Prevalence estimates of gambling and problem gambling among 13- to 15-year-old adolescents in Reykjavík: An examination of correlates of problem gambling and different accessibility to electronic gambling machines in Iceland
Bibliographic record
Abstract
This paper reports the main findings from a prevalence study of adolescent gambling and problem gambling among Icelandic adolescents. The final sample consisted of 3,511 pupils aged 13 to 15 in 25 primary schools in Reykjavík. The results indicated that 93% of adolescents had gambled some time in their life and 70% at least once in the preceding year. Problem gambling prevalence rates were evaluated with two gambling screens, American Psychological Association Diagnostic and Statistical Manual, 4th edition, Multiple-Response-Junior (DSM-IV-MR-J) and the South Oaks Gambling Screen Revised for Adolescents (SOGS-RA). The DSM-IV-MR-J identified 1.9% as problem gamblers, while SOGS-RA identified 2.8% as problem gamblers. The results also showed that problem gamblers reported more difficulties in school and used alcohol and other drugs more frequently than adolescents who gambled socially or not at all. Finally, evaluation of electronic gambling machine (EGM) accessibility revealed that gambling on low-stakes EGMs in public places was more common than on EGMs in arcades or bars and restaurants. The potential implications of these findings are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".