Randomized controlled trial of an Internet intervention for problem gambling provided with or without access to an Internet intervention for co-occurring mental health distress
Bibliographic record
Abstract
BACKGROUND AND AIMS: The current randomized controlled trial tested whether there was benefit to providing an online gambling intervention and a separate self-help mental health intervention for anxiety and depression (i.e. MoodGYM) (G + MH), compared to only a gambling intervention (G only) among people with co-occurring gambling problems and mental health distress. The primary outcome of interest was improvement in gambling outcomes. Secondary analyses also tested for the impact of the combined intervention on depression and anxiety outcomes. METHODS: Participants who were concerned about their gambling were recruited to help evaluate an online intervention for gamblers. Those who met criteria for problem gambling were randomized to receive either the G only or the G + MH intervention. Participants were also assessed for current mental health distress at baseline, with three quarters (n = 214) reporting significant current distress and form the sample for this study. Participants were followed-up at 3- and 6-months to assess changes in gambling status, and improvements in depression and anxiety. RESULTS: Follow-up rates were poor (47% completed at least one follow-up). While there were significant reductions in gambling outcomes, as well as on measures of current depression and anxiety, there was no significant difference in outcomes between participants receiving the G only versus the G + MH intervention. DISCUSSION AND CONCLUSION: There does not appear to be a benefit to providing access to an additional online mental health intervention to our online gambling intervention, at least among participants who are concerned about their gambling.Trial registration: ClinicalTrials.govNCT02800096; Registration date: June 14, 2016.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.026 | 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; 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".