Interprofessional collaborative patient-centred care: a critical exploration of two related discourses
Bibliographic record
Abstract
There has been sustained international interest from health care policy makers, practitioners, and researchers in developing interprofessional approaches to delivering patient-centred care. In this paper, we offer a critical exploration of a selection of professional discourses related to these practice paradigms, including interprofessional collaboration, patient-centred care, and the combination of the two. We argue that for some groups of patients, inequalities between different health and social care professions and between professionals and patients challenge the successful realization of the positive aims associated with these discourses. Specifically, we argue that interprofessional and professional-patient hierarchies raise a number of key questions about the nature of professions, their relationships with one another as well as their relationship with patients. We explore how the focus on interprofessional collaboration and patient-centred care have the potential to reinforce a patient compliance model by shifting responsibility to patients to do the "right thing" and by extending the reach of medical power across other groups of professionals. Our goal is to stimulate debate that leads to enhanced practice opportunities for health professionals and improved care for patients.
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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 | 0.075 | 0.077 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.037 | 0.131 |
| Scholarly communication | 0.032 | 0.034 |
| Open science | 0.005 | 0.031 |
| Research integrity | 0.013 | 0.022 |
| Insufficient payload (model declined to judge) | 0.002 | 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".