The Incidence of Upper Extremity Injuries in Endoscopy Nurses Working in the United States
Bibliographic record
Abstract
Numerous studies have addressed musculoskeletal disorders in the international working population. The literature indicates that injuries exist at astounding rates with significant economic impact. Attempts have been made by government, private industry, and special interest groups to address the issues related to the occurrence and prevention of musculoskeletal injuries. Because of the limited research on the gastrointestinal (GI) endoscopy nursing sector, this descriptive, correlational study explored the incidence of upper extremity injuries in GI endoscopy nurses and technicians in the United States. A total of 215 subjects were included in the study. Findings show that upper extremity injuries exist among nurses working in GI endoscopy. Twenty-two percent of respondents missed work for upper extremity injuries. The findings also show that the severity of disability is related to the type of work done, type of assistive aids available at work, and whether or not ergonomic or physiotherapy assessments were provided at the place of employment. In reference to rate of injury and the availability of ergonomics and physiotherapy assessments, those who had ergonomic assessments available to them had scores on the Disabilities of the Arm, Shoulder, and Hand (DASH) inventory (indicating upper extremity disability) that were significantly lower (DASH score, 9.96) than those who did not have the assessments available (DASH score, 14.66). The results suggest that there are a significant number of subjects who are disabled to varying degrees and the majority of these are employed in full-time jobs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".