Childhood trajectories of anxiousness and disruptiveness explain the association between early-life adversity and attempted suicide
Bibliographic record
Abstract
BACKGROUND: Suicidal behavior is frequently associated with a history of childhood abuse yet it remains unclear precisely how early life adversity may increase suicide risk later in life. As such, our aim was to examine whether lifetime trajectories of disruptiveness and anxiousness trait dysregulation explain the association between childhood adversity and suicidal behavior; and moreover, to test the potential modifying effects of mental disorders on these associations. METHOD: A sample of 1776 individuals from a prospective school-based cohort followed longitudinally for over 22 years was investigated. We tested the influence of disruptiveness and anxiousness trajectories from age 6 to 12 years on the association between childhood adversity (i.e. sexual and physical abuse) and history of suicide attempts (SA) using logistic regression models. Both adolescent externalizing and internalizing Axis I disorders and gender were tested as potential modifiers of these associations. RESULTS: Four distinct longitudinal trajectories were identified for both disruptiveness and anxiousness. The high disruptiveness trajectory accounted for the association between childhood adversity and SA, but only for females. The high anxiousness trajectory also explained the association between adversity and SA; however, in this case it was not sex but mental disorders that influenced the potency of the mediating effect. More specifically, anxiousness fully explained the effect of adversity on SA in the presence of externalizing disorders, whereas in the absence of these disorders, this effect was significantly attenuated. CONCLUSIONS: This study provides evidence that both disruptiveness and anxiousness play an important role in explaining the relationship between childhood adversity and SA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".