Calibrating the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) for detecting alcohol-related problems among Canadian, UK and US soldiers: cross-sectional pre-deployment and post-deployment survey results
Bibliographic record
Abstract
OBJECTIVES: Excessive alcohol use can bring about adverse health and work-related consequences in civilian and military populations. Screening for excessive drinking can help identify individuals at risk for alcohol-related problems who may require clinical interventions. The brief validated measures of alcohol use such as the Alcohol Use Disorders Identification Test (AUDIT), or abbreviated AUDIT-Consumption (AUDIT-C), are often included in military deployment screening and epidemiologic surveys, but appropriate cut-points must be used to effectively identify individuals at risk. Although the conventional AUDIT-C cut-points ≥4 for men and ≥3 for women are commonly used, recent validation studies of veterans and civilians recommend higher cut-points to minimise misclassification and overestimation of alcohol-related problems. This study aims to ascertain optimal AUDIT-C cut-points for detecting alcohol-related problems among serving Canadian, UK and US soldiers. DESIGN: Cross-sectional pre/post-deployment survey data were used. SETTINGS: Comprised Army locations in Canada and UK, and selected US Army units. PARTICIPANTS: Included soldiers in each of the above-mentioned settings. OUTCOME MEASURES: Soldiers' AUDIT scores for hazardous and harmful alcohol use or high levels of alcohol problems served as a benchmark against which optimal sex-specific AUDIT-C cut-points were assessed. RESULTS: Across the three-nation samples, AUDIT-C cut-points of ≥6/7 for men and ≥5/6 for women performed well in detecting hazardous and harmful alcohol use and provided comparable prevalence estimates to AUDIT scores ≥8 for men and ≥7 for women. The AUDIT-C cut-point ≥8/9 for both men and women performed fair-to-good when benchmarked against AUDIT ≥16, although inflated AUDIT-C-derived prevalence estimates and low positive predictive values were observed. CONCLUSION: This multi-national study provides valuable information regarding appropriate AUDIT-C cut-points for detecting hazardous and harmful alcohol use, and high levels of alcohol problems among soldiers. Such information can be useful for population surveillance, pre-deployment/post-deployment screening of military personnel, and clinical practice.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".