329 Identifying priority areas for public health action to reduce youth suicide and self-harm in British Columbia, Canada
Bibliographic record
Abstract
Background Suicide is a leading cause of injury deaths, and among all causes of deaths for 10–24-year-olds in British Columbia (B.C.), Canada. Similarly, self-harm (both suicide attempts and non-suicidal self-injury) is a leading cause of hospitalization among children and youth. Given that youth suicide and self-harm (YSSH) is a priority for the province, the BC Injury Prevention Committee (BCIPC) formed a YSSH working group, with the mandate of identifying YSSH public health actions for prevention. Objective This presentation outlines steps taken by the BCIPC YSSH working group to identify priority areas for public health action that can reduce the incidence of suicide and self-harm among children and youth. Programme Description Following data analyses, a literature synthesis and extensive environmental scans, a modified Delphi approach was implemented to rank 11 potential focus areas, based on a pre-determined set of criteria (effectiveness, acceptability, feasibility, evaluability and equity). Outcomes and Learnings Three top-ranking interventions were approved for YSSH prevention efforts: ‘the creation of supportive environments and reduction of adverse childhood experiences’, ‘means restriction’, and ‘provide learning opportunities to children and youth in schools’. In each area of prevention, it was agreed to fully consider the particular needs of over-represented sub-populations, including children and youth who are gender diverse as well as those who are newcomers to Canada. Given the importance of reconciliation with Indigenous peoples, a dedicated stream of work was created to respond to the needs and direction of Indigenous peoples. Implications This initiative allowed public health injury prevention to define its role in YSSH prevention – a priority for the Province - using a defensible process that used an evidence-informed prioritization process, data-driven situational analysis, rigorous evidence synthesis, in-depth regional and provincial environmental scans, and multi-disciplinary teamwork. Conclusions The group is currently working to identify specific actions in the three areas prioritized for YSSH public health actions for prevention at the provincial and regional levels. The group is also learning more about Indigenous life promotion approaches and respectful engagement, recognizing that priorities and actions in this area must be determined and led by First Nations, Métis and Inuit organizations and communities.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.011 | 0.001 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".