Cognitive Treatment of Pathological Gambling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study evaluated the efficacy of a cognitive treatment package for pathological gambling. Sixty-six gamblers, meeting DSM-IV criteria for pathological gambling, were randomly assigned to treatment or wait-list control conditions. Cognitive correction techniques were used first to target gamblers' erroneous perceptions about randomness and then to address issues of relapse prevention. The dependent measures used were the South Oaks Gambling Screen, the number of DSM-IV criteria for pathological gambling met by participants, as well as gamblers' perception of control, frequency of gambling, perceived self-efficacy, and desire to gamble. Posttest results indicated highly significant changes in the treatment group on all outcome measures, and analysis of data from 6- and 12-month follow-ups revealed maintenance of therapeutic gains. Recommendations for clinical interventions are discussed, focusing on the cognitive correction of erroneous perceptions toward the notion of randomness.
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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) | 0.000 | 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 it