Longitudinal interplay between gambling participation and substance use during late adolescence: A genetically-informed study.
Bibliographic record
Abstract
Substance use and gambling participation during adolescence are correlated, both concurrently and over time. It is unclear, however, whether this association can be explained by common underlying genetic vulnerabilities or environmental factors. The present study explored the concurrent and longitudinal associations between substance use and gambling participation and their genetic and environmental underpinnings by late adolescence. Participants were 373 pairs of monozygotic and dizygotic twins. Self-reports of substance use and gambling participation were collected at Ages 17 and 19 years. Results showed concurrent associations between substance use and gambling participation as well as a small, but significant unidirectional longitudinal association over time from substance use to gambling participation. Common genetic factors largely accounted for the concurrent associations at Ages 17 and 19, as well as for the unidirectional longitudinal association between substance use and gambling participation. Substance use and gambling participation share a common genetic component that account for most of their concurrent and longitudinal links during late adolescence. However, these behaviors are also influenced by specific environmental factors. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".