Patient satisfaction with nursing care in Ethiopia: A systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Patient satisfaction with nursing care has been considered as the most important predictor of the overall patient satisfaction with hospital service and quality of health care service at large. However, the national level of patient satisfaction with nursing care remains unknown. Hence, the objective of this systematic review and meta-analysis was to estimate patient satisfaction with nursing care in Ethiopia. Methods Studies were accessed through an electronic web-based search strategy from PubMed, Cochrane Library, Google Scholar, Embase, PsycINFO and CINAHL by using combination search terms. Qualities of each included article assessed by using a modified version of the Newcastle-Ottawa Scale for cross-sectional studies. All statistical analyses were done using STATA version 14 software. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was followed for reporting results. Results Of 1,166 records screened, 15 studies with 6091 participants were included. The estimated pooled level of patient satisfaction with nursing care in Ethiopia was 55.15% (95% CI (47.35, 62.95%)). Based on the subgroup analysis, the estimated level of patient satisfaction was 61.84% (95% CI: 44.49, 79.2) in Addis Ababa, 54.24 %(95%CI: 46.84, 61.65) in Amhara region, 44.06% (95%CI: 38.09, 50.03) in SNNP, and 53.02 %(95% CI: 50.03, 56.00) in other regions. Patients who have one nurse in charge [(OR 1.08(0.45, 2.62)], with no history of previous hospitalization [(OR 1.37(0.82, 2.31)], living in the urban area [(OR 1.07(0.70, 1.65)], / and those who have no comorbid disease [(OR 1.08(0.48, 2.62)] were more likely to be satisfied with nursing care than their counterparts even though it was not statistically significant. Conclusion This meta-analysis revealed that about one in two patients were not satisfied with the nursing care provided in Ethiopia. Therefore, Ministry of Health should give more emphasis to the quality of nursing care in order to increase patient satisfaction which is important to improve the overall quality of healthcare service.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".