Religiosity and Occupational Well-Being Among Kindergarten Teachers: The Mediating Role of Mindfulness in Advancing SDG 3
Bibliographic record
Abstract
This study explores the influence of religiosity and mindfulness on the occupational well-being of early childhood education teachers in Indonesia, with a focus on the mediating role of mindfulness. While previous research has examined religiosity and mindfulness in isolation, few have investigated their combined effect on occupational well-being, particularly within non-Western early childhood education contexts. Using a quantitative correlational design, data were collected from 118 kindergarten teachers at Aisyiyah institutions in Sidoarjo. Three adapted instruments were employed: a religiosity scale based on Glock and Stark's model, the Toronto Mindfulness Scale, and the Tripartite Occupational Well-being Scale. Results of Pearson correlation analysis showed significant positive relationships among religiosity, mindfulness, and occupational well-being. Structural equation modeling confirmed that mindfulness partially mediated the relationship between religiosity and occupational well-being. These findings suggest that both religiosity and mindfulness contribute meaningfully to teacher well-being and can serve as protective psychological resources in demanding professional environments. The study highlights the importance of culturally rooted psychological factors and supports efforts to promote teacher well-being in line with the United Nations Sustainable Development Goal 3. Future research is encouraged to examine other relevant variables, such as self-efficacy and emotional intelligence, to broaden understanding of what shapes occupational well-being in early childhood educators.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".