Healthcare Providers' Perceptions of Single-Room Versus Traditional Maternity Models
Bibliographic record
Abstract
While many hospitals have transitioned from traditional maternity care to a single-room maternity model, little is known about how healthcare providers' practice differs between the models. This mixed-methods study compared healthcare providers' job satisfaction and team collaboration between traditional and single-room maternity care and explored how each model shaped providers' practice. Data were collected via questionnaires and interviews with healthcare providers from 2 hospitals. Independent t tests, Mann-Whitney U tests, and thematic analysis were used in analysis; findings were then triangulated. No difference was found in team collaboration and job satisfaction scores between single-room (n = 84) and traditional (n = 42) maternity care; however, providers described different means toward satisfaction and collaboration in the interviews (n = 18). Single-room maternity care providers valued interprofessional teamwork, patient/family involvement, and continuity of care. Traditional maternity care providers enjoyed specialization but described teamwork as uniprofessional and disconnected across professions; transfers between units weakened communication and fragmented care. While single-room maternity care providers described less tension and a more holistic patient-family journey, further research must be undertaken to examine whether and how interprofessional collaboration and communication impact patient and health system outcomes.
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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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".