The Factors Determining the Physical Activity of Students: A Systematic Review
Bibliographic record
Abstract
Background Physical activity in students in addition to positively affecting their different health aspects is also effective in academic progress and reducing absence from school. Physical activity in students is affected by several factors. The aim of this systematic review research was to identify the factors determining physical activities in students. Materials and Methods The search for detecting relevant studies was performed in electronic databases within the time range of 2008-2018. The studies were searched in Google scholar, Medline, Cochran, Scopus, EMBASE, and Web of Science. Studies meeting the inclusion criteria were included in the review. Assessment of the quality of papers was performed using New Castle-Ottawa (BOS) scale. Then, the required information was extracted and the results were reported qualitatively. Results A total of 12 studies (including 41,407 year-old students) were enrolled in the research according to inclusion criteria. The demographic factors associated with physical activity included age, gender, academic degree of parents and economic status. On the other hand, the psychological factors were supported by parents, support of friends, and lack of time due to school homework, computer games, sense of laziness and self-efficacy, which had a relationship with physical activity of students. Further, the environmental determinants included climatic conditions, sports facilities and equipment, and lighting of passages. Conclusion In students' physical activity, factors such as demographic, psychological, and environmental factors are involved. Identification of these factors can be used in health promotion interventions and planning for 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 | 0.008 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".