A Study of Prolonged Standing And Work-related Musculoskeletal Disorder Among Cashier At Hypermarket / Rukiah Chandra
Bibliographic record
Abstract
Musculoskeletal disorders (MSDs) were recognized as having occupational etiologic factors as early as the beginning of the 18th century. Work-related musculoskeletal disorders (WRMDs) are increasingly prevalent in the Malaysian workforce. Canadian Center for Occupational Health and Safety (CCOHS) in 2005 claims that WMSDs are known as leading causes of significant human suffering, loss of productivity, and economic burdens on society. Objectives of this study were to determine time (hours) of standing among cashiers, to classify the musculoskeletal disorder among cashiers and to identify association between prolonged standing and musculoskeletal disorder among cashiers. A cross sectional study was conducted to see the prevalence of MSDs among standing cashiers. The questionnaire was edited from previously used and validated questions including the Standardized Nordic Questionnaire for the Analysis of Musculoskeletal Symptoms (Kuorinka et al, 1987) and the Rapid Upper Limb Assessment (RULA) (McAtamney & Corlett, 2004) were distributed to respondents participated (n=60). Significant difference (p = 0.001) of mean of time (hours) between standing and sitting cashiers were recorded. However, risk is not significantly associated with pf0Ionged standing (p=0.417) among standing cashiers. Significant association of prolonged standing and MSD in last 12 months at low back p=0.035, ankle p=0.001 and knees p=0.003. As conclusion, advance hazard analysis and administrative control are recommended to reduce the risk faced by cashier while perform their job.
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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 | 0.000 |
| 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 | 0.000 | 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".