Safety analysis of patient transfers and handling tasks
Bibliographic record
Abstract
BACKGROUND: Low-back disorders are related to biomechanical demands, and nurses are among the professionals with the highest rates. Quantification of risk factors is important for safety assessment and reduction of low-back disorders. OBJECTIVE: This study aimed to quantify physical demands of frequent nursing tasks and provide evidence-based recommendations to increase low-back safety. METHODS: Thirty-six volunteer female nurses participated in a cross-sectional study of nine nursing tasks. Lumbar range of motion (ROM) and motion during nursing tasks were measured. Compression and shear forces at L5/S1, ligament strain and percentage of population without sufficient torso strength to perform 14 phases of nine nursing tasks were estimated. RESULTS: Peak flexions during trolley-to-bed, bed-to-chair and chair-to-bed transfers reached the maximum flexion ROM of the nurses. Average lumbar flexion during trolley-to-bed transfers was >50% of flexion ROM, being higher than during all other tasks. Mean (SD) compression at L5/S1 (4754 N (437 N)) and population without sufficient torso strength (37% (9%)) were highest during the pushing phase of bed-to-trolley transfers. Shear force (487 N (40 N)) and ligament strain (14% (5%)) were highest during the pulling phase of trolley-to-bed transfers. CONCLUSIONS: Nursing tasks impose high biomechanical demands on the lumbar spine. Excessive lumbar flexion and forces are critical aspects of manual transfers requiring most of the nurses' capabilities. Evidence-based recommendations to improve low-back safety in common nursing tasks were provided. Fitness to work, job modifications and training programs can now be designed and assessed based on the results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".