Roles, processes, and outcomes of interprofessional shared decision-making in a neonatal intensive care unit: A qualitative study
Bibliographic record
Abstract
Shared decision-making provides an opportunity for the knowledge and skills of care providers to synergistically influence patient care. Little is known about interprofessional shared decision-making processes in critical care settings. The aim of this study was to explore interprofessional team members’ perspectives about the nature of interprofessional shared decision-making in a neonatal intensive care unit (NICU) and to determine if there are any differences in perspectives across professional groups. An exploratory qualitative approach was used consisting of semi-structured interviews with 22 members of an interprofessional team working in a tertiary care NICU in Canada. Participants identified four key roles involved in interprofessional shared decision-making: leader, clinical experts, parents, and synthesizer. Participants perceived that interprofessional shared decision-making happens through collaboration, sharing, and weighing the options, the evidence and the credibility of opinions put forward. The process of interprofessional shared decision-making leads to a well-informed decision and participants feeling valued. Findings from this study identified key concepts of interprofessional shared decision-making, increased awareness of differing professional perspectives about this process of shared decision-making, and clarified understanding of the different roles involved in the decision-making process in an NICU.
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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 | 0.019 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".