Associations between work-related factors and the carpal tunnel syndrome—a systematic review
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to make a quantitative assessment of the exposure-response relationships between work-related physical and psychosocial factors and the occurrence of carpal tunnel syndrome (CTS) in occupational populations. METHODS: A systematic review of the literature was conducted on the associations of type of work, physical load factors, and psychosocial aspects at work to the occurrence of CTS. The associations between work factors and CTS were expressed in quantitative measures, namely, odds ratios (OR) or relative risks. RESULTS: Jobs with the highest risk of CTS included work in the meat- and fish-processing industry, forestry work with chain saws, and electronic assembly work (OR 76.5, 21.3, and 11.4, respectively). The occurrence of CTS was associated with high levels of hand-arm vibration, prolonged work with a flexed or extended wrist, high requirements for hand force, high repetitiveness, and their combination. No association was found between any psychosocial risk factor and CTS. Contradictory findings were reported for associations between computer work and CTS. CONCLUSIONS: This review provides consistent indications that CTS is associated with an average hand force requirement of >4 kg, repetitiveness at work (cycle time 50% of cycle time performing the same movements), and a daily 8-hour energy-equivalent frequency-weighted acceleration of 3.9 m/s2.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".