Trends in Patient-Centered Care in South West Nigeria: A Holistic Assessment of the Nurses Perception of Primary Healthcare Practice
Bibliographic record
Abstract
BACKGROUND: A key dimension of a quality healthcare to patients is patient-centered care approach which is increasingly gaining recognition worldwide. However, this concept is not fully implemented in practice. AIM: The aim of this study is to provide outcomes from assessment of nurses’ perceptions about patient-centered care and the current trends in Primary Health Care system in South West Nigeria. METHODS: This study employed a qualitative participatory action research study approach and conducted a semi-structured individual interview with thirty-five nurses and four focus group discussions in Osun State South West Nigeria Primary Health Care centres. RESULTS: Primary Health Care (PHC) nurses perceived and described patient-centered care (PCC) as a global approach to improve and enhance nursing care to foster patient participation. The narratives were categorised into two: positive and negative perception. Ten main themes emerged: (I) Attitude of the nurses (ii) Lack of enforcement and implementation, (iii) Experience of the nurses, (iv) Quality-Caring, (v) Effective communication with patient, (vi) Motivated and Proactive healthcare, (vii) Sharpen the form of care, (viii) Outcome and after-effect driven healthcare, (ix) Approved support, and (x) Guarantor of service and motivation. CONCLUSION: Our participatory action research study on the assessment of nurses’ perception on the utilization of PCC at the PHC for effective and quality healthcare service revealed the importance of nurses’ role, acceptability of PCC and current nursing care practice at the Primary Health Care (PHC) rural community setting. Nurses as healthcare providers expressed PCC as a common and global approach that would enhance patient experiences and improves the quality of nursing healthcare delivery through integration of PCC and healthcare service at the PHC healthcare system.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".