THE EFFECT OF PHYSICAL ACTIVITY AND SLEEP ON QUALITY OF LIFE AND DEPRESSION LEVEL IN 18- 25 YEARS OLD UNIVERSITY STUDENTS
Bibliographic record
Abstract
ABSTRACT Aim:Physical activity,which involves movements exceeding basal energy levels, affects both physical and psychological health.This descriptive study examines the effects of physical activity and sleep on quality of life and depression in university students. Methods:Sociodemographic data was collected using a form.Physical activity was assessed with the International Physical Activity Questionnaire short form (IPAQ), sleep quality with the Pittsburgh Sleep Quality Index (PSQI), depression levels with the Beck Depression Inventory, and quality of life with the Quality of Life Scale (SF-36). Results:While there was no statistically significant correlation between PSQI,which was used to evaluate sleep duration and quality, and SF-36 sub-parameters Physical Function (r=-0.127;p=0.133) and Physical Role Difficulty (r= -0.155;p=0.066);There was a weak negative statistically significant relationship between the sub-parameters of Vitality (r=-0.281*;p=0.001),Social Functioning (r=-0.278*;p=0,001),Pain (r=-0.296*;p=0.000), General Health (r=-0.290*;p=0.000). A statistically significant relationship was found between PSQI and Emotional Role Difficulty (r=-0.300*;p=0.000), Mental Health (r=-0.409*;p=0.000) sub-parameters at a moderate negative level. There was also a statistically significant moderate positive correlation between the total scores of PSQI and Beck Depression Inventory (r=0.483*;p=0.000). Conclusions:Adequate sleep and physical activity improve the quality of life and mood in university students,a critical life stage.Therefore, interventions to assess and improve physical activity levels and sleep quality are necessary. In this population, physical activity levels and sleep quality should be questioned and interventions to improve them are needed.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".