Evaluation of Health Promotive and Protective Behaviors in Terms of Different Qualities: A Study on Physical Education Teachers
Bibliographic record
Abstract
Health is one of the most valuable things that we can have. The first thing that comes to mind when we think of health is our physical structure. However, mental health is also of crucial importance. In this context, the aim of this study is to examine physical education teachers’ health promoting and protective behaviors in terms of different qualities. Study sample consisted of 42 female and 98 male physical education teachers. Data were collected using the Health Promoting and Protective Behaviors Scale (HPPBS) developed by Bostan, Örsal, & Montenegro (2016). Data were descriptively analyzed. T-test and one-way analysis of variance (ANOVA) were used for independent groups. Tukey’s multiple comparison test was used for posthoc pairwise comparisons to determine the source of difference. Health promoting and protective behaviors did not differ significantly by gender. However, there was a statistically significant difference in health promoting and protective behaviors between participants who have regular check-ups and pay attention to their diet and sleep and those who do not.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".