Emergency department visits and hospital admissions for suicidal ideation, self-poisoning and self-harm among adolescents in Canada during the COVID-19 pandemic
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic had profound effects on the mental wellbeing of adolescents. We sought to evaluate pandemic-related changes in health care use for suicidal ideation, self-poisoning and self-harm. METHODS: We obtained data from the Canadian Institute for Health Information on emergency department visits and hospital admissions from April 2015 to March 2022 among adolescents aged 10-18 years in Canada. We calculated the quarterly percentage of emergency department visits and hospital admissions for a composite outcome comprising suicidal ideation, self-poisoning and self-harm relative to all-cause emergency department visits and hospital admissions. We used interrupted time-series methods to compare changes in levels and trends of these outcomes between the prepandemic (Apr. 1, 2015-Mar. 1, 2020) and pandemic (Apr. 1, 2020-Mar. 31, 2022) periods. RESULTS: The average quarterly percentage of emergency department visits for suicidal ideation, self-poisoning and self-harm relative to all-cause emergency department visits was 2.30% during the prepandemic period and 3.52% during the pandemic period. The level (0.08%, 95% confidence interval [CI] -0.79% to 0.95%) or trend (0.07% per quarter, 95% CI -0.14% to 0.28%) of this percentage did not change significantly between periods. The average quarterly percentage of hospital admissions for the composite outcome relative to all-cause admissions was 7.18% during the prepandemic period and 8.96% during the pandemic period. This percentage showed no significant change in level (-0.70%, 95% CI -1.90% to 0.50%), but did show a significantly increasing trend (0.36% per quarter; 95% 0.07% to 0.65%) during the pandemic versus prepandemic periods, specifically among females aged 10-14 years (0.76% per quarter, 95% CI 0.22% to 1.30%) and females aged 15-18 years (0.56% per quarter, 95% CI 0.31% to 0.81%). INTERPRETATION: The quarterly change in the percentage of hospital admissions for suicidal ideation, self-poisoning and self-harm increased among adolescent females in Canada during the first 2 years of the COVID-19 pandemic. This underscores the need to promote public health policies that mitigate the impact of the pandemic on adolescent mental health.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".