Examining Risk Factors in the Cannabis–Suicide Link: Considering Trauma and Impulsivity among University Students
Bibliographic record
Abstract
Cannabis is a commonly used substance among university students that may have several negative health repercussions, including suicidal ideation (SI) and suicide attempts (SA). The factors that contribute to or help explain this relation remain uncertain. Earlier negative experiences, especially trauma encountered during early life, have been associated with the development of psychopathology upon later stressor encounters. In the current study, we examined the associations between SI and SA with problematic cannabis use among young adults and the role of earlier trauma experiences and trait impulsiveness in understanding this link. Among university students (N = 539), problematic cannabis use was moderately related to lifetime and past-12-months suicidal ideation and attempts. Impulsiveness mediated the relationship between problematic cannabis use and lifetime SI and SA. Moreover, previous life trauma moderated the relationship between problematic cannabis use and SA, such that the association between problematic cannabis use and SA was stronger among those who experienced high levels of trauma. These findings highlight behavioral and environmental factors that could predict suicide ideation and attempts among young cannabis users. Accordingly, trait impulsiveness and early trauma experiences should be considered, alongside problematic cannabis use, in suicide-risk detection and prevention strategies among young adults.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".