Engaged teachers and well-being: the mediating role of burnout dimensions
Bibliographic record
Abstract
Background Engaged teachers experience a positive, fulfilling, and work-related state of mind related to their work tasks able to affect their well-being positively. Nevertheless, teachers are particularly exposed to burnout risk, which is highly probable to occur during teachers’ professional careers. The current study investigates the mediating effect of burnout, through which work engagement influences subjective well-being.Methods Participants were 807 Italian teachers (Female, 91.7%; Mage = 47.54; SD = 9.91). Self-report instruments were administered to evaluate teachers’ burnout (BAT, Burnout Assessment Tool), well-being (WHO-5 Well-being Index), and work engagement (UWES-3, Utrecht Work Engagement Scale).Results Findings show that exhaustion (β = −0.2162, p < 0.001) and psychological distress (β = −0.2811, p < 0.001) mediate the relationship between work engagement and well-being (total effect, β = 0.6409, p < 0.001).Conclusions These results enable us to gain a deeper understanding of how the phenomenon of burnout impacts teachers’ well-being, allowing us to design training, prevention, and evaluation programs that consider the complex nature of burnout.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".