Differences in psychological well-being, physical activity, and perception of the value of physical education among Italian middle and high school teachers: A cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Research shows that teachers with high self-efficacy and emotional stability are better able to manage lessons, respond to student behavior, and apply proactive, student-centered approaches. In addition, teachers’ emotional well-being enhances their teaching effectiveness and has a positive impact on students’ perceptions of their competence, with positive emotions increasing student satisfaction and engagement. In this study, we want to examine the perception that middle and high school physical education teachers have of the importance of physical education, as well as their level of physical activity and psychological well-being. MATERIALS AND METHODS: Italian physical education teachers (total: 267; F = 193; M = 74; mean age 42.69 ± 9.05 years) completed an online survey that included sociodemographic data, perceptions of the importance of physical education, the International Physical Activity Questionnaire—Short Form (IPAQ-SF), Depression Anxiety Stress Scales (DASS-21), and the Italian version of the Oxford Happiness Inventory (OHI). RESULTS: Male teachers were significantly more likely to rate physical education (PE) lessons as very important ( P = 0.001) and reported lower levels of anxiety ( P = 0.026), depression ( P = 0.019), and stress ( P < 0.001). Younger teachers also rated PE as more important ( P < 0.001). Older age was associated with less depression ( P = 0.003) and stress ( P < 0.001). Moderately or highly physically active teachers had significantly lower anxiety and depression scores than non-active teachers ( P < 0.05). CONCLUSION: These findings highlight the need to support female and older teachers to recognize the value of exercise and address their mental health needs/issues. Promoting physical activity among teachers can increase their psychological well-being and improve teaching effectiveness and student outcomes.
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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 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".