A Survey on Work-Related Musculoskeletal Disorders Among Construction Trades
Bibliographic record
Abstract
Work-related musculoskeletal disorders (WMSDs) are the common health problem among workers in a construction site. Construction workers tend to experience neck pain, lower back pain, knee pain, leg fatigue and feet discomfort due to the occupation they performed. This study aims to investigate the issue related to musculoskeletal disorders among construction workers while performing construction works. Field observation was conducted at four construction sites in Perak Tengah district in order to identify the types of trades who exposed to musculoskeletal disorders. Next, a survey form was developed by modifying the existing Nordic Musculoskeletal Questionnaire (NMQ) in determining the symptoms of WMSDs. Surveys were carried out on 100 construction workers at the selected four construction sites to identify the area and causes of pain and discomfort, types of treatment received by the workers and recovery duration for pain and discomfort. Based on the survey, shoulder, wrists/hands and low back were the common area of pain or discomfort after and while performing works. The main causes of pain and discomfort were mostly from repetitive works, awkward working postures and manipulation of heavy load. Types of treatment received by workers were taking a medicine and rest, while the recovery duration for pain or discomfort was around a week. Interviews with panels of expert regarding the strategies or best practice to minimize the WMSDs among construction workers revealed that the most preferable practice is the contractor of the construction project should follow the safety and health regulation, particularly in managing WMSDs, such as implementing medical surveillance for workers. This study will help construction stakeholders, especially contractors to discover the type of occupations that are majorly impacted with WMSDs and further provide the best strategies or control measures to reduce the effect of WMSDs to their employees while performing work.
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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 | 0.001 | 0.002 |
| 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) | 0.002 | 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".