Nurses’ Perceptions of an Intervention Program to Improve Miscarriage Care in Emergency Departments
Bibliographic record
Abstract
INTRODUCTION: Miscarriage affects approximately 20% of known pregnancies and can have significant physical and emotional consequences. The emergency department is often the first point of contact for parents experiencing this event. However, studies have indicated dissatisfaction with the quality of care provided in the emergency department. Interventions for enhancing physical and emotional health in the emergency department within the context of miscarriage are limited. This study aimed to explore nurses' perceptions of an intervention program for miscarriage care in the emergency department to assess its potential impact on their views of miscarriage experience and care practices. METHODS: This study used a descriptive qualitative approach with semistructured interviews. A total of 8 emergency nurses who attended a training session on miscarriage care, which was part of the intervention program, were interviewed. A thematic analysis of the collected data was conducted. RESULTS: Results showed that nurses experienced an increased level of confidence in providing overall care for parents' emotional needs while addressing gaps in emotional and informational support. This research indicated that targeted training and resources can improve nurses' confidence in supporting parents experiencing a miscarriage in the emergency department. DISCUSSION: The findings provide a relevant foundation for future research, and these interventions could be adapted and implemented in other health care settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".