Evidence from regression‐discontinuity analyses for beneficial effects of a criterion‐based increase in alcohol treatment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Brief interventions effectively reduce alcohol problems; however, it is controversial whether longer interventions result in greater improvement. This study aims to determine whether an increase in treatment for people with more severe problems resulted in better outcome. We employed regression-discontinuity analyses to determine if drinking driver clients (n = 22,277) in Ontario benefited when they were assigned to a longer treatment program (8-hour versus 16-hour) based on assessed addiction severity criteria. Assignment to the longer16-hour program was based on two addiction severity measures derived from the Research Institute on Addictions Self-inventory (RIASI) (meeting criteria for assignment based on either the total RIASI score or the score on the recidivism subscale). The main outcome measure was self-reported number of days of alcohol use during the 90 days preceding the six month follow-up interview. We found significant reductions of one or two self-reported drinking days at the point of assignment, depending on the severity criterion used. These data suggest that more intensive treatment for alcohol problems may improve results for individuals with more severe problems.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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 it