Greater impulsivity is associated with a reduced propensity to cash out of bets
Why this work is in the frame
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Bibliographic record
Abstract
A common feature of contemporary sports-betting apps is ‘instant cash-out’, which allows users to settle a bet early in exchange for a discounted immediate payout. Despite high prevalence and links with gambling-related harm, relatively little is known about how personality traits associated with gambling, such as impulsivity, predict instant cash-out usage. To address this question, we recruited 145 general-population adult participants (69 men, 66 women, 10 non-binary or undisclosed; Mage = 36.3, SD = 10.7; participants resided in Australia, Canada, Ireland, New Zealand, the UK, or the USA) to complete five self-report questionnaires related to impulsivity, as well as the Problem Gambling Severity Index (PGSI), and a validated cognitive task measuring individual differences in cash-out frequency. We then assessed how cash-out frequency in the behavioral task was associated with both self-reported impulsivity and PGSI. We found that cash-out frequency was negatively correlated both with PGSI scores and with a number of impulsivity-related traits including Dysfunctional Impulsivity, Lack of Premeditation, Positive Urgency, Sensation Seeking, and Fun Seeking. An exploratory factor analysis revealed that higher scores on a latent ‘Dysfunctional Impulsivity’ factor were negatively associated with cash-out frequency overall, whereas higher scores on an ‘Inhibition and Inflexibility’ factor predicted higher cash-out frequency specifically for bets with a low win probability. Taken together, results suggest that instant cash-out may primarily appeal to less impulsive people and those with lower PGSI scores. This raises the possibility that instant cash-out may specifically facilitate increased gambling behaviors among people with less prior experience of gambling.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.033 |
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