Suicidal transition rates and their predictors in the adult general population: a repeated survey over 21 years in France
Bibliographic record
Abstract
BACKGROUND: The "suicidal transition" from ideation to an act has become a specific topic of research. However, rates in the general population, variations across time and risk factors are unclear. METHODS: among 18-75-year-olds in France. Seven independent samples interviewed between 2000 and 2021 (total N = 133,827 people; 51.3% females) were questioned about suicidal ideation and attempts over the previous 12 months. Transition was calculated as the weighted ratio of attempt on ideation 12-month rates. RESULTS: Mean 12-month rates of suicidal ideation, attempts and transition were 4.7% (95% Confidence Interval (CI) (4.6-4.8)), 0.5% (95% CI (0.4-0.5)) and 7.7% (95% CI (6.8-8.6)), respectively. Transition rates varied between 4.5 and 11.9% across surveys. In multivariable analyses, higher transitions rates were associated with a previous suicide attempt (adjusted Odds Ratio (aOR) = 11.1 95% CI (7.9-15.6)); 18-25 vs 26-55-year-olds (1.8 95% CI (1.2-2.8)); lower vs higher income (1.7 95% CI (1.0-2.7); and lower vs higher professional categories (aOR around 1.9). No significant association was found with gender, education level, employment status, living alone, urbanicity, current major depression, daily smoking, weekly heavy drinking, cannabis use, and body mass index. CONCLUSIONS: Most people with suicidal ideation do not attempt suicide. These findings emphasize the need to avoid generic terms such as "suicidality", and to increase research on suicidal transition to improve prevention and prediction. They may also inform the organization of suicide prevention in the general population.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".