Association between stimulant and non-stimulant ADHD medications and completed suicide in adolescents and adults: A population-based nested case-control study
Bibliographic record
Abstract
INTRODUCTION: ADHD has been linked to an increased risk of completed suicide. The aim of this study was to assess the relationship between ADHD medication use and completed suicide. METHODS: This nested case-control study included individuals aged 12-49 in Quebec, Canada, diagnosed with ADHD and/or dispensed ADHD medication. Suicide cases (n = 472) between 2000 and 2021 were matched with 5 controls each (n = 2360) on date of birth, sex, and continuous public drug insurance coverage for at least 365 days before suicide death (index date). Multivariable conditional logistic regression was used to estimate the association between ADHD medication use and completed suicide. The association between specific ADHD medication types and completed suicide was also assessed. RESULTS: After controlling for potential confounders, no significant association was found between ADHD medication use and completed suicide in the overall sample, in individuals aged 12-24 and 25 to 49 years, and those with a prior ADHD physician diagnosis. No significant differences were found when comparing the use of non-stimulants only (aOR 1.27; 95 % CI: 0.62, 2.63), stimulants and non-stimulants (aOR 1.01; 95 % CI: 0.33, 3.08), and ADHD consultation without medication (aOR 0.94; 95 % CI: 0.69, 1.28) against stimulant-only use. CONCLUSION: Both stimulants and non-stimulants were not associated with the risk of completed suicide. These findings can inform clinical decision-making.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".