Counting the cold ones: A comparison of methods measuring total alcohol consumption of managed alcohol program participants
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Managed alcohol programs (MAP) aim to reduce harms experienced by unstably housed individuals with alcohol use disorders by providing regulated access to beverage alcohol, usually alongside housing, meals and other supports. This study compares two methods of estimating participants' outside alcohol consumption in order to inform program policies and practices around alcohol dosing and reducing risks of alcohol-related illnesses. METHODS: The total alcohol consumption of 65 people participating in Canadian MAPs was assessed comparing daily MAP records (1903 client days) with researcher-administered surveys over the same time period. A sub-sample of more complete daily MAP records for 39 people (696 client days) was also compared with the equivalent survey data on drinking. RESULTS: Significantly more standard drinks per day (SDs, one SD = 17.05 mL ethanol) were reported in research interviews than recorded by program staff, whether for program administered drinks alone (means 16.04 vs. 8.32 SDs, t = 5.79, P < 0.001) or including outside-program drinks as reported to staff (16.04 vs. 8.89 SDs, t = 5.37, P < 0.001). Consistent results were found in the sub-sample. The number of outside drinks estimated by comparing program records with the research interviews, varied between 2.71 and 9.94 mean drinks per day per site. DISCUSSION AND CONCLUSIONS: At two sites, MAP participants reported consuming more than twice the amount of alcohol administered on the program. At most sites, there was significant under-reporting of outside drinking. Addressing the problem of outside drinking and total daily consumption is critical for achieving program goals of both short and long-term harm reduction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".