1477 Stress amongst elementary and high school teachers
Bibliographic record
Abstract
Introduction Teachers, as in other professions, are exposed to different types of problems within the field of occupational medicine. Generally, teachers heavily stressed show signs of psychological distress that usually shows as severe anxiety, low psychological comfort and low job satisfaction. Methods The questionnaire was distributed within elementary, middle and high schools in the district of Hay Hassani, Casablanca. All subjects voluntarily accepted to be on the study. We’ve distributed 300 questionnaires but only gathered 140. Results From 140 subjects, 58,06% were female, 26% worked in primary schools, 51% in middle schools and 47% in high schools. Almost half of them (48.38%) have been teaching for over 20 years. Of the participants, 31,14% never felled energetic, full of life or being eager to go through every new day. The auto evaluation of mental health found that 20,16% rated their mental health as being medium to poor. Burnout was felt by 36,51% of the respondents once or more than once per month and 26,63% say that they always have a heavy workload. Roughly half of the participants (44%) were not satisfied with their jobs. Discussion In a Suiss study, they found that more than 80% of teachers showed medium burnout signs. In our study 37% showed exhaustion signs once or more every month which indicates that there is a disproportion between individual possibilities and the reality of working conditions. In a survey conducted by the autonomous federation of education of Quebec, they found that a heavy workload is the main determinant of stress experienced by teachers which explains our findings. Conclusion Professional stress affects the well being of teachers. The main prevention mechanism that can be used is self management which represents the process that teachers have the most control on.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".