Problematising assumptions about ‘centredness’ in patient and family centred care research in acute care settings
Bibliographic record
Abstract
Over the last two decades significant efforts have been made to implement patient and family 'centred' care as both a practical and moral imperative for adult acute care delivery. Although many resources have been developed and adopted by institutions, research suggests persistent and diverse barriers to implementing and achieving patient and family 'centred' care in adult acute care practice settings. These issues in implementation suggest re-examining the nature of 'centredness' in care may be useful. A structured problematisation method, as outlined by Alvesson and Sandberg, is utilised to identify and analyse assumptions about the central notions of 'centring' that inform patient and family centred care intervention research. From our analysis, we highlight three predominant areas within 'centring' intervention research that may benefit from rethinking: Vitruvian spatiality, democratising care, and 'centring' positioned as primarily a problem and accomplishment for nursing. As a challenge to these assumptions, we argue for the adoption of theoretical lenses that 'de-centre' individual actors to better account for complex relations among multiple actors, both human and nonhuman, which work to involve patients and families in care practices.
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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 | 0.320 | 0.315 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.012 | 0.016 |
| Science and technology studies | 0.004 | 0.054 |
| Scholarly communication | 0.019 | 0.030 |
| Open science | 0.008 | 0.011 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.002 | 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".