Heavy alcohol use in patients on highly active antiretroviral therapy: What responses are needed?
Bibliographic record
Abstract
BACKGROUND: Alcohol has a negative effect on antiretroviral therapy (ART) adherence and HIV treatment outcomes. METHOD: As part of formative work for a project to test the efficacy of an alcohol-focused intervention to reduce alcohol consumption and improve HIV treatment outcomes, we investigated the extent of problem drinking among patients at ART clinics in Tshwane, South Africa (SA), using the Alcohol Use Disorders Identification Test (AUDIT). RESULTS: The finding that a third of drinkers reported hazardous drinking, roughly 10% reported harmful drinking, and a further 10% were possibly alcohol dependent replicates the findings of similar research in the Western Cape and Gauteng provinces of SA. It also points to the need for more routine screening of ART patients for problematic alcohol use. CONCLUSION: The 10-item AUDIT may be too time consuming for health workers in busy ART clinics to administer and score, necessitating even briefer screening instruments for assessing hazardous and harmful drinking.
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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 | 0.018 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".