High rates of suicidality and parasuicidal behavior in individuals at clinical high-risk for psychosis: Implications for suicide risk assessment and suicide prevention
Bibliographic record
Abstract
BACKGROUND: Prior early psychosis studies have reported higher rates of suicidal ideation (SI) and parasuicidal behavior compared to healthy controls, but there is limited research examining rates and predictors of SI or protective factors in clinical high risk (CHR) youth. We investigated suicidality in CHR participants in the third sample of the North American Prodrome Longitudinal Study (NAPLS-3) and investigated associated demographic, life event, symptom, functional, treatment and outcome information. METHODS: The sample included 710 CHR (mean age 18.2, 45.8 % female) and 96 healthy control (HC) participants (mean age 18.6, 50.0 % female). Past SI, plans, self-harm and attempts were assessed via the clinician-administered Structured Assessment of Violence Risk in Youth (SAVRY) scale and the Calgary Depression Scale for Schizophrenia (CDSS). RESULTS: A significantly greater proportion of CHR participants compared to HC participants endorsed a history of SI or plan (30.7 % vs 0 %), a history of self-harm with no intent (25.6 % vs 4.2 %), serious suicide attempts (12 % vs 0 %) and suicide attempts designed to end in death (1 % vs 0 %). Within the CHR group, increasing levels of suicidality were significantly associated with worse symptoms; comorbid DSM diagnoses; decreased global and premorbid functioning; and stressful life events at baseline. Although parasuicidal behavior predicted future general symptoms including dysphoria and stress intolerance, it did not predict psychotic conversion at future timepoints. CONCLUSION: Suicidality is prominent in CHR youth and an indicator of greater acuity, highlighting the importance of suicide risk assessments and suicide prevention interventions specifically targeted to CHR youth.
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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 | 0.001 |
| 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".