Are early‐life antecedents of suicide mortality associated with psychiatric disorders and suicidal ideation in midlife?
Bibliographic record
Abstract
OBJECTIVE: To establish whether previously identified early-life antecedents of suicide mortality (i.e. low birthweight, younger maternal age, higher birth order, externalizing problems and adversities) are associated with proximal psychiatric disorders and suicidal ideation, which are themselves associated with an increased risk of suicide. METHODS: Participants were from the 1958 British birth-cohort (N = 8905) with information on prenatal/childhood experiences and the Clinical Interview Schedule-Revised at age 45 years. Outcomes were as follows: any internalizing disorder (anxiety disorder/depressive episode), depressive episode, alcohol use disorder and suicidal ideation. RESULTS: = 0.026) were associated with an increased risk of internalizing disorders. For example, the OR (95% CI) in fourth- or later-born children was 1.48 (1.06-2.07) and for young maternal age (<19 years) was 1.31 (0.89-1.91). Effect sizes were similar in magnitude for depressive episode and suicidal ideation, although associations did not reach conventional significance levels. No associations were found for low birthweight and externalizing problems (in males) and investigated outcomes. CONCLUSION: Associations for younger maternal age, higher birth order and adversities with adult internalizing disorders suggest that psychiatric disorders may be on the pathway linking some early-life factors and suicide.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".