Personality factors associated with problem gambling behavior in university students
Bibliographic record
Abstract
This study investigated sex differences and personality factors associated with gambling behavior in a non-clinical sample of young men and women. The participants were 212 university students (62 men and 150 women) and their mean age was 18.7 years. The South Oaks Gambling Screen (SOGS) was used to assess problem gambling behavior and the NEO Five-Factor Inventory Form S (College Age) was used to assess personality traits. The results indicated that men were more likely to endorse indicators of gambling problems than were women, with sex differences in different endorsed gambling activities. Of the five personality factors investigated, low Openness to experience and low Agreeableness were most strongly associated with higher scores on the SOGS, indicative of potentially problematic gambling behavior. Further analysis illustrated that for men in particular, low Openness to experience was a key personality factor in relation to higher SOGS scores.
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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) | 0.000 | 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".