption through the indiscernible sweat vapors on the skin. This continuous alcohol monitoring capability could provide a new method for alcohol services to monitor service users at various stages of their alcohol treatment. OBJECTIVE: We aimed to assess the feasibility of using a TAS as part of alcohol treatment with alcohol service users using the device with or without contingency management (CM). METHODS: A feasibility study was conducted of a convenience sample of 29 current service users from 3 South London alcohol services. Participants were randomized into either a control (treatment as usual) or CM group (treatment as usual+CM). We assessed the feasibility of enrollment, participation, device tampering and return, and device wearability and the accuracy of data capture. These data were reported descriptively where appropriate, the groups were compared, and alcohol self-report data were compared to the transdermal alcohol concentration to assess accuracy. RESULTS: A total of 34 individuals were approached, and 32 (94%) were enrolled and randomized (n=17, 53% to the control group and n=15, 47% to the CM group) over 5 months. In total, 3 participants withdrew (n=2, 67% from the control group and n=1, 33% from the CM group). There was a total of 203 meetings arranged (29 participants × 7 meetings), and 185 (91.1%) were attended. Only 1 of the 29 participants (3%) admitted to turning the TAS off to avoid monitoring. There were some issues with the TAS not functioning properly and not being able to be cleaned. Removals were recorded, but the definition of TAS removal may need to be improved for future trials. There was a high TAS return rate (28/29, 97% of the participants returned the TAS). Secondary outcomes suggest that the BACtrack Skyn remains an accurate tool to monitor alcohol consumption compared to self-report data and that it is acceptable to wearers over 2 weeks, with many participants (27/28, 96%) answering that they would wear it again and for longer but that the CM procedure could be made clearer. CONCLUSIONS: The delivery of CM via a TAS was feasible in this study, but recommendations for a future larger trial include that the study design should be changed to provide an operationalized rather than manual method of checking whether TAS data meet CM criteria. This would reduce researcher burden and researcher and participant time. Current recruitment and research meeting design seem suitable for a future larger trial. TRIAL REGISTRATION: International Standard Randomised Controlled Trial Number (ISRCTN) ISRCTN46845361; https://www.isrctn.com/ISRCTN46845361.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".