Development of the National Association of Orthopaedic Nurses Guidance Statement on Safe Patient Handling and Movement in the Orthopaedic Setting
Bibliographic record
Abstract
High-risk patient-handling tasks lead to work-related musculoskeletal disorders for orthopaedic nurses and other members of the healthcare team who are involved in moving patients with orthopaedic issues. Serious consequences can arise from manually moving/lifting these patients. A task force was organized that included representatives from the National Association of Orthopaedic Nurses, the Patient Safety Center of Inquiry at the James A. Haley Veterans Administration Medical Center in Tampa, the National Institute for Occupational Safety and Health, and the American Nurses Association to identify high-risk tasks performed in the orthopaedic setting and to develop evidence-based solutions to minimize the risk of musculoskeletal disorders. High-risk tasks for moving and lifting orthopaedic patients were identified. Four orthopaedic algorithms and a clinical tool were developed by the task force to direct nurses and healthcare team members caring for orthopaedic patients through the use of scientific evidence and available safe patient-handling equipment and devices.
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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 | 0.094 | 0.111 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.014 | 0.015 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".