An Occupational Stress Management Program for Physical Education Teachers in Rural Primary Schools: Implementation and Evaluation in Guangxi Province
Bibliographic record
Abstract
Physical education teachers in rural primary schools experience significant occupational stress that impacts their well-being, job satisfaction, and teaching effectiveness. The rapid implementation of China’s “health first” educational policy has intensified demands on rural physical education teachers, while existing support systems remain inadequate. This research aimed to: (1) investigate occupational stressors that affect physical education teachers in rural primary schools in Guangxi Province, (2) assess current and desired states of occupational stress management support systems, and (3) develop a comprehensive occupational stress management program based on contemporary adult learning theory. A three-phase sequential mixed-methods design was employed. Phase 1 validated five occupational stressor categories through expert consultation (n=5). Phase 2 assessed current and desired states using surveys with 378 stakeholders from rural primary schools. Phase 3 developed and validated a stress management program incorporating experiential learning (70%), peer learning (20%), and formal training (10%). Five primary stressor categories were identified: student situations, work situations, parent situations, interpersonal relationships, and occupational demands. Significant gaps existed between current support levels (X̅=1.92, low level) and desired support levels (X̅=4.01, high level), with improvement gaps ranging from 1.97 to 2.17 points across all stressor categories. Expert validation confirmed high program suitability (X̅=4.65) and feasibility (X̅=4.20). This study provides the first comprehensive framework for addressing occupational stress among rural physical education teachers in China. The developed program offers a systematic, evidence-based approach combining theory and practice with demonstrated high suitability and feasibility for implementation.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".