Mental Health Service Use Among Children and Youth in Ontario: Population-Based Trends Over Time
Bibliographic record
Abstract
OBJECTIVE: Little is known about mental health service use among Canadian children and youth. Our objective was to examine temporal trends in mental health service use across different sectors of the health care system among children and youth living in Ontario. METHODS: We conducted a population-based, repeated annual cross-sectional study of mental health service use, including mental health- and addictions-related emergency department (ED) visits, psychiatric hospitalizations, and mental health-related outpatient physician visits using linked health administrative databases. Subjects included Ontario residents between 10 and 24 years of age. We tested temporal trends between 2006 and 2011 using linear regression models. RESULTS: Between 2006 and 2011, the relative increase in rates of mental health-related ED visits and hospitalizations were 32.5% and 53.7%, respectively. The absolute increase in anxiety disorders, the most common reason for ED visits, was 2.2 per 1000 population (P < 0.001) while mood and affective disorders, the most common reason for hospitalizations, showed an increase of 0.6 per 1000 population (P < 0.01). The overall relative increase in rates of outpatient visits was 15.8%, with the largest absolute increase found among family physician visits (28.7 per 1000 population, P = 0.01). CONCLUSIONS: Mental health care use for children and youth is increasing over time in all sectors, but appears to be increasing at a greater rate in the acute care sector. Further research is required to understand whether the observed differences reflect difficulty with access to outpatient care.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".