Identifying correlates of suicide attempts in suicidal ideators: a population-based study
Bibliographic record
Abstract
BACKGROUND: Identification of factors that distinguish between ideators who act on their suicidal thoughts from those who do not is an important clinical and research objective. METHOD: We examined correlates of suicide attempts in suicidal ideators, members of a French-Canadian, school-based cohort. Suicidal thoughts were evaluated in adolescence and early adulthood in the total sample of suicidal ideators, who were then stratified into subgroups consisting of persistent ideators, male ideators and female ideators. RESULTS: In addition to persistent suicidal ideas [odds ratios (ORs) 2.1-2.8], Axis I psychopathology, female gender and childhood sexual abuse (CSA) were the most consistent correlates of suicide attempts. Externalizing disorders were significant contributors in persistent ideators [drug misuse: OR 2.8, 95% confidence interval (CI) 1.1-6.9] and in male ideators in particular (disruptive disorders: OR 5.9, 95% CI 2.2-16.0). In women, psychiatric co-morbidity also had a significant effect (OR 1.6, 95% CI 1.1-2.1). CSA was of relevance in both women (OR 1.2, 95% CI 1.1-1.4) and persistent ideators (OR 1.3, 95% CI 1.1-1.5). Personality traits showed gender-specific contribution with affective instability (OR 1.1, 95% CI 1.01-1.1) and anxiousness (OR 1.3, 95% CI 1.1-1.7) contributing in men and disruptive aggression (OR 1.1, 95% CI 1.03-1.3) in women. CONCLUSIONS: Correlates of suicide attempts in suicidal ideators vary as a function of the persistence of suicidal ideas and gender. This heterogeneity across subgroups of suicidal ideators may be attributed, at least in part, to differences between the sexes, early environmental adversity, maladaptive personality, and psychiatric symptoms. Further exploration and continued prospective follow-up is necessary to examine these possibilities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".