ASSOCIATION OF PHYSICAL ACTIVITY AND SLEEP QUALITY WITH ACADEMIC PERFORMANCE AMONG DPT STUDENTS
Bibliographic record
Abstract
AIM AND OBJECTIVES It was to determine association of physical activity and sleep quality with academic performance among Doctor of Physical Therapy students. METHODOLOGY It was a cross sectional survey done among 230 DPT students of Riphah College of Rehabilitation, Lahore. The study was completed in 4 months. Both male and female having age range between 17 to 22 were included. Those doing their internship or part time job were excluded. Pittsburgh Sleep Quality Index was for assessing sleep quality, while physical activity was measured by Global Physical Activity Questionnaire. Chi square test was used to analyze association, while frequency tables, mean with standard deviation was used for descriptive statistics. RESULTS The results showed mean score and standard deviation 338.03+257.642 and 310.68+213.621 for high achievers and low achievers respectively, without any significant difference and correlation (p value 0.431 and 0.039). The results regarding PSQI were 11.185+6.359 and 10.041+6.316 for high achievers and low achievers respectively (p value 0.205 and 0.099). CONCLUSION The study concluded that overall there is poor sleep quality and low physical activity irrespective of academic performance or gender. There is no association in sleep quality, physical activity with academic performance in doctor of physical therapy students. KEY WORDS: Academic performances, Exercise, Physical Activity, Physical Therapy, Sleep Quality, Sleep
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".