Characteristics and drinking behaviour of patients on antiretroviral therapy who drink and attend HIV clinics in Tshwane, South Africa: Implications for intervention
Bibliographic record
Abstract
BACKGROUND: Patients on antiretroviral therapy (ART) who drink alcohol are at risk of poor medication adherence and negative health outcomes. OBJECTIVES: To explore the drinking behaviour of patients on ART and assess the associations between drinking, adherence to ART and viral load, and in particular factors associated with binge drinking (≥6 drinks per occasion) at least monthly. METHODS: We recruited 623 HIV patients from six hospitals in the Tshwane metropole who scored positive on the Alcohol Use Disorders Identification Test (AUDIT-C) but were 'non-dependent' drinkers into a randomised controlled trial. This article reports on baseline data. RESULTS: Of the patients, 51% reported drinking in the past week, 60% of men and 33% of women consumed ≥6 standard drinks on a typical drinking day, and 19% of men and 5% of women were identified as drinking at harmful levels. Over a quarter reported having a friend or relative, or a doctor or other healthcare worker, express concern about their drinking or suggest that they cut down. AUDIT total scores were significantly negatively correlated with self-reported adherence to ART and positively correlated with viral load. Number of years on ART was not significantly associated with binge drinking. Persons who were employed part time (odds ratio (OR) 1.474) or were self-employed (OR 2.135) were more likely to binge-drink than unemployed persons. Beer drinkers (OR 1.716) were more at risk for binge drinking than non-beer drinkers, and persons who drank monthly or less (OR 0.053) or 2 - 4 times a month (OR 0.168) were less at risk for bingeing than those who drank ≥4 times per week. CONCLUSIONS: The high volume of alcohol consumed per occasion by patients on ART, especially beer and spirits drinkers, is a concern. Interventions that address structural drivers of heavy drinking and target HIV patients at risk of heavy drinking are needed.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".