The association between teacher distress and student mental health outcomes: a cross-sectional study using data from the school mental health survey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Few studies have examined the inter-relationships between teacher and student mental health. We aimed to examine associations between teacher distress and student mental health difficulties and if student perceptions of school safety moderate these associations. METHOD: Data from 23,568 students in grades 6-12 and 1,478 teachers from 268 schools participating in the School Mental Health Surveys in Ontario, Canada, were used. Three-level (student, classroom, school) multivariable linear regression models were fit to examine associations between teacher distress and student internalizing and externalizing symptoms by elementary (grades 6-8) and secondary (grades 9-12) school. Statistical interactions were used to evaluate effect modification. RESULTS: Small but statistically significant, positive associations were found between teacher distress and internalizing (b = 0.02; 95% CI [0.01, 0.04], p < 0.05) and externalizing symptoms (b = 0.03; 95% CI [0.01, 0.05], p < 0.001) among elementary students only. Student perceptions of school safety moderated the association between teacher distress and externalizing symptoms among elementary students, whereby the positive association was magnified among students reporting lower school safety. CONCLUSIONS: Findings from this study highlight the importance of concurrently addressing the mental health needs of educators and students. School safety represents a modifiable target for prevention and intervention efforts in schools that could serve to promote student mental health and mitigate potential risk factors in schools.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it