Prospective associations between meth/amphetamine (speed) and MDMA (ecstasy) use and depressive symptoms in secondary school students
Bibliographic record
Abstract
BACKGROUND: Research has raised significant concern regarding the affective consequences of synthetic drug use. However, little evidence from well-controlled longitudinal studies exists on these consequences. The aim of this study was to determine whether use of meth/amphetamine (speed) and ±3,4-methylenedioxymethamphetamine (MDMA, ecstasy) is independently predictive of subsequent depressive symptoms in adolescents. METHODS: A sample of 3880 adolescents from secondary schools in disadvantaged areas of Quebec, Canada, were followed over time (2003-2008). Logistic regression was used to test the association between meth/amphetamine and MDMA use in grade 10 (ages 15-16 years) and elevated depressive symptoms on an abridged Center for Epidemiologic Studies-Depression scale in grade 11, controlling for pre-existing individual and contextual characteristics. RESULTS: After adjustment, both MDMA use (OR 1.7, 95% CI 1.1 to 2.6) and meth/amphetamine use (OR 1.6, 95% CI 1.1 to 2.3) in grade 10 significantly increased the odds of elevated depressive symptoms in grade 11. These relationships did not vary by gender or pre-existing depressive symptoms. Increased risk was particularly observed in concurrent usage (OR 1.9, 95% CI 1.2 to 2.9). CONCLUSIONS: Adolescent use of meth/amphetamine and MDMA (particularly concurrent use) is independently associated with subsequent depressive symptoms. Further enquiry must determine whether these associations reflect drug-induced neurotoxicity and whether adolescence is a period of increased vulnerability to the hazards of synthetic drug exposure.
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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 | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 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".