A method for the risk assessment of biomechanical overload in hospital physiotherapists
Bibliographic record
Abstract
BACKGROUND: In physiotherapists, biomechanical overload risk assessment (RA) is particularly complex due to the tasks' variability. The present study aims to propose a new methodology, named Whole Body RA Biomechanical Overload (WB-RAMBO), to assess the risk in the activities performed by physiotherapists. METHODS: Each type of intervention was broken down into elementary operations. The risk factors (force, repetitiveness, and incongruous postures) were recorded and evaluated for each of these. For each task, the risk level was obtained by integrating the results of multiple ergonomic methods among those proposed by the international literature. To verify and validate the obtained results, we reviewed the medical records of health surveillance carried out on physiotherapists. RESULTS: From the ergonomic point of view, RA shows a situation of acceptability. The observed slight dysergonomies are diluted in the work shift and allow an optimal functional recovery of the musculoskeletal system. CONCLUSIONS: This method proposes a RA for each operation performed. A work plan subjected to such a peculiar RA can be redesigned and adapted to the company's and the hypersusceptible worker's organizational needs.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".