Striving Towards National Lower-Risk Gambling Guidelines: An Empirical Investigation Among a Sample of Swedish Gamblers
Bibliographic record
Abstract
Several countries, including Canada and Australia, have developed public health-based lower-risk gambling limits to differentiate lower-risk from higher-risk gambling. This study aimed to identify a preliminary set of lower-risk gambling limits (gambling frequency, duration, expenditure, expenditure as a proportion of personal net income, and diversity), and investigate if gambling types are linked to additional harms, in a Swedish context. The study involved secondary analyses of two online survey studies using the Gambling Disorder Identification Test (GDIT). Receiver operating curve analyses were conducted in relation to both + 1 and + 2 gambling-related harms in a sample of 705 past-year gamblers. Potential lower-risk limits ranges identified were: gambling frequency of "2-3 times a week" to "4 or more times a week" (8-16 times monthly); gambling duration of 6 to 15 h per month; gambling expenditure of 2,000 SEK (approximately $USD190) per month; gambling expenditure as a proportion of personal net income of 5%; and gambling diversity of only one problematic gambling type. Gambling on slots and sports betting were associated with gambling-related harms. The lower-risk limits in the current study were higher than in previous studies, which may be explained by the large proportion of support- or treatment-seeking gamblers with high rates of problem gambling and problematic online gambling in the study sample. An international consensus-based framework on gambling consumption is warranted, with lower-risk limits validated in future empirical studies using larger datasets collected from the Swedish general population.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".