School mental health promotion and intervention: Experiences from four nations
Bibliographic record
Abstract
All around the world, partnerships among schools and other youth-serving systems are promoting more comprehensive school-based mental health services. This article describes the development of international networks for school mental health (SMH) including the International Alliance for Child and Adolescent Mental Health and Schools (INTERCAMHS) and the more recent School Mental Health International Leadership Exchange (SMHILE). In conjunction with World Conferences on Mental Health Promotion, SMHILE has held pre-conference and planning meetings and has identified five critical themes for the advancement of global SMH: 1) Cross-sector collaboration in building systems of care; 2) meaningful youth and family engagement; 3) workforce development and mental health literacy; 4) implementation of evidence-based practices; and 5) ongoing monitoring and quality assurance. In this article we provide general background on SMH in four nations, two showing strong progress (the United States and Canada), one showing moderate progress (Norway), and one beginning the work (Liberia). Following general background for each country, actions in relation to the SMHILE themes are reviewed. The article concludes with plans and ideas for future global collaboration towards advancement of the SMH field.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".