Relationship between patient-perceived quality of nurse caring attitudes and behaviours and quality of life of haemodialysis patients in Switzerland
Bibliographic record
Abstract
Background: Chronic kidney disease (CKD) is a fast-growing cause of morbidity and mortality worldwide. Patients suffering from CKD almost always develop end-stage renal disease (ESRD) that is often treated with haemodialysis (HD). In this context, the quality of the nurse-patient relationship (NPR) plays a major role in supporting the quality of life (QoL) of HD patients. This study examined the relationship between quality of nurse behaviours and attitudes as perceived by HD patients and QoL of these patients.Methods: The study used a cross-sectional correlational design. The sample consisted of 140 patients recruited in 10 HD units in French-speaking Switzerland. The Caring Nurse-Patient Interaction Scale (CNPI-70) was used to assess the NPR, and the French version of the WHOQOL-Bref was used to evaluate different dimensions of QoL. Random-intercept linear regressions adjusted for sociodemographic characteristics were used to study the relationship between patient-perceived quality of nurse caring attitudes and behaviours and patient QoL.Results: Patients reported a high frequency of caring attitudes and behaviours from their attending nurses, except relative to the dimension of spirituality. All the dimensions of patient QoL were positively influenced by the caring factor composing the CNPI-70. In particular, nurse attention to patient dignity when providing support for basic human needs seemed to be a major factor in patient QoL.Conclusions: Quality of NPR is essential to improving patient QoL. Interventions need to be developed to support quality of NPR.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".