Reward-Related Decision-Making in Current and Past Disordered Gambling: Implications for Impulsive Choice and Risk Preference in the Maintenance of Gambling Disorder
Bibliographic record
Abstract
Impulsive reward-related decision-making (RRDM) is robustly associated with gambling disorder (GD), although its role in the development and perpetuation of GD is still being investigated. This project sought to examine the possible roles of impulsive and risky choice, two aspects of RRDM, in the perpetuation of GD. Additionally, the potential moderating role of comorbid substance misuse was considered. A total of 434 participants with symptoms of current GD and symptoms of concurrent substance use disorder (SUD; n = 105), current GD with past SUD ( n = 98), past GD with current SUD ( n = 53), or past GD with past substance use disorder (SUD; n = 92), and 96 healthy controls were recruited through MTurk. Participants completed a randomly adjusting delay discounting (a measure of impulsive choice) and probabilistic discounting (a measure of risky choice) task and self-report questionnaires of gambling participation, GD and SUD symptomology, and trait impulsivity. Although control participants showed significantly greater delay discounting compared to individuals with a current or history of GD, no significant group differences emerged between individuals with current GD or a history of GD. Individuals with current GD showed significantly less probabilistic discounting compared to individuals with a history of GD and control participants showed the greatest rates of probabilistic discounting. These effects remained after controlling for lifetime gambling symptom severity and trait impulsivity. Overall, these findings suggest a potential maintaining role of risky choice in gambling disorder, but do not support a maintaining role for impulsive choice.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".