Motivational pathways from reward sensitivity and punishment sensitivity to gambling frequency and gambling-related problems.
Bibliographic record
Abstract
Motives for gambling have been shown to have an important role in gambling behavior, consistent with the literature on motives for substance use. While studies have demonstrated that traits related to sensitivity to reward (SR) and sensitivity to punishment (SP) are predictive of substance use motives, little research has examined the role of these traits in gambling motives. This study investigated motivational pathways from SR and SP to gambling frequency and gambling problems via specific gambling motives, while also taking into account history of substance use disorder (SUD). A community sample of gamblers (N = 248) completed self-report questionnaires assessing SR, SP, gambling frequency, gambling-related problems, and motives for gambling (social, negative affect, and enhancement/winning motives). Lifetime SUD was also assessed with a structured clinical interview. The results of a path analysis showed that SR was uniquely associated with all 3 types of gambling motives, whereas SP and SUD were associated with negative affect and enhancement/winning motives but not social motives. Also, both negative affect and enhancement/winning motives were associated with gambling problems, but only enhancement/winning motives were significantly related to gambling frequency. Analyses of indirect associations revealed significant indirect associations from SR, SP, and SUD to gambling frequency mediated through enhancement/winning motives and to gambling problems mediated through both negative affect and enhancement/winning motives. The findings highlight the importance of SR and SP as independent predictors of gambling motives and suggest that specific motivational pathways underlie their associations with gambling outcomes.
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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) | 0.000 | 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) | 0.000 | 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".