New and continuing physician-based outpatient mental health care among children and adolescents during the COVID-19 pandemic in Ontario, Canada: a population-based study
Bibliographic record
Abstract
Objective: To assess physician-based mental health care utilization during the COVID-19 pandemic among children and adolescents new to care and those already engaged with mental health services, and to evaluate differences by sociodemographic factors. Study design: We performed a population-based repeated cross-sectional study using linked health and administrative databases in Ontario, Canada among all children and adolescents 3-17 years. We examined outpatient visit rates per 1,000 population for mental health concerns for those new to care (no physician-based mental healthcare for ≥1 year) and those with continuing care needs (any physician-based mental healthcare <1 year) following onset of the pandemic. Results: Among ~2.5 million children and adolescents (48.7% female, mean age 10.1 ± 4.3 years), expected monthly mental health outpatient visits were 1.5/1,000 for those new to mental health care and 5.4/1,000 for those already engaged in care. Following onset of the pandemic, visit rates for both groups were above expected [adjusted rate ratio (aRR) 1.22, 95% CI 1.17, 1.27; aRR 1.10, 95% CI 1.07, 1.12] for new and continuing care, respectively. The greatest increase above expected was among females (new: aRR 1.33, 95% CI 1.25, 1.42; continuing: aRR 1.22 95% CI 1.17, 1.26) and adolescents ages 13-17 years (new: aRR 1.31, 95% CI 1.27, 1.34; continuing: aRR 1.15 95% CI 1.13, 1.17). Mood and anxiety concerns were prominent among those new to care. Conclusion: In the 18 months following onset of the pandemic, outpatient mental health care utilization increased for those with new and continuing care needs, especially among females and adolescents.
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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 | 0.001 |
| 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) | 0.001 | 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".