Concurrent validity of an estimator of weekly alcohol consumption (EWAC) based on the extended AUDIT
Bibliographic record
Abstract
BACKGROUND AND AIMS: The three-question Alcohol Use Disorders Identification Test (AUDIT-C) is frequently used in healthcare for screening and brief advice about levels of alcohol consumption. AUDIT-C scores (0-12) provide feedback as categories of risk rather than estimates of actual alcohol intake, an important metric for behaviour change. The study aimed to (i) develop a continuous metric from the Extended AUDIT-C expressed in United Kingdom (UK) units (8 g pure ethanol), offering equivalent accuracy, and providing a direct estimator of weekly alcohol consumption (EWAC) and (ii) evaluate the EWAC's bias and error using the graduated-frequency (GF) questionnaire as a reference standard of alcohol consumption. DESIGN: Cross-sectional diagnostic study based on a nationally-representative survey. SETTINGS: Community dwelling households in England. PARTICIPANTS: A total of 22 404 household residents aged ≥16 years reporting drinking alcohol at least occasionally. MEASUREMENTS: Computer-assisted personal interviews consisting of (i) AUDIT questionnaire with extended response items (the 'Extended AUDIT') and (ii) GF. Primary outcomes were: mean deviation <1 UK unit (metric of bias); root-mean-square deviation <2 UK units (metric of total error) between EWAC and GF. The secondary outcome was the receiver operating characteristic area under the curve for predicting alcohol consumption in excess of 14 and 35 UK units. FINDINGS: EWAC had a positive bias of 0.2 UK units (95% CI = 0.08, 0.4) compared with GF. Deviations were skewed: whereas the mean error was ±11 UK units/week [9.5, 11.9], in half of participants the deviation between EWAC and GF was between 0 and ±2.1 UK units/week. EWAC predicted consumption in excess of 14 UK units/week with a significantly greater area under the curve (0.918 [0.914, 0.923]) than AUDIT-C (0.870 [0.864, 0.876]) or the full AUDIT (0.854 [0.847, 0.860]). CONCLUSIONS: A new estimator of weekly alcohol consumption, which uses answers to the Extended AUDIT-C, meets the targeted bias tolerance. It is superior in accuracy to AUDIT-C and the full 10-item AUDIT when predicting consumption thresholds, making it a reliable complement to the Extended AUDIT-C for health promotion interventions.
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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 | 0.000 |
| 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) | 0.001 | 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".