Assessing Teacher Burnout in Elementary Education: A Study in Southwestern Greece
Bibliographic record
Abstract
Introduction Occupational burnout in education is a major problem, especially among elementary school teachers (ESTs) who have the dual task of imparting knowledge and nurturing children’s emotional intelligence. Research in recent years focuses on understanding, preventing and addressing teachers’ burnout. Objectives We aimed to evaluate professional burnout levels among ESTs and identify associated factors. Methods We conducted a cross-sectional study among ESTs in southwestern Greece from September to December 2022. Participants answered to a self-administered questionnaire that included the Maslach’s Burnout Inventory Educator Survey (MBI-ES), socio-demographic, and other characteristics. Results A total of 126 ESTs (63.5% kindergarten, 36.5% elementary school) participated in the study, 81% were female, 39.7% were 31-40 years old, and 51 (40.5%) had 11-20 years of work experience. The majority (63.5%) had a permanent job, mainly as a preschool teacher. Teachers experienced moderate to high levels of job burnout, as indicated by measures of emotional exhaustion (mean 30.03), depersonalization (mean 9.45), and feelings of low personal achievement (mean 46.42). Male teachers had higher levels of emotional exhaustion (50% vs. 46.1%) and female teachers had significantly higher rates of low personal accomplishment (80.4% vs. 66.7%). More experienced teachers showed higher emotional exhaustion (11-12 years: 58.8% vs. 6-10 years: 44.4%). Finally, kindergarten teachers were more likely to report low levels of personal accomplishment compared to other teachers (84% vs. 68.6%). Conclusions Elementary school teachers experience moderate to high levels of job burnout, which is influenced by factors such as gender, years of service, employment status, and phase of teaching. These findings can serve as a basis for prevention strategies and interventions to reduce the effects of burnout in elementary school teachers. Disclosure of Interest None Declared
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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 | 0.002 | 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".