Online interventions for problem gamblers with and without co-occurring problem drinking: study protocol of a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: The current randomized controlled trial seeks to evaluate whether providing access to an Internet intervention for problem drinking in addition to an Internet intervention for problem gambling is beneficial for participants with gambling problems who do or do not have co-occurring problem drinking. METHODS: Potential participants will be recruited online via a comprehensive advertisement strategy, if they meet the criteria for problem gambling. As part of the baseline measures, problem drinking will also be assessed. Eligible participants (N = 280) who agree to partake in the study and to be followed up for 6 months will be randomized into one of two versions of an Internet intervention for gamblers: an intervention that targets only gambling issues (G-only) and one that combines a gambling intervention with an intervention for problem drinking (G + A). For problem gamblers who exhibit co-occurring problem drinking, it is predicted that participants who are provided access to the G + A intervention will demonstrate a significantly greater level of reduction in gambling outcomes at 6 months compared to those provided access to the G-only intervention. DISCUSSION: This trial will expand upon the current research on Internet interventions for addictions and inform the development of treatments for those with co-occurring problem drinking and gambling. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03323606 . Registered on 24 October 2017.
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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 | 0.048 | 0.045 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.014 | 0.006 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.094 | 0.016 |
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".