Assessing Suicidal Youth with Antisocial, Borderline, or Narcissistic Personality Disorder
Bibliographic record
Abstract
OBJECTIVE: This paper has 3 objectives. First, we review the epidemiologic evidence for the association between suicidal behaviour and suicide in individuals diagnosed with antisocial, borderline, or narcissistic personality disorder. Second, we examine whether any potentially modifiable risk factors are associated with these diagnoses, based on existing empirical evidence. Last, we discuss clinical approaches to assessing youth with antisocial, borderline, or narcissistic personality disorder presenting at risk for suicide. METHOD: We reviewed the English-language literature for the last 12 years (from January 1, 1991, to December 31, 2002), using as search terms the names of the 3 disorders, as well as the key words suicide, suicidal behaviour, youth, and adolescents. RESULTS: Patients with antisocial or borderline personality disorder are likely to be at increased risk for suicidal behaviour when they demonstrate such comorbid disorders as major depressive episodes or substance abuse disorders, when they experience recent negative life events, or when they have a history of childhood sexual abuse. CONCLUSIONS: For patients with antisocial personality disorder, the risk of violence has to be judged in addition to the risk of suicide or self-harm. For patients with borderline personality disorder, interventions are determined by differentiating acute-on-chronic from chronic risk of suicidal behaviour. Finally, patients with narcissistic personality disorder can be at high risk for suicide during periods when they are not suffering from clinical depression. These episodes can seem to be unpredictable.
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.000 |
| 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".