Sexual diversity, adolescent mental health, and adult cannabis use: Longitudinal associations through cannabis use motives
Bibliographic record
Abstract
PURPOSE: We examined prospective pathways between adolescent mental health and early adulthood cannabis use (CU) by sexual diversity, and the potential explanatory role of CU motives, accounting for confounders (demographics, CU frequency in adolescence). METHODS: Participants from the Quebec Longitudinal Study of Child Development self-reported at 17 years on depressive symptoms, anxiety symptoms, and CU frequency, and at 23 years on CU motives, frequency and problems (471 participants total; 425 heterosexual; 46 sexually diverse). RESULTS: Depression - but not anxiety - symptoms at 17 years predicted CU problems at 23 years among sexually diverse participants only. This association was fully explained through coping motives, which were strongly predicted by depression symptoms in sexually diverse youth. While coping motives also predicted CU problems in heterosexual participants, coping motives were not predicted by mental health at 17 in this group. Depression symptoms at 17 also predicted social motives for CU among sexually diverse participants only, but this was not associated with CU frequency and problems. Finally, enhancement motives predicted CU problems at 23 years in both heterosexual and sexually diverse participants, but were not predicted by mental health at 17 years. CONCLUSIONS: Among sexually diverse youth, depression symptoms in adolescence may confer particular risk for later CU problems through CU for coping purposes. Increasing coping resources for sexually diverse adolescents experiencing psychological distress could help prevent later CU problems.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".