A Multivariate Evaluation of 25 Proximal and Distal Risk-Factors for Gambling-Related Harm
Bibliographic record
Abstract
Individual differences in the risk of developing gambling-related harm play an important role in theoretical models and practical interventions. The present study attempted comprehensive measurement and evaluation of 25 known risk factors for gambling-related harm in order to determine which factors provided large and unique explanatory power. We surveyed 1650 regular gamblers from an online panel, screening in 1174 (466 male) who passed all checks of attention and response consistency. We evaluated each risk factor based on bivariate correlations with harms, then made separate multivariate evaluations of proximal (e.g., gambling motivations) and distal (e.g., religiosity) risk factors. Almost all bivariate correlations were significant, but most distal factors were not significant in multivariate models. Trait impulsivity was the most important risk factor by a large margin. Excessive consumption, less use of safe gambling practices, and more fallacies were key proximal risks of harm. Many well-known correlates of gambling harm (e.g., youth, lower educational attainment) do not show a direct role in the development of gambling harm when controlling for other factors. The results support theoretical models that emphasise early conditioning and biological vulnerability (manifested through impulsivity). Since maladaptive cognitive and behavioural schemas appear to be more important than motivations (e.g., escape, excitement, ego), interventions may benefit by targeting these proximal drivers of harm.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".