Examining the contributions of hope and optimism to teacher wellbeing and burnout through a structural equation modeling analysis
Bibliographic record
Abstract
This study investigated the contributions of hope and optimism to teacher well-being and burnout through a Structural Equation Modeling (SEM) framework. A sample of 200 Iranian language teachers completed validated measures of hope, optimism, well-being, and burnout. Correlation analyses revealed strong positive relationships between hope and optimism, as well as their significant positive associations with well-being and negative associations with burnout. Mediation analyses demonstrated that burnout partially mediated the effects of hope and optimism on well-being. Path analysis indicated that optimism had a stronger protective influence against burnout ( β = -0.48) and a more pronounced effect on well-being ( β = 0.34) compared to hope ( β = -0.37 and β = 0.26, respectively). The findings highlight the distinct and complementary roles of hope and optimism in enhancing teacher well-being and reducing burnout, underscoring the importance of fostering these psychological resources to promote resilience and sustainable professional practice. By adopting a SEM approach, this study provides a more nuanced understanding of the pathways through which hope and optimism interact with burnout and well-being, offering insights for intervention and teacher support programs.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".