The Role of Nursing in Enhancing the Quality of Life for Hemodialysis Patients
Bibliographic record
Abstract
Background: Chronic Kidney Disease (CKD) is a prevalent health issue that requires long-term management, with many patients relying on hemodialysis therapy due to the limited availability of kidney transplants. Hemodialysis patients face significant physical and psychological challenges, which can impact their overall quality of life. Nurses play a crucial role in ensuring patient adherence to hemodialysis regimens and providing high-quality care, yet various factors such as workload, stress, and limited resources may affect their ability to deliver optimal care. Understanding the relationship between the role of nurses and the quality of life in hemodialysis patients is essential for improving treatment outcomes. Methods: This study employed a descriptive quantitative correlation design with a cross-sectional approach. A total of 80 hemodialysis patients were recruited through power analysis. Data collection was conducted using two structured questionnaires: one to assess the quality of life in hemodialysis patients and another to evaluate the role of nurses in providing hemodialysis care. The quality of life questionnaire was adapted from the WHOQOL instrument and used a 4-point Likert scale, with higher scores indicating better quality of life. The nursing role questionnaire assessed key aspects of care, including assessment, planning, implementation, and evaluation. Data analysis was performed using univariate and bivariate statistical methods, with the Spearman rho correlation test used to determine the relationship between nurses’ roles and patients’ quality of life. Results: The study found that 90.8% of nurses demonstrated good performance in delivering hemodialysis care, while 9.2% had lower effectiveness. Regarding patient quality of life, 63.2% of hemodialysis patients reported a high quality of life, while 36.8% had a moderate quality of life. The correlation analysis revealed a significant positive relationship between nurses' roles and patient quality of life (r = 0.520, p = 0.002), indicating that better nursing care is associated with improved patient well-being. Conclusion: The findings highlight the crucial role of nurses in enhancing the quality of life among hemodialysis patients. Effective nursing care, including proper assessment, planning, implementation, and evaluation, contributes to better treatment adherence and overall well-being. Strengthening nurse-patient relationships, reducing nurse fatigue, and providing continuous professional training can further improve the quality of care and patient outcomes. Future research should explore additional interventions to optimize nursing care in hemodialysis settings.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".