Brief interventions for older adults (BIO) delivered by non-specialist community health workers to reduce at-risk drinking in primary care: a study protocol for a randomised controlled trial
Bibliographic record
Abstract
Introduction Evidence suggests that brief interventions are effective in reducing alcohol consumption among older adults. However, the effectiveness of these interventions when delivered by community health workers (non-specialists) in a primary healthcare setting is unknown. To our knowledge, this will be the first randomised trial to examine this. Methods and analysis Two hundred and forty-two individuals considered at-risk drinkers (Alcohol Use Disorders Identification Test-Consumption, AUDIT-C score ≥4) will be recruited and randomly allocated to usual care (waiting-list) or usual care plus an intervention delivered by trained community health workers (non-specialists). Seven primary care units (PCUs) in Sao José dos Campos, Brazil. PCUs are part of the Brazilian public healthcare system (Sistema Único de Saúde). Follow-up 6 months. Outcomes The primary outcome will be the proportion of participants considered at-risk drinkers (AUDIT-C score ≥4). Secondary outcomes will include alcohol consumption in a typical week in the last 30 days (in units per week) assessed by the AUDIT, service use questionnaire, cognitive performance—assessed by The Health and Retirement Study Harmonised Cognitive Assessment, physical activity—assessed by the International Physical Activity Questionnaire, depression—assessed by the Geriatric Depression Scale and quality of life—assessed by the Control, Autonomy, Self-realisation and Pleasure-16 instrument. The analysis will be based on intention-to-treat principle. Ethics and dissemination This study has been approved by the Ethics Committee of the Universidade Federal de São Paulo, CEP/UNIFESP Project n: 0690/2018; CAAE: 91648618.0.0000.5505. All eligible participants will provide informed consent prior to randomisation. The results of this study will be published in relevant peer-reviewed journals and in conference presentations. Trial registration number RBR-8rcxkk.
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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 | 0.043 | 0.038 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.017 | 0.008 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.060 | 0.012 |
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".