Digital Therapeutic Intervention for Women in the UK Armed Forces Who Consume Alcohol at a Hazardous or Harmful Level: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Alcohol misuse is common in the United Kingdom Armed Forces (UKAF), with prevalence significantly higher than in the general population. To date, digital health initiatives to support alcohol misuse have focused on male individuals, who represent approximately 89% of the UKAF. However, female veterans drink disproportionally more than female members of the public. OBJECTIVE: This 2-arm participant-blinded (single-blinded) confirmatory randomized controlled trial (RCT) aims to assess the efficacy of a brief alcohol intervention (DrinksRation) in reducing weekly self-reported alcohol consumption between baseline and a 3-month follow-up (day 84) among women who have served in the UKAF. METHODS: In this 2-arm single-blinded RCT, a smartphone app that includes interactive user-focused features tailored toward the needs of female veterans and designed to enhance participants' motivations to reduce the amount of alcohol they consume is compared with the UK Chief Medical Officer guidance on alcohol consumption. The trial will be conducted among women who have served at least 1 day of paid service in the UKAF. Recruitment, consent, and data collection will be carried out automatically through the DrinksRation app or the BeAlcoholSmart platform. The primary outcome is change in self-reported weekly alcohol consumption between baseline (day 0) and the 3-month follow-up (day 84) measured using the Timeline Follow Back for alcohol consumption. The secondary outcome is the change in the Alcohol Use Disorders Identification Test score measured at baseline and 3-month follow-up between the control and intervention groups. The process evaluation measures include (1) app use and (2) usability ratings as measured by the mHealth App Usability Questionnaire. RESULTS: RCT recruitment will begin in January 2024 and last for 5 months. We aim to complete all data collection, including interviews, by May 2024. CONCLUSIONS: This study will assess whether a smartphone app tailored to the needs of women who have served in the UKAF is efficacious in reducing self-reported alcohol consumption. If successful, the digital therapeutics platform could be used not only to support women who have served in the UKAF but also for other conditions and disorders. TRIAL REGISTRATION: ClinicalTrials.gov NCT05970484; https://www.clinicaltrials.gov/study/NCT05970484. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/51531.
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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 | 0.040 | 0.038 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.016 | 0.008 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.099 | 0.018 |
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".