The intraprofessional and interprofessional relations of neurorehabilitation nurses: a negotiated order perspective
Bibliographic record
Abstract
AIMS: To report a study of the negotiation practices of neurorehabilitation nurses with one another and with allied health professionals to understand nursing relations. BACKGROUND: Negotiated order theory offers a promising theoretical lens with which to explore negotiation between nurses and other professionals. This study is the first to apply the perspective to nurse-nurse and nurse-allied health professional relations. DESIGN: The study is a secondary analysis of findings from a multi-site arts-based intervention to improve patient-centred neurorehabilitation practice. METHODS: Interviews and ethnographic observations were conducted (2008-2011) in two neurorehabilitation units in Ontario, Canada. Participants (n = 31) included registered and practical nurses, nurse leaders, and allied health professionals from physical, occupational, and recreational therapy, speech language pathology, and social work. FINDINGS: Neurorehabilitation nursing is characterized by heavy workload, high patient acuity, and poor interprofessional collaboration. This practice context was negotiated by nurses through two strategies: (1) intraprofessional collegialism, accomplished through tactics including task and knowledge sharing, emotional support, coercive threats, and suppression of dissension; and (2) vying for an autonomous essential nursing role in interprofessional practice, accomplished by claiming unique nursing knowledge based on 24/7 nursing proximity, the expansion of the division of professional labour with allied health professionals and modifying physical therapy care plans. CONCLUSION: The intraprofessional context and negotiations therein were linked in significant ways to interprofessional negotiations. Understanding this complexity has important implications for improving patient safety and interprofessional practice interventions.
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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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.035 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".