P019: Examining non-suicidal self injury at a Canadian pediatric emergency department
Bibliographic record
Abstract
Introduction: Adolescents who present to emergency departments (ED) following intentional injuries present a challenge in terms of ascertaining their intent and risk for future self-injurious or suicidal behaviour. Our ED has seen an 80% increase in visits for mental health issues over the past ten years. As usage of our Emergency Mental Health and Addictions Services (EMHAS) team continues to rise, it is increasingly important to understand the incidence of NSSI among our youth, explore if NSSI is reported at triage and identify characteristics that may distinguish these adolescents from others presenting for mental health assessment. Methods: This is an exploratory research study using retrospective data. Patients who had an Emergency Mental Health Triage (EMHT) form on their health record from an ED visit between June 1, 2017 and May 31, 2018 were eligible. Trained research assistants, using a structured data collection form in REDCap. abstracted data from the EMHT form, the EMHAS Assessment form, the Assessment of Suicide Risk Inventory and our CHIRPP (Canadian Hospitals Injury Reporting and Prevention Program) database. We calculated kappa values and 95% confidence intervals to describe the extent to which the forms agree with respect to identifying NSSI. We will compare the cohort who reports NSSI with the cohort who does not report NSSI using chi-square statistics depending. We will use descriptive statistics to characterize the NSSI patients. Results: During the one-year study period 955 patients had an EMHT form completed. In preliminary analysis 558 (58.4%) reported a history of NSSI. Patients reported NSSI on both the EMHT form and the EMHAS assessment form 64.7% of the time (kappa 0.56) indicating moderate agreement. In patients with NSSI, 9.5% of patients reported it only at triage and 25.8% of patients reported it only during their EMHAS assessment. Between group comparisons and descriptive analysis is underway. Conclusion: More than half of youth triaged with an emergency mental health complaint in our ED reported a history of NSSI. Screening at triage was moderately effective in identifying adolescents with NSSI compared to an in-depth assessment by the mental health team. Further research is needed to clarify how NSSI relates to risk for suicide.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".