in Teacher Stress and Burnout: Results From Two Randomized, Waitlist-Control Field Trials. Journal of Educational Psychology. Advance online publication. doi: 10.1037/a0032093 Mindfulness Training and Reductions in Teacher Stress and Burnout: Results From
Bibliographic record
Abstract
The effects of randomization to mindfulness training (MT) or to a waitlist-control condition on psychological and physiological indicators of teachers ’ occupational stress and burnout were examined in 2 field trials. The sample included 113 elementary and secondary school teachers (89 % female) from Canada and the United States. Measures were collected at baseline, post-program, and 3-month follow-up; teachers were randomly assigned to condition after baseline assessment. Results showed that 87 % of teachers completed the program and found it beneficial. Teachers randomized to MT showed greater mindfulness, focused attention and working memory capacity, and occupational self-compassion, as well as lower levels of occupational stress and burnout at post-program and follow-up, than did those in the control condition. No statistically significant differences due to MT were found for physiological measures of stress. Mediational analyses showed that group differences in mindfulness and self-compassion at post-program mediated reductions in stress and burnout as well as symptoms of anxiety
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.
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 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".