Social Disparities in Mental Health Service Use Among Children and Youth in Ontario: Evidence From a General, Population-Based Survey
Bibliographic record
Abstract
OBJECTIVES: To examine differences in mental health-related service contacts between immigrant, refugee, racial and ethnic minoritized children and youth, and the extent to which social, and economic characteristics account for group differences. METHODS: The sample for analyses includes 10,441 children and youth aged 4-17 years participating in the 2014 Ontario Child Health Study. The primary caregiver completed assessments of their child's mental health symptoms, perceptions of need for professional help, mental health-related service contacts, experiences of discrimination and sociodemographic and economic characteristics. RESULTS: Adjusting for mental health symptoms and perceptions of need for professional help, children and youth from immigrant, refugee and racial and ethnic minoritized backgrounds were less likely to have mental health-related service contacts (adjusted odds ratios ranged from 0.54 to 0.79), compared to their non-immigrant peers and those who identified as White. Group differences generally remained the same or widened after adjusting for social and economic characteristics. Large differences in levels of perceived need were evident across non-migrant and migrant children and youth. CONCLUSION: Lower estimates of mental health-related service contacts among immigrant, refugee and racial and ethnic minoritized children and youth underscore the importance and urgency of addressing barriers to recognition and treatment of mental ill-health among children and youth from minoritized backgrounds.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".