Effects of using recommended coping strategies on drinking outcome following a brief intervention
Bibliographic record
Abstract
AIMS: To explore the unique contribution to outcome drinking of clients' use of six strategies for moderating drinking, after statistically accounting for variance explained by some client and intervention variables. DESIGN: An exploratory hierarchical regression analysis assessed the contributions to variance in drinking outcome of pre-intervention (client characteristics, baseline drinking), assignment (level of assessment, therapist experience) and early follow-up variables. Data came from an experimental trial which evaluated the effect of adding assessment to provision of a self-help book to heavy drinkers. SETTING: Diverse Ontario communities. PARTICIPANTS: Heavy drinkers (99 males, 56 females) were selected from 185 media-recruited applicants who were screened by telephone to exclude cases with severe alcohol-related problems. Their mean (+/- SD) pre-admission weekly quantity of alcohol consumed was 22 +/- 15 drinks. Follow-up rates at 3 and 12 months were 92% and 88%. MEASUREMENTS: Regressed onto weekly quantity at follow-up were: client characteristics, previous measures of weekly quantity, experimental condition and use of the menu of strategies (setting goals for drinking, keeping track of drinking, pacing drinking, planning ahead to avoid heavy drinking, developing free-time activities and coping with problems without drinking). FINDINGS: At 3 months the variables predicting lower weekly quantity were: pre-intervention weekly quantity, developing free-time activities, setting goals for drinking and condition. Lower weekly quantity at 12 months was predicted by lower 3-month and pre-intervention weekly quantity, and regular use of: coping with problems without drinking, setting goals for drinking and keeping track of drinking. CONCLUSIONS: This descriptive study revealed a positive association between level of use of recommended coping strategies at follow-up and drinking outcome. Controlled studies of the effects of strategy use on drinking outcome are therefore warranted.
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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 | 0.002 | 0.012 |
| 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 | 0.001 |
| 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".