Internet-based interventions for disordered gamblers: study protocol for a randomized controlled trial of online self-directed cognitive-behavioural motivational therapy
Bibliographic record
Abstract
BACKGROUND: Gambling disorders affect about one percent of adults. Effective treatments are available but only a small proportion of affected individuals will choose to attend formal treatment. As a result, self-directed treatments have also been developed and found effective. Self-directed treatments provide individuals with information and support to initiate a recovery program without attending formal treatment. In previous research we developed an telephone-based intervention package that helps people to be motivated to tackle their gambling problem and to use basic behavioral and cognitive change strategies. The present study will investigate the efficacy of this self-directed intervention offered as a free online resource. The Internet is an excellent modality in which to offer self-directed treatment for gambling problems. The Internet is increasingly accessible to members of the public and is frequently used to access health-related information. Online gambling sites are also becoming more popular gambling platforms. METHOD/DESIGN: A randomized clinical trial (N=180) will be conducted in which individuals with gambling problems who are not interested in attending formal treatment are randomly assigned to have access to an online self-directed intervention or to a comparison condition. The comparison condition will be an alternative website that offers a self-assessment of gambling involvement and gambling-related problems. The participant's use of the resources and their gambling involvement (days of gambling, dollars loss) and their gambling problems will be tracked for a twelve month follow-up period. DISCUSSION: The results of this research will be important for informing policy-makers who are developing treatment systems. TRIAL REGISTRATION: ISRCTN06220098.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.030 | 0.021 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.005 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.100 | 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".