Examining lottery play and risk among young people in Great Britain
Bibliographic record
Abstract
Purpose & Significance: Despite the popularity of lottery and scratchcards and some evidence of gambling problems among players, limited research focuses on the risks of lottery and scratchcard play and predictors of problems, especially among young people. The purpose of this project is to examine whether lottery and scratchcard participation is related to gambling problems among 16-24 year olds in Great Britain and whether general and mental health and gambling behaviours explain this relationship. Methodology: Samples of 16-24 year olds were pooled from the 2012, 2015, and 2016 Gambling in England and Scotland: Combined Data from the Health Survey for England and the Scottish Health Survey (n=3,454). Bivariate analyses and Firth method logistic regression were used to examine the relationship between past-year lottery and scratchcard participation and gambling problems, assessing the attenuating role of mental wellbeing, mental health disorders, self-assessed general health, and playing other games in past year. Results: There is a significant association between scratchcard play and gambling problems. The association somewhat attenuated but remained significant after taking into account wellbeing, mental health disorders, general health, and engagement in other gambling activities. Findings also show that gambling problems are further predicted by age (20-24 years), gender (male), lower wellbeing, and playing any other gambling games. Implications: Results are valuable for informing youth-focused education, decisions around the legal age for National Lottery products, and the development of safer gambling initiatives for high risk groups and behaviours, such as scratchcard play.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".