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Record W4408392943 · doi:10.62754/joe.v3i8.6607

The Role of Nursing in Enhancing the Quality of Life for Hemodialysis Patients

2024· article· en· W4408392943 on OpenAlex
Wala Awadh Dahem Alenezi, Ruba Abdulaziz Alomran, Nasser Sanad Alshlagi, A Alrashedi, Wedad Awadh Dahem Alenezi, A. Zahrani, Muhammad A. Al-Zahrani, Nahla maan Aljuwaie

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Ecohumanism · 2024
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsNursingHemodialysisQuality (philosophy)PsychologyMedicineIntensive care medicineInternal medicinePhilosophy

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.129

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.332
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it