Exploring Differences in Patient-Centered Practices among Healthcare Professionals in Acute Care Settings
Bibliographic record
Abstract
There is limited evidence of the extent to which Healthcare professionals implement patient-centered care (PCC) and of the factors influencing their PCC practices in acute care organizations. This study aimed to (1) examine the practices reported by health professionals (physicians, nurses, social workers, other healthcare providers) in relation to three PCC components (holistic, collaborative, and responsive care), and (2) explore the association of professionals' characteristics (gender, work experience) and a contextual factor (caseload), with the professionals' PCC practices. Data were obtained from a large scale cross-sectional study, conducted in 18 hospitals in Ontario, Canada. Consenting professionals (n = 382) completed a self-report instrument assessing the three PCC components and responded to standard questions inquiring about their characteristics and workload. Small differences were found in the PCC practices across professional groups: (1) physicians reported higher levels of enacting the holistic care component; (2) physicians, other healthcare providers, and social workers reported implementing higher levels of the collaborative care component; and (3) physicians, nurses, and other healthcare providers reported higher levels of providing responsive care. Caseload influenced holistic care practices. Interprofessional education and training strategies are needed to clarify and address professional differences in valuing and practicing PCC components. Clinical guidelines can be revised to enable professionals to engage patients in care-related decisions, customize patient care, and promote interprofessional collaboration in planning and implementing PCC. Additional research is warranted to determine the influence of professional, patient, and other contextual factors on professionals' PCC practices in acute care hospitals.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".