Sex differences among children, adolescents and young adults for mental health service use within inpatient and outpatient settings, before and during the COVID-19 pandemic: a population-based study in Ontario, Canada
Bibliographic record
Abstract
OBJECTIVES: The pandemic and public health response to contain the virus had impacts on many aspects of young people's lives including disruptions to daily routines, opportunities for social, academic, recreational engagement and early employment. Consequently, children, adolescents and young adults may have experienced mental health challenges that required use of mental health services. This study compared rates of use for inpatient and outpatient mental health services during the pandemic to pre-pandemic rates. DESIGN: Population-based repeated cross-sectional study. SETTING: Publicly delivered mental healthcare in primary and secondary settings within the province of Ontario, Canada. PARTICIPANTS: All children 6-12 years of age (n=2 043 977), adolescents 13-17 years (n=1 708 754) and young adults 18-24 years (n=2 286 544), living in Ontario and eligible for provincial health insurance between March 2016 and November 2021. PRIMARY OUTCOME MEASURES: to emergency departments and hospitalisations for: substance-related and addictive disorders, anxiety disorders, assault-related injuries, deliberate self-harm and eating disorders. All outcomes were analysed by cohort and sex. RESULTS: During the pandemic, observed outpatient visit rates were higher among young adults by 19.01% (95% CI: 15.56% to 22.37%; 209 vs 175 per 1000) and adolescent women 24.17% (95% CI: 18.93% to 29.15%; 131 vs 105 per 1000) for mood and anxiety disorders and remained higher than expected. Female adolescents had higher than expected usage of inpatient care for deliberate self-harm, eating disorders and assault-related injuries. CONCLUSIONS: Study results raise concerns over prolonged high rates of mental health use during the pandemic, particularly in female adolescents and young women, and highlights the need to better monitor and identify mental health outcomes associated with COVID-19 containment measures and to develop policies to address these concerns.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".