Mental Health Hospitalizations in Canadian Children, Adolescents, and Young Adults Over the COVID-19 Pandemic
Bibliographic record
Abstract
ImportanceThe COVID-19 pandemic resulted in multiple socially restrictive public health measures and reported negative mental health impacts in youths. Few studies have evaluated incidence rates by sex, region, and social determinants across an entire population.ObjectiveTo estimate the incidence of hospitalizations for mental health conditions, stratified by sex, region, and social determinants, in children and adolescents (hereinafter referred to asyouths) and young adults comparing the prepandemic and pandemic-prevalent periods.Design, Setting, and ParticipantsThis Canadian population-based repeated ecological cross-sectional study used health administrative data, extending from April 1, 2016, to March 31, 2023. All youths and young adults from 6 to 20 years of age in each of the Canadian provinces and territories were included. Data were provided by the Canadian Institute for Health Information for all provinces except Quebec; the Institut National d’Excellence en Santé et en Services Sociaux provided aggregate data for Quebec.ExposuresThe COVID-19–prevalent period, defined as April 1, 2020, to March 31, 2023.Main Outcomes and MeasuresThe main outcome measures were the prepandemic and COVID-19–prevalent incidence rates of hospitalizations for anxiety, mood disorders, eating disorders, schizophrenia or psychosis, personality disorders, substance-related disorders, and self-harm. Secondary measures included hospitalization differences by sex, age group, and deprivation as well as emergency department visits for the same mental health conditions.ResultsAmong Canadian youths and young adults during the study period, there were 218 101 hospitalizations for mental health conditions (ages 6 to 11 years: 5.8%, 12 to 17 years: 66.9%, and 18 to 20 years: 27.3%; 66.0% female). The rate of mental health hospitalizations decreased from 51.6 to 47.9 per 10 000 person-years between the prepandemic and COVID-19–prevalent years. However, the pandemic was associated with a rise in hospitalizations for anxiety (incidence rate ratio [IRR], 1.11; 95% CI, 1.08-1.14), personality disorders (IRR, 1.21; 95% CI, 1.16-1.25), suicide and self-harm (IRR, 1.10; 95% CI, 1.07-1.13), and eating disorders (IRR, 1.66; 95% CI, 1.60-1.73) in females and for eating disorders (IRR, 1.47; 95% CI, 1.31-1.67) in males. In both sexes, there was a decrease in hospitalizations for mood disorders (IRR, 0.84; 95% CI, 0.83-0.86), substance-related disorders (IRR, 0.83; 95% CI, 0.81-0.86), and other mental health disorders (IRR, 0.78; 95% CI, 0.76-0.79).Conclusions and RelevanceThis cross-sectional study of Canadian youths and young adults found a rise in anxiety, personality disorders, and suicidality in females and a rise in eating disorders in both sexes in the COVID-19–prevalent period. These results suggest that in future pandemics, policymakers should support youths and young adults who are particularly vulnerable to deterioration in mental health conditions during public health restrictions, including eating disorders, anxiety, and suicidality.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".