Validation of a screening test for alcohol use, the Russian Federation
Bibliographic record
Abstract
OBJECTIVE: To validate a Russian-language version of the World Health Organization's Alcohol Use Disorders Identification Test (AUDIT). METHODS: We invited 2173 patients from 21 rural and urban primary health-care centres in nine Russian regions to participate in the study (143 declined and eight were excluded). In a standardized interview, patients who had consumed alcohol in the past 12 months provided information on their sociodemographic characteristics and completed the Russian AUDIT, the Kessler Psychological Distress Scale and the Composite International Diagnostic Interview to identify problem drinking and alcohol use disorders. We assessed the feasibility of administering the test, its internal consistency and its ability to predict hazardous drinking and alcohol use disorders in primary health care in the Russian Federation. FINDINGS: : 0.842) and accurately predicted alcohol use disorders and other outcomes (area under the curve > 75%). A three-item short form of the test correlated well with the full instrument and had similar predictive power (area under the curve > 80%). We determined sex-specific thresholds for all outcomes, as non-specific thresholds resulted in few women being identified. CONCLUSION: With the validated Russian AUDIT, there is no longer a barrier to introducing screening and brief interventions into primary health care in the Russian Federation to supplement successful alcohol control policies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".