Treating alcohol problems with self-help materials: a population study.
Bibliographic record
Abstract
OBJECTIVE: An experimental trial was used to assess the effectiveness of a self-help book and a personalized assessment-feedback intervention, both separately and in combination with each other, in a general population survey. METHOD: Participants (N = 86; 66.3% male) were recruited through a random digit dialing telephone survey conducted by the Centre for Addiction and Mental Health, Toronto, Ontario, Canada. Respondents were randomly assigned to one of four conditions in a two-by-two factorial design: "no-intervention" control group, "personalized feedback only," "self-help book only" and "both personalized feedback and self-help book." Respondents were followed up in 6 months' time, and differences in drinking status were compared between experimental conditions using a multivariate analysis of covariance with baseline drinking severity as the covariate. RESULTS: Support was provided for an interaction hypothesis in which respondents who received both interventions reported significantly improved drinking outcomes at 6-month follow-up, compared with respondents who received just one of the interventions or who received no intervention. CONCLUSIONS: Because respondents were recruited from a representative sample of the general population into a randomized trial with a no-intervention control group, this research design maximized both external and internal validity in examining the effectiveness of self-help interventions.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".