Canadian educators’ preparedness in addressing mental health needs of secondary students
Bibliographic record
Abstract
An anonymous paper based survey was used to collect qualitative and quantitative data on a sample of teachers and special education assistants in an urban secondary school in British Columbia. The aim of this study was to investigate educators’ level of skills and knowledge to deal with student mental health issues. The results of the survey indicate that although the teachers acknowledge the importance of addressing mental health needs of their students, they also request greater access to resources, skill development, and information about mental health. They reported a global lack of training and knowledge to access various supports available within the school and the community. The survey revealed that most of them relied on school counsellors in most aspects of mental health service delivery, such as screening and behavioural assessments, monitoring student progress, and referring students to other services in the community. Most of the participants reported to have minimal training during their pre-service teacher education program and attempted to learn a majority about mental health through experiences of dealing with situations and some professional development. Major barriers to effective student mental health delivery that were identified included lack of time, resources, and knowledge about what is available both within and outside the school. A majority of the participants called for more professional development opportunities about mental health issues in students. They also insisted on more involvement from the administration at the school. Implications of the findings are discussed.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".