Exploring differences in substance use among emerging adults at-risk for problem gambling, and/or problem video gaming
Bibliographic record
Abstract
Both problem gambling (PG) and problem video gaming (PVG) contribute to physical, psychological, and interpersonal issues, and are associated with elevated substance use. This is particularly troublesome among emerging adults (18–27 years) who report high levels of substance use and represent a significant proportion of the gamblers and video game players. The present study assessed PG and PVG symptoms among 1, 621 emerging adults (54.5% female; M = 20.55, SD = 2.70) in conjunction with their frequency of using cigarettes, alcohol, marijuana, and other drugs (e.g. cocaine, opioids). Results revealed that 6.1% and 22.7% of emerging adults were at-risk for PG or PVG, respectively. Those at at-risk for either PG or PVG had used substances more frequently than those who were either non-problematic or at low-risk. A small subset of participants (2.2%) were at-risk for both PG and PVG and were the most likely to report using cigarettes, marijuana, and other drugs frequently, even after accounting for the effects of age, gender, race, and gambling and video gaming frequency. As such, exhibiting a risk for both PG and PVG places individuals at greater risk for substance use. The implications of these findings to policy and future research are discussed.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".