Low Back Pain, Disability and Quality of Life in Nursing Personnel: A Cross-Sectional Study
Bibliographic record
Abstract
Background and Purpose:Low back pain (LBP) is a global health problem and one of the leading causes of disability. Also, LBP is a major occupational problem among nursing staff. The study aims to determine LBP, disability, quality of life (QoL), and the relationship between LBP and job-related risk factors and dimensions of QoL in nurses. Materials and Methods: In this cross-sectional study with a descriptive-analytic approach, eligible nurses working in teaching hospitals affiliated with Mazandaran University of Medical Sciences were included in the study by census method. Data were collected based on the demographic questionnaire, Visual Analog Scale (VAS), Quebec Back Pain Disability Scale (QBPDS), and Short-Form 36 (SF-36) health survey questionnaire. Data were analyzed (descriptive, logistic regression, spearman correlation) using SPSS software, version 23. Results: This study included 402 nurses with a mean age of 36.47±7.1 years and employment mean of 11.83±6.4 years of an employment. The prevalence of LBP was 86.3% and the mean of pain intensity and disability were 4.8±2.7 and 30.4±17.4, respectively. The mean QoL components, such as physical and mental were 58.03±19.6 and 57.42±18.3, respectively. The factors that were significantly associated with LBP were body mass index (BMI) (P<0.0001), frequent bending (P=0.004), and workplace communication (P=0.008). LBP affected dimensions of QoL, especially physical function (P=0.008), role physical (P=0.02), general health (P<0.0001), and social function (P=0.03). Conclusion: This study showed the high prevalence of LBP among nurses and the role of individual and workplace factors in the occurrence of LBP. Such cognition facilitates the design of an educational program and undertakes the targeted preventive actions.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".