Personality disorder risk factors for suicide attempts over 10 years of follow-up.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Identifying personality disorder (PD) risk factors for suicide attempts is an important consideration for research and clinical care alike. However, most prior research has focused on single PDs or categorical PD diagnoses without considering unique influences of different PDs or of severity (sum) of PD criteria on the risk for suicide-related outcomes. This has usually been done with cross-sectional or retrospective assessment methods. Rarely are dimensional models of PDs examined in longitudinal, naturalistic prospective designs. In addition, it is important to consider divergent risk factors in predicting the risk of ever making a suicide attempt versus the risk of making an increasing number of attempts within the same model. This study examined 431 participants who were followed for 10 years in the Collaborative Longitudinal Personality Disorders Study. Baseline assessments of personality disorder criteria were summed as dimensional counts of personality pathology and examined as predictors of suicide attempts reported at annual interviews throughout the 10-year follow-up period. We used univariate and multivariate zero-inflated Poisson regression models to simultaneously evaluate PD risk factors for ever attempting suicide and for increasing numbers of attempts among attempters. Consistent with prior research, borderline PD was uniquely associated with ever attempting. However, only narcissistic PD was uniquely associated with an increasing number of attempts. These findings highlight the relevance of both borderline and narcissistic personality pathology as unique contributors to suicide-related outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it