Prevalência de lesões músculo-esqueléticas nos enfermeiros de um hospital da região centro de Portugal
Bibliographic record
Abstract
Introduction: Work-Related Musculoskeletal Disorders (WRMDs) are one of the main causes of absenteeism and work disability, being a problem that affects nurses. Objective: To identify the prevalence of WRMSDs among nurses in a hospital in the central region of Portugal. Methodology: A descriptive, quantitative, cross-sectional study was conducted using a convenience sample. Data collection was carried out using the Nordic Musculoskeletal Questionnaire during the first quarter of 2023. Data processing and analysis were performed using SPSS, version 28 (p< 0.05). Ethical principles were ensured. Results: A total of 837 responses were obtained, corresponding to 26.1% of the population, with a mean age of 43.8 ± 10.23.A high prevalence of symptoms was observed, with an emphasis in the lower back region (77.5% in the last 12 months, 49.6% in the last 7 days), with 55% reporting activity limitations in the last 12 months. Over the past 7 days, 55.7% of participants reported a mean pain intensity of 3.95 ± 1.88. Statistically significant associations were found between the prevalence of symptoms by anatomical location in the last 12 months and: i) age; ii) professional activity duration; iii) nursing activities/body postures adopted during shifts. Conclusion: The results align with several national and international studies, revealing a high prevalence of musculoskeletal symptoms among nurses, which negatively impacts their health and quality of life as well as the sustainability of the national healthcare system. This highlights the need to develop, implement, and evaluate WMSD prevention programs to mitigate the issue.
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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 | 0.010 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.024 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".