Utility of Brief Versions of the Alcohol Use Disorders Identification Test (AUDIT) to Identify Excessive Drinking Among Patients in HIV Care in South Africa
Bibliographic record
Abstract
OBJECTIVE: In sub-Saharan Africa, large proportions of patients who are on antiretroviral therapy (ART) engage in excessive alcohol use, which may lead to adverse health consequences and may go undetected. Consequently, health care workers need brief screening tools to be able to routinely identify and manage excessive alcohol use among their patients. Various brief versions of the valid and reliable 10-item Alcohol Use Disorders Identification Test (AUDIT) (i.e., the AUDIT-C, AUDIT-3, AUDIT-QF, AUDIT-PC, AUDIT-4, and m-FAST) may potentially replace the full AUDIT in busy HIV care settings. This study aims to assess the utility of these six brief versions of the AUDIT relative to the full AUDIT for identifying excessive alcohol use among patients in HIV care settings in South Africa. METHOD: Participants were 188 (95 women) patients from three ART clinics within district hospitals in the City of Tshwane Metropolitan Municipality who reported past-12-month alcohol use. Performance of each brief AUDIT measure for identifying excessive alcohol use was evaluated against that of the full AUDIT (with a cutoff score of ≥6 for women and ≥8 for men) as the gold standard. We used receiver-operating characteristic (ROC) analysis. RESULTS: Most brief AUDIT measures had an area under the receiver operating curve (AUROC) above .90 when compared with the full AUDIT (five of six for women and three of six for men). The AUDIT-PC, AUDIT-4, and m-FAST had the highest AUROCs, whereas the three brief measures comprising only consumption items had low specificities at the most optimal cutoff levels. CONCLUSIONS: Various brief versions of the AUDIT may be appropriate substitutes for the full AUDIT for screening for excessive alcohol use in HIV clinics in sub-Saharan Africa.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".