A suicide prevention strategy for youth presenting to the emergency department with suicide related behaviour: protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Suicide is a leading cause of death among adolescents in North America. Youth who present to the Emergency Department (ED) with acute suicidality are at increased risk for eventual death by suicide, thereby presenting an opportunity for secondary prevention of suicide. The current study evaluates the effectiveness of a standardized individual and family-based suicidal behaviour risk reduction intervention targeting adolescents at high-risk for suicide. METHODS: A randomized controlled trial (RCT) will be conducted to evaluate the effectiveness of a manualized youth- and family- based suicide prevention strategy (SPS) as compared with case navigation (NAV) among adolescents aged 12 to 18 years of age who present to the ED with acute suicidal ideation (SI) or suicide risk behaviours (SRB). We will recruit 128 participants and compare psychiatric symptoms including SI/SRB, family communication, and functional impairment at baseline and follow-ups (post-intervention [6 weeks], 24 weeks). The primary outcome is change in suicidal ideation measured with the Suicide Ideation Questionnaire- Junior. SRBs are measured with the Suicide Behaviour Questionnaire. Secondary outcomes are change in depressive and anxious symptoms measured with semi-structured psychiatric interview and Screen for Child Anxiety Related Disorders; acute mental health crises measured by urgent medical (including ED) visits; family communication measured with Conflict Behaviour Questionnaire, functional impairment measured by Columbia Impairment Scale; cost effectiveness, and fidelity of implementation measured by audio recording and fidelity checklist. DISCUSSION: Results of this study will inform a larger multi-centre RCT that will include both community and academic hospitals in urban and rural settings. Study results will be shared at international psychiatry and emergency medicine meetings, in local rounds, and via publication in academic journals and clinician-oriented newsletters. If effective, the intervention may provide a brief, scalable, and transportable treatment program that may be implemented in a variety of settings, including those in which access to children's mental health care services is challenging. TRIAL REGISTRATION: ClinicalTrials.gov: NCT03488602, retrospectively registered April 4, 2018.
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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 | 0.041 | 0.039 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.017 | 0.009 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.090 | 0.014 |
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".