Supporting children’s mental health in school over a decade later: Current teacher perspectives.
Bibliographic record
Abstract
Over a decade ago, teacher perspectives of supporting student mental health in schools were assessed, including perceptions of mental health needs; their knowledge, skills, and training needs; their roles for supporting children's mental health; and barriers to supporting mental health needs in their school settings. The purpose of this study was to again assess teacher perceptions on these same topics to determine the current landscape for supporting student mental health. Findings from a sample of 420 teachers indicate that the majority of teachers agree that schools should be involved in supporting the mental health of students. Most teachers also felt that they should be involved in implementing classroom interventions and social-emotional learning curriculum. Teachers continue to report that they do not have the knowledge to meet the mental health needs of students, in particular students from diverse backgrounds. The top areas for professional development were identifying mental health issues, classroom behavior management, and culturally responsive practices. The most identified mental health issue in schools was disruptive behavior problems. Finally, the vast majority of teachers now recognize the term evidence-based interventions/practices as compared to the prior study, but teachers note the same barriers to implementing mental health supports as over a decade ago. Implications for practice are discussed. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".