The Russian translations of the Alcohol Use Disorders Identification Test (AUDIT): A document analysis and discussion of implementation challenges
Bibliographic record
Abstract
Aims: To analyze existing Russian translations of the Alcohol Use Disorders Identification Test (AUDIT) and their applicability in Russian-language populations.
 Method: Document analysis of different Russian-language versions of the AUDIT and its shorter versions as identified in a systematic search.
 Findings: A total of 122 Russian translations of the AUDIT or its shorter versions from Russia and other countries were included in the document analysis, 61 of which were unique versions. Across the translations, a series of inconsistencies was identified, most of which related to the first three consumption items and the concept of a standard drink. The identified problems appeared to have been caused by difficulties in adapting the tool to local drinking patterns and local beverage volumes. None of the analyzed sources mentioned systematic translation procedures according to a predetermined protocol.
 Conclusions: Despite the fact that the AUDIT was developed as a standardized screening tool almost 30 years ago, there is still no official translation into the Russian language according to the commonly used procedures for the translation and adaptation of instruments. A systematic translation and validation appears to be urgently needed in order to have an internationally comparable AUDIT for research and clinical purposes in Russian-speaking populations.
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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 | 0.002 | 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) | 0.000 | 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".