Brief interventions for problem gambling: A meta-analysis
Bibliographic record
Abstract
BACKGROUND: Brief interventions have been increasingly investigated to promote early intervention in gambling problems; an accurate estimate of the impact of these interventions is required to justify their widespread implementation. The goal of the current investigation was to evaluate the efficacy of in-person brief interventions for reducing gambling behaviour and/or problems, by quantifying the aggregate effect size associated with these interventions in the published literature to date. METHODS: Randomized controlled trials including the following design features were identified via systematic review: an adult sample experiencing problems associated with gambling; an in-person individual psychosocial intervention of brief duration (≤3 sessions); a control/comparison group; and an outcome related to gambling behaviour and/or problems. RESULTS: Five records compared brief interventions to assessment only control; using a random effect model, brief interventions were associated with a small but statistically significant reduction in gambling behaviour across short-term follow-up periods versus assessment only control (g = -.19, 95% CI [-.37, -.01]). Aggregate effect sizes for gambling problems and long-term follow-up periods were not statistically significant. Five records compared brief interventions to longer active interventions; there was no significant difference between brief interventions and longer active interventions. CONCLUSIONS: Results supported the efficacy of brief interventions for problem gambling compared to inactive control in the reduction of gambling behaviour; no differences were found across brief versus longer interventions for both gambling behaviour and problems. While these findings must be interpreted in the context of the limited number of studies and small magnitude of the combined effect sizes, the current meta-analysis supports the further investigation of the public health impact of these cost-effective interventions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.013 |
| Bibliometrics | 0.001 | 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) | 0.005 | 0.002 |
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; both teacher heads agree on what is shown here.
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".