Correlation between Heavy School Bags and Upper Limb Disabilities among School Going Children
Bibliographic record
Abstract
Aim: To find out correlation between heavy school bags and upper limb disabilities among school going children. Methods: This descriptive cross-sectional survey, using non-probability convenience sampling, was conducted on 396 students of 11 to 15 years after ethical approval in 6 months. Height (in cm) and weight (in Kg) were noted and BMI was calculated. Students with the normal BMI were included in the study. Weigh of the students were recorded with their shoes off while the weight of the bags was calculated with all the stationary included. Quick DASH scale score was calculated and correlated with the weight of the bag by applying Chi-Square test. Results: The mean age of the participants was13.49±1.12 years. The mean weight of the school bag was 6.10±2.1Kgs while the students were carrying more than one-quarter of their body weight. The disability calculated from the quick DASH scale was as high as 40%. Chi-square showed a significant correlation between the upper limb disabilities and the weight of the bag. Conclusion: The study showed that there is a significant correlation that the use of heavy school bags can cause upper limb disabilities in children. Keywords: Heavy School Bags, Upper Limb Disabilities, Children, Disabilities of Arm Shoulder and Hand
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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) | 0.005 | 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".