Teaching mental health in the classroom: A mixed-methods implementation evaluation of a mental health literacy program in elementary schools
Bibliographic record
Abstract
Mental illnesses are the largest disease burden for adolescents, affecting 20 % of youth in Canada. As mental health needs arise earlier and with greater prevalence, it is essential to work upstream and prepare youth before psychological distress emerges. When implemented in the classroom as part of the educational curriculum, Mental Health Literacy (MHL) fulfills these goals as a universal response to the societal and development stressors experienced by youth. The aim of this implementation evaluation was to explore the experience of educators delivering the Elementary Mental Health Literacy Resources (EMHLR) during a 4-month period across Canada. The specific objectives were to identify the individual (educator) and organizational (district) level barriers and facilitators to delivery of the EMHLR to improve future implementation of the program. An explanatory sequential design used data from an existing feedback survey and qualitative data was gathered from group interviews with Educators. Findings were integrated using the RE-AIM framework to identify barriers and facilitators and develop considerations for implementation System level barriers included the pre-existing stigma around mental health, competing priorities for classroom time, and cultivating buy-in from leadership. Individual level barriers included the time and knowledge to teach MHL. The flexible design of the EMHLR curriculum and specific implementation strategies were seen as facilitators. Mental Health Literacy offers language for youth to communicate about their experience clearly and accurately. The EMHLR curriculum offers an evidence-based and adaptable means to build the MHL of youth across Canada. This holds potential for improving youth mental health but requires intentional implementation strategies to be successful.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.039 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".