Self-efficacy in pathological gambling treatment outcome: development of a gambling abstinence self-efficacy scale (GASS)
Bibliographic record
Abstract
A 21-item measure of gambling abstinence self-efficacy (GASS) was developed. A principal component analysis of 101 pathological gamblers supported the use of a total score that showed good internal (α=.93) and retest reliability (ICC (n=35)=.86) as well as four subscales: 1) winning/external situations (6 items, α=.91); 2) negative emotions (9 items, α=.87); 3) positive mood/testing/urges (3 items, α=.70); 4) social factors (3 items, α=.81). The total and subscales showed moderate relationships with single item ratings of confidence to abstain from gambling and weak or non-significance relationships with demographic and gambling-related variables. The total score and three of the subscales showed evidence of predictive validity for gamblers not currently involved with treatment. Higher self-efficacy was related to fewer days of gambling over a 12-month period. These results provide preliminary support for the reliability and validity of the GASS.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".