A Longitudinal Study of the Temporal Relation Between Problem Gambling and Mental and Substance Use Disorders Among Young Adults
Bibliographic record
Abstract
OBJECTIVE: Relatively little is known about the temporal relation between at-risk gambling or problem gambling (PG) and mental and substance use disorders (SUDs) in young adulthood. Our study aimed to examine whether past-year, at-risk, or PG is associated with incident mental disorders and SUDs (that is, depression, generalized anxiety disorder, obsessive-compulsive disorder [OCD], or alcohol dependence) and illegal drug use, and whether past-year mental disorders and SUDs and illegal drug use is associated with incident at-risk or PG. METHOD: Data for this longitudinal study were drawn from the Manitoba Longitudinal Study of Young Adults (MLSYA). Respondents aged 18 to 20 years in 2007 were followed prospectively for 5 years. RESULTS: In cross-sectional analyses, at-risk or PG was associated with increased odds of depression, OCD, alcohol dependence, and illegal drug use. In longitudinal analysis at-risk or PG at cycle 1 was associated with incident major depressive disorder, alcohol dependence, and illegal drug use in the follow-up period. Only illegal drug use at cycle 1 was associated with incident at-risk or PG during follow-up. CONCLUSIONS: At-risk or PG was associated with more new onset mental disorders and SUDs (depression, alcohol dependence, and illegal drug use), compared with the reverse (illegal drug use was the only association with new onset at-risk or PG). Preventing at-risk or PG from developing early in adulthood may correspond with decreases in new onset mental disorders and SUDs later in adulthood.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".