Development and psychometric evaluation of a three‐dimensional Gambling Motives Questionnaire
Why this work is in the frame
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Bibliographic record
Abstract
AIMS: This study was designed to develop and evaluate a self-report measure of gambling motives. Participants A community-recruited sample of 193 gamblers (70% male; mean age = 35.5 years) were selected to fill two groups according to scores on the South Oaks Gambling Screen: probable pathological gamblers (PPG; n = 154) and non-pathological gamblers (NPG; n = 39). MEASURES: Participants completed a novel 15-item measure of gambling motives called the Gambling Motives Questionnaire (GMQ), which was modeled after the original Drinking Motives Questionnaire, as well as a variety of gambling behavior and problem criterion measures. RESULTS: An exploratory principal components analysis revealed three intercorrelated factors tapping enhancement (ENH), coping (COP), and social (SOC) motives, respectively. Each GMQ subscale showed good internal consistency (alphas > 0.80). The PPG group scored higher on all three scales than the NPG group, with larger differences for ENH and COP. In line with the clinical literature, PPG women scored higher than PPG men on the COP subscale but also, unexpectedly, on the SOC subscale. In concurrent validity analyses, ENH consistently predicted greater gambling behavior, and COP and ENH consistently predicted more severe gambling problems. With gambling behavior levels controlled, only COP remained a significant predictor of gambling problem severity. Finally, gender interacted with gambling motives in predicting gambling problem severity: COP predicted gambling problems more strongly in women, whereas ENH predicted gambling problems more strongly in men. CONCLUSIONS: The GMQ appears to be a promising tool for both research and clinical applications with problem gamblers.
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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