The Cumulative Incidence of Self-Reported Suicide-Related Thoughts and Attempts in Young Canadians
Bibliographic record
Abstract
OBJECTIVE: To estimate the cumulative incidence of self-reported suicide-related thoughts (SRTs) and suicide attempts (SAs) in males and females from 11 to 25 years of age in Canada. METHODS: A cohort study was conducted by linking cycles 2 to 8 from the National Longitudinal Survey of Children and Youth, a representative survey of Canadians aged 11 to 25 years conducted from 1996 to 2009. The 11- to 25-year cumulative incidence of self-reported SRTs and SAs (with suicidal intent) was estimated in males and females using a novel application of a counting process approach to account for discontinuous risk intervals between survey cycles. RESULTS: The risk of SRTs was 29% (95% confidence interval [CI], 26% to 31%) in females and 19% (95% CI, 16% to 23%) in males. The risk of SAs was 16% (95% CI, 14% to 19%) in females and 7% (95% CI, 6% to 8%) in males. Over 70% of SRTs and SAs first occur between 11 and 16 years of age and 30% between 11 and 13 years of age, respectively. CONCLUSIONS: The risk of SRTs and SAs is high in young Canadians, with most events first occurring in early to mid-adolescence and possibly earlier. Females are at a higher risk compared to males. This research underscores the need for better longitudinal surveillance of SRTs and SAs in the population. A counting process framework could be useful for future research using existing longitudinal surveys suffering from design limitations relating to gaps in respondent follow-up. Furthermore, these findings have implications for younger SRT and SA risk management by clinicians and earlier implementation of suicide prevention programs.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".