Understanding the experiences of birthing care during COVID-19: A qualitative systematic review
Bibliographic record
Abstract
Background: The Covid-19 pandemic was a challenging time for people who sought health care and for health care providers. Throughout the pandemic women and birthing people, families, and health care providers adapted to ongoing changes, restrictions, and new information to ensure that babies were born safely. There was a strong policy focus on safety and the reduction of infection, however this focus did not account for how the changes to birthing care practice would influence the experiences of the people most continuously sharing space during birth - women and birthing people, midwives, and nurses. Objective: To explore and understand the birthing care experiences of women and birthing people, midwives, and nurses. Methods: We used the JBI methodology and methods to conduct our qualitative review. We included studies with participants who were women or birthing people, nurses, and midwives who received or provided birthing care during the Covid-19 global pandemic. Studies published between January 2020 and February 2023 were included. Studies had to report qualitative data. Results: A total of 5694 studies were identified for this review. After duplications were removed, screening and critical appraisal, 26 studies were included. Following meta-aggregation, 3 synthesized findings and 9 categories were created. The synthesized findings are 1) Navigating a pandemic and the chaos of constant changes 2) Striving for business as usual during a pandemic and 3) Amplifying variations in birthing care experiences. Conclusions: The experiences and needs of people who provide and receive birthing care must be prioritized in all spaces. Midwives, nurses, women, and birthing people must be included in decision making for changes to practices and policies at all levels, especially during uncertain times. Birth experiences must be respected and supported to ensure that health and wellness outcomes are optimized for families at all stages of the intrapartum, postpartum and early parenting journeys. Registration: https://doi.org/10.11124/JBIES-21-00300.
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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 | 0.052 | 0.112 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| 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".