Person-centred care: an overview of reviews
Bibliographic record
Abstract
BACKGROUND: Existing evidence suggests that a person-centred approach can improve coordination and access to health care and services. OBJECTIVES: This overview sought to: (1) identify and define components of person-centred care; (2) explore nursing and health-care provider behaviours that are person-centred; and (3) identify systems level supports required to enable person-centred care. METHODS: An overview of reviews was conducted to locate synthesized literature published between June 2005 and April 2014. Two independent reviewers screened, extracted data and quality appraised the sources. Results were synthesized narratively. RESULTS: A total of 46 articles were deemed relevant to this overview. This paper synthesizes the results of 43 of the 46 articles. A universal definition of person-centred care was not found, however; common components, associated health-care provider behaviours and the organizational supports required for person-centred care are discussed. CONCLUSIONS: Key findings from this review outline that health-care providers and organizations need to promote person-centred care by engaging persons in partnerships, shared decision-making, and meaningful participation in health system improvement.
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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 | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.016 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".