Feasibility of mHealth Strategies to Promote Use of Wrist-Worn Alcohol Biosensors Among Young Adults With HIV: Protocol for the Engage Microrandomized Trial
Bibliographic record
Abstract
BACKGROUND: Alcohol use among young adults with HIV is disproportionately high compared to other age groups with HIV, despite its negative health-related consequences. However, alcohol use interventions tailored to the interests and needs of young adults with HIV are scarce. Self-management interventions that include self-monitoring components have the potential to improve chronic illness outcomes and mitigate alcohol misuse. Although wearable technologies promote self-monitoring behaviors and facilitate the delivery of personalized feedback, people rarely adhere to the long-term use of wearables. OBJECTIVE: The primary aim of this pilot study is to test the feasibility and acceptability of translating theoretically grounded reciprocity and personalized feedback strategies. These strategies will be delivered through app-based messages to promote engagement in wearing a wrist-worn alcohol biosensor among young adults with HIV. METHODS: A total of 40 young adults with HIV (aged 18-29 years) will be enrolled in a 30-day pilot microrandomized trial (MRT). The MRT is an experimental design that facilitates the development and optimization of mobile health just-in-time adaptive interventions. Participants will wear the BACtrack Skyn biosensor, a wrist-worn transdermal alcohol biosensor, and play a smartphone-based game geared toward earning points to care for virtual animals. Longer alcohol biosensor wear time will translate into earning more game points. Every morning and evening, participants will be randomized at equal probability to receive (1) a reciprocity message offering a no-strings-attached gift of either 100 game points or US $1, (2) a message with personalized feedback about their Skyn biosensor wear time, or (3) no message. RESULTS: Data collected during this 30-day MRT will be used to examine the feasibility and acceptability of translating theoretically grounded strategies into messages suitable for a mobile health alcohol intervention tailored to young adults with HIV. Recruitment for this study began in spring 2024, with data collection wrapping up in spring 2025. CONCLUSIONS: This pilot MRT will provide valuable feasibility and acceptability data and set the stage for a full-scale MRT to optimize the integration of reciprocity and personalized feedback into a just-in-time adaptive intervention that increases engagement in biosensor-based alcohol self-management among young adults with HIV. TRIAL REGISTRATION: Clinicaltrials.gov NCT05431855; https://clinicaltrials.gov/study/NCT05431855. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/69966.
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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 | 0.019 | 0.026 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.072 | 0.013 |
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".