Enhancing youth suicide prevention: The critical role of family involvement in screening, intervention, and postvention.
Bibliographic record
Abstract
BACKGROUND: Suicide often arises from a collapse of personal identity and life narrative; yet, traditional risk assessments frequently overlook these deeper disruptions. Narrative identity theory offers a lens to understand suicidality as a crisis of selfhood and meaning. AIM: This article introduces a clinically applicable method to assess suicide risk through three core narrative domains: character (who the person is), setting (where they come from), and script (where they believe they are going). METHOD: Drawing on narrative identity theory and existential psychology, the proposed approach guides clinicians to identify disconnections in role, belonging, and future orientation. Story-based tools for assessment and intervention are presented to support the reconstruction of narrative coherence and personal agency. RESULTS: Mapping narrative disruptions across character, setting, and script enables early identification of suicide risk, especially in individuals who may not meet traditional thresholds for acute risk. Narrative reauthoring interventions help reestablish continuity, coherence, and hope. CONCLUSION: This narrative framework enhances suicide prevention by moving beyond symptom management toward meaning-centered engagement. By helping individuals reweave fragmented life stories, clinicians can more effectively intervene in the existential and identity-based dimensions of suicidality. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".