Factors Associated with Physical Activity among Medical Students of Jazan University: A Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Physical activity is one of the most important factors that affect human health; it reduces the chances of hypertension, coronary heart disease, stroke, diabetes, breast and colon cancer, and depression.OBJECTIVES: The objectives of this study were to measure prevalence of physical activity and to determine the factors affecting the level of physical activity among medical student in Jazan University.METHODS: A cross-sectional study was conducted among the students of medical colleges of Jazan University. A random sample of 419 was determined using most recent physical activity prevalence. A validated self-administered questionnaire was used for data collection.RESULTS: There is a high prevalence of inactivity among study participants (88.1%). Females (91.7%) were more significantly (p value=0.013) inactive than males (83.8%). The most influential barrier perceived by participants is (heavy) academic work as well as lack of places for physical activity; the latter factor being more effective in hindering female students' physical activity.CONCLUSION: Results revealed that the inactivity rate was very high among medical students. The results of this study call for a well-planned intervention at the university level for improving the level of physical activity among university students.
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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 | 0.000 |
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".