The Association Between Personality Disorder Traits and Suicidality Following Sudden Bereavement: A National Cross-Sectional Survey
Bibliographic record
Abstract
Personality disorder is associated with increased risk of suicidal behavior. The authors aimed to investigate the association between number of personality disorder traits and suicidality risk following sudden bereavement. A secondary analysis of cross-sectional data on 3,167 young adults in the United Kingdom who had experienced sudden bereavement investigated the association between number of traits (measured using a standardized screening instrument) and postbereavement suicide attempt and suicidal ideation. Using multivariable logistic regression, the authors found a linear relationship between number of traits and suicide attempt (adjusted odds ratio [AOR] = 1.36, 95% CI [1.23, 1.49]) and suicidal ideation (AOR = 1.31, 95% CI [1.25, 1.38]) following bereavement. This represented an increase in odds by 36% and 31%, respectively, for each additional personality trait. The authors suggest that individuals with a greater number of traits suggestive of a personality disorder diagnosis are at increased risk of suicidality after a negative life event.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".