An Exploratory Qualitative Study of Perinatal Experiences in an Acute Setting during Early Phases of the COVID-19 Pandemic
Bibliographic record
Abstract
The COVID-19 pandemic was highly disruptive for people delivering babies in-hospital and for obstetrical healthcare professionals. The purpose of this study was to explore the experiences of people with or without COVID-19 giving birth in a community-based hospital to provide patient insight to obstetrical care providers regarding the services/policies used during the pandemic. Nine interviews were conducted with participants within six months of giving birth in-hospital – four who tested positive for COVID-19 and five who tested negative. Seven themes were identified in the analysis: conflicting emotions; experiences of COVID-related protocols; altered experiences of pregnancy and birth; other aspects of in-hospital care; support from family and friends; interactions and communications with the healthcare team; and seeking information. Results were positively received by the perinatal clinical team and changes were identified to further improve experiences of care. A deeper understanding of patients' lived experiences of hospital services available during public health emergencies can offer important, actionable information for healthcare providers.
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".