A controlled study: Evaluating the clinical impact of a nurse‐centred multidisciplinary hospice care model on anxiety, depression, and quality of life in patients with advanced malignant tumours
Bibliographic record
Abstract
OBJECTIVE: To explore the clinical effect of a nurse-centred multidisciplinary collaborative hospice care model in patients with advanced malignant tumours. METHODS: A total of 30 patients with advanced malignant tumours were hospitalised and randomly divided into a study group and a control group, each consisting of 15 cases. The study group received nurse-led multidisciplinary collaborative hospice care, whereas the control group underwent high-quality nursing intervention. Variables such as the self-rating anxiety scale (SAS) score, self-rating depression scale (SDS) score, quality of life scale (EORTC QLQ-C30) score, patient happiness, and nursing satisfaction were compared between the two groups. RESULTS: Post-intervention, the SAS and SDS scores in the study group were lower than those in the control group (p < 0.01). The overall quality of life score of the study group was higher than that of the control group (p < 0.01). The Memorial University of Newfoundland Scale of Happiness scores in the study group also surpassed those of the control group (p < 0.01). Additionally, nursing satisfaction in the study group exceeded that of the control group (p = 0.027). CONCLUSION: The nurse-led multidisciplinary collaborative hospice care model substantially alleviated negative emotions among patients, effectively improved their quality of life and happiness, and garnered positive evaluations of nursing satisfaction.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".