Pilot randomized controlled trial of an online intervention for problem gamblers
Bibliographic record
Abstract
INTRODUCTION: This pilot randomized controlled trial sought to evaluate whether an online intervention for problem gambling could lead to improved gambling outcomes compared to a no intervention control. Participants were recruited through a crowdsourcing platform. METHODS: Participants were recruited to complete an online survey about their gambling through the Mechanical Turk platform. Those who scored 5 or more on the Problem Gambling Severity Index and were thinking about quitting or reducing their gambling were invited to complete 6-week and 6-month follow-ups. Each potential participant who agreed was sent a unique password. Participants who used their password to log onto the study portal were randomized to either access an online intervention for gambling or to a no intervention control. RESULTS: A total of 321 participants were recruited, of which 87% and 88% were followed-up at 6 weeks and 6 months, respectively. Outcome analyses revealed that, while there were reductions in gambling from baseline to follow-ups, there was no significant observable impact of the online gambling intervention, as compared to a no intervention control condition. CONCLUSIONS: While the current trial observed no impact of the intervention, replication is merited with a larger sample size, and with participants who are not recruited through a crowdsourcing platform.Trial registration: ClinicalTrials.govNCT03124589.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".