Musculoskeletal disorders among office workers: prevalence, ergonomic risk factors, and their interrelationships
Bibliographic record
Abstract
This cross-sectional study investigated the prevalence of work-related musculoskeletal disorders (WMSDs), ergonomic risks, and psychosocial factors among 99 office workers at an industrial company. Participants, aged 20-50 years with minimum one year of experience, were selected using census sampling. Exclusion criteria comprised history of musculoskeletal disorders, fractures, hand surgery, major systemic diseases, pregnancy, menstruation, or recent hospitalization. Data collection utilized the extended nordic musculoskeletal questionnaire and rapid office strain assessment (ROSA). Results demonstrated 80.81% WMSDs prevalence, most commonly affecting neck (58.6%), lower back (52.5%), and shoulders (37.4%). The mean ROSA score of 5.40 ± 1.27 indicated suboptimal workstation ergonomics. Significant associations were identified between chair height and knee/shoulder/upper back pain (p < 0.01), and between job stress and WMSDs across all body regions (p < 0.05). The findings emphasize the necessity of comprehensive interventions targeting ergonomic improvements, postural correction, and stress management to mitigate WMSDs risks in office environments.
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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) | 0.001 | 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".