Internet‐based <scp>CBT</scp> intervention for gamblers in Finland: Experiences from the field
Bibliographic record
Abstract
From September 2007 to May 2011 a total of 471 participants (325 males and 146 females) signed up for an 8-week Internet-based cognitive behavioral therapy offered for gamblers in Finland. Sixty-four percent of the participants were pathological gamblers (PGs) (NODS 5> points), 14% were problem gamblers (NODS 3-4 points) and 10% were at risk of gambling problems (NODS 1-2 points). Two hundred and twenty four participants completed the treatment and after the treatment period significant changes were found in the following variables: gambling related problems (NODS), gambling urge, impaired control of gambling, alcohol consumption (AUDIT-C), social consequences, gambling-related cognitive erroneous thoughts and depression (MARD-S). In this sample co-morbid alcohol consumption was stronger among males. The main finding of this study was that the onset age of gambling was associated with a greater amount of gambling-related cognitive erroneous thoughts.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".