The Person-Centred Care Guideline: From Principle to Practice
Bibliographic record
Abstract
Background: A standardized definition and approach for the delivery of person-centered care (PCC) in cancer care that is agreed upon by all key policy makers and clinicians is lacking. The PCC Guideline defines core PCC principles to outline a level of service that every person accessing cancer services in Ontario, Canada should expect to receive. This article describes the dissemination of the PCC Guideline in practice. Methods: Three strategies were utilized: (1) educational intervention via a PCC video, (2) media engagement, and (3) research/knowledge user networks. Results: As of October 2016, the PCC video has been viewed 7745 times across 92 countries. Significant mean differences pre- and post-PCC video were found for understanding of PCC principles ( P < .001) and perceived ability to bring these PCC principles to practice ( P < .001). Through content analysis, the PCC Guideline recommendations were referenced 236 times, with “Enabling Patients to Actively Participate in their Care” (n = 81), and “Essential Requirements of Care” (n = 79) being referenced most frequently. Conclusions: These strategies are an effective way to target multiple PCC stakeholders in the health-care system to increase awareness of the PCC Guideline, in order to further impart knowledge of PCC behaviors.
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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 | 0.054 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".