A mental health outreach program for elementary schools.
Bibliographic record
Abstract
INTRODUCTION: Expanding linkages between mental health services and schools is one strategy to improve early access to help children with emerging mental health problems. However, there are few descriptions of such outreach efforts in Canada. This report describes one model used in Alberta, Canada. METHOD: Key aspects of the organization and operation of the Community Outreach in Pediatrics/Psychiatry and Education (COPE) program are described. RESULTS: The COPE program provides child psychiatric and paediatric consultations to families and schools throughout the elementary school systems in the Calgary and Rocky View School Districts in Alberta, Canada. Participating schools refer prioritized children with emotional, behavioural and/or developmental problems. After an inter-professional screening process, most children go on to a physician-based assessment within the school setting which involves the child, family and key school personnel. Following assessment, an action plan is developed and attempts are made to link children and families with needed services. CONCLUSION: The COPE program represents one approach to linking mental health services with students through schools. Further study is required to determine the range of such models used in Canada. In addition, evaluation of these and other models are sorely needed to better determine the cost-effectiveness of these approaches.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.002 |
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".