Impact of normative feedback on problem drinkers: a small-area population study.
Bibliographic record
Abstract
OBJECTIVE: As many as one in four adults in North America experiences some problems due to alcohol consumption. Although most of these problem drinkers do not have concerns that are severe enough to merit formal treatment, such drinking has large economic costs and can place the drinker at risk for long-term negative health and social consequences. The present study evaluated a minimal intervention that used normative feedback about population drinking to motivate changes in alcohol use. METHOD: An intervention pamphlet was mailed to over 6,000 households in Toronto, randomized by block from a region containing almost 10,000 households. In the month after the mailing, a general population survey was conducted in the region to assess alcohol use. RESULTS: Respondents from households receiving normative feedback (n = 472) reported significantly lower alcohol use than controls (n = 225), but this effect occurred only among respondents who met an objective criterion for problem drinking and who perceived some risk associated with their drinking. CONCLUSIONS: Viewed from a public health perspective, normative feedback interventions have the potential for a significant payoff because they can be provided at low cost and to problem drinkers who might ordinarily never access any treatment services.
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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) | 0.001 | 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".