Comparison of Patient Satisfaction with the Nursing Care Quality in Medical and Surgical Wards between Developed and Developing Countries: A Systematic Review
Bibliographic record
Abstract
Background: Patient Satisfaction (PS) is a key indicator of health-care service quality. This review compared PS in medical and surgical wards among developed and developing countries. Materials and Methods: This systematic review of cross-sectional studies was conducted following Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Related articles were identified through a search of PubMed, Scopus, and Web of Science databases using a combination of relevant terms from January 2000 to December 2022. The Newcastle-Ottawa Scale was used to evaluate the quality of related studies. Narrative synthesis was used for the extracted data. Results: Out of 7656 records retrieved, 61 studies met the inclusion criteria. The studies used three reporting schemes for PS: the overall status of PS, the percentage of satisfied patients, and the mean and standard deviation of PS scores. The overall status of PS was higher in developed countries compared to developing countries. In developing countries, 59.25% of studies reported high levels of satisfaction, while in developed countries, all seven studies reported high levels. The percentage of satisfied patients varied, with a higher percentage in developed countries. In developing countries, nine studies reported over 75% satisfaction, 12 studies reported 50%-75% satisfaction, and three studies reported less than 50% satisfaction. In contrast, developed countries had one study reporting over 75% satisfaction and one study reporting 35%-61% satisfaction. Conclusions: Low PS in developing countries necessitates better nursing care. A global standard for assessing PS is needed for improved health-care service quality monitoring worldwide.
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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 | 0.021 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.011 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".