An extended model of gambling motives: The first results with the long and short versions of the gambling motives questionnaire-revised
Bibliographic record
Abstract
Motives underlying addictions have been widely studied, using validated tools such as the Gambling Motives Questionnaire (GMQ) (Stewart and Zack, 2008). Nevertheless, subsequent studies have suggested the need to extend this model. The present paper aimed to identify potential additional factors, such as escapism, omnipotence, pleasure and financial motives, in addition to the social, enhancement and coping aspects already included. A total of 40 motivational items (adding 25 additional items to the original GMQ items) were analysed within two datasets. Sample 1 was a player panel from a gambling service provider ( N = 1829; mean age: 42.4 [SD = 13.3]; Females: 30 % [ n = 548]), while Sample 2 consisted of a nationally representative sample of the Hungarian population ( N = 437; mean age: 42.9 [SD = 13.55]; Females: 49.2 % [ N = 215]). Exploratory Factor Analysis on Sample 1 identified four factors (including a total of 27 items): coping/escapism, social motives, enhancement/pleasure, and financial motives. The four-factor structure was confirmed on Sample 2 with confirmatory factor analysis showing adequate model fit (CFI = 0.987; TLI = 0.986; RMSEA[CI] = 0.047 [0.041–0.052]); however, high inter-factor correlations were evident in the general population sample. A shorter, 14-item version of the scale was also suggested. Although the newly identified motives overlap with the original ones, the content of the factors enables the inclusion of certain aspects, like escapism within the coping factor, that proved to be the most important in relation to other potentially addictive behaviours. This suggests that examining the role of motives in gambling may be crucial in differentiating between problem gambling and recreational gambling. • Examining the role of motives in addictions is crucial in understanding and preventing them. • Coping, social, enhancement or financial motives predict gambling severity. • Escapism motive might be pivotal in the development of addictive behaviours. • Social motives for gambling might play a protective role. • GMQ-R-27 is a revised and valid measure of gambling motives, including new aspects like escapism.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".