Characterizing mental health related service contacts in children and youth: a linkage study of health survey and administrative data
Bibliographic record
Abstract
BACKGROUND: To inform the provision and organization of care, and to improve equitable access to mental health services for children and youth, we must first characterize the children and youth being served, taking into consideration factors related to mental health need. Our objective was to use a population-based survey linked with health administrative data to estimate mental health related contacts and determine socio-demographic correlates, after adjusting for factors related to mental health need. METHODS: Data from the 2014 Ontario Child Health Study (OCHS) were linked at the individual level to health administrative databases from Ontario's Ministry of Health and Long-Term Care (MOHLTC). Mental health related service contacts were identified in the 6-months prior to the OCHS survey date. Service contacts with physicians were obtained from health administrative data, and non-physician service contacts from survey data (parent-report). RESULTS: 21.7% of Ontarian children (4-11 years) and youth (12-17 years) had at least one mental health related contact in the 6-months prior to their OCHS survey date (18.8% non-physician, 8.0% physician, 5.2% both). Children and youth contacting both physician and non-physician services (ref. contact with physician or non-physician services alone) had higher mean symptom ratings of mental disorders across all classes of disorder. After adjusting for total symptom ratings, children and youth with immigrant parent(s) (ref. non-immigrant) (Prevalence Ratio: 0.65, 95% CI 0.55, 0.75) were less likely to have any mental health related service contact. CONCLUSIONS: Results indicate that children and youth with the highest mental health symptom ratings are more likely to have contact with multiple providers across sectors. As such, the coordination of care across and within sectors are critical components of mental health related services for children and youth. Our results indicate that the greatest disparities in mental health related service contacts may exist for children and youth with immigrant parent(s) and that targeted outreach efforts are required to reduce barriers to care and improve equitable access to mental health related services for children and youth in Ontario.
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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 | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".