Experiences of birthing care during COVID-19: a systematic review protocol
Bibliographic record
Abstract
ABSTRACT Objective: The objective of this review is to explore and understand the birthing care experiences of midwives, nurses, women, and birthing people during COVID-19. Introduction: The COVID-19 pandemic has had implications for providing and receiving birthing care globally. In addition to navigating fears of contracting COVID-19, health care providers and families have had to adapt to changing policies and clinical practices in response to varying recommendations and evidence. These changes, including restrictive visitor policies and mandated mask-wearing, influenced the experience of birthing care. Synthesizing qualitative evidence about the birthing experiences of midwives, nurses, women, and birthing people (people who give birth but who do not identify as women) during COVID-19 can provide important information for policies and decision-making for future global pandemics. Inclusion criteria: Studies including licensed midwives, licensed nurses, women, and birthing people who provided or received birthing care during the COVID-19 pandemic will be considered. Studies published from January 2020 onward will be included. The review will consider all studies that present qualitative data, including, but not limited to, research designs such as phenomenology, ethnography, grounded theory, feminist research, and action research. Methods: The following databases will be searched: MEDLINE, Embase, CINAHL, PsycINFO, and LitCovid. MedArchiv, PsyArXiv, and Google Scholar will be searched for gray literature. Studies will be assessed independently by two reviewers. Any disagreements will be resolved through discussion or with a third reviewer. Data extraction will be completed by two reviewers. The JBI tools and resources will be used for meta-aggregation, including the creation of categories and synthesized findings. Systematic review registration number: PROSPERO CRD42021292832
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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 | 0.094 | 0.084 |
| Meta-epidemiology (narrow) | 0.004 | 0.006 |
| Meta-epidemiology (broad) | 0.017 | 0.012 |
| Bibliometrics | 0.023 | 0.018 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.069 | 0.009 |
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".