Medical Conditions of Hazardous Drinkers and Drug Users in Primary Care Clinics in Cape Town, South Africa
Bibliographic record
Abstract
Research has identified a wide range of health conditions related to alcohol and drug use in studies conducted primarily in developed countries and in populations with severe alcohol and drug problems. Little is known about medical conditions in those with less severe alcohol and drug use in developing countries. We used WHO AUDIT and ASSIST screeners to identify hazardous drinking or drug use in public health clinics in Cape Town, South Africa, and included questions about doctor-diagnosed medical conditions. Using logistic regression we examined the relationship of medical conditions to hazardous alcohol, drug and tobacco use. Those with hazardous substance use had higher prevalence of many health conditions including tuberculosis. Hepatitis B, migraine, chronic bronchitis, and liver cirrhosis. Optimal treatment for some medical conditions may include treatment of underlying hazardous substance use, particularly use of drugs other than alcohol. In these populations, access to substance use treatment is limited and even brief interventions or advice may be useful.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".