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Record W4213197673 · doi:10.11124/jbies-21-00300

Experiences of birthing care during COVID-19: a systematic review protocol

2022· review· en· W4213197673 on OpenAlexaff
Danielle Macdonald, Erna Snelgrove‐Clarke, Amanda Ross‐White, Kristen Bigelow-Talbert

Bibliographic record

VenueJBI Evidence Synthesis · 2022
Typereview
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsQueen's UniversityCentre for Excellence in Mining Innovation
Fundersnot available
KeywordsCINAHLPsycINFOMEDLINEPandemicNursingHealth careQualitative researchMedicineCoronavirus disease 2019 (COVID-19)PsychologyPolitical scienceSociologyPsychological intervention

Abstract

fetched live from OpenAlex

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

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.358
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.000

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.

Opus teacher head0.083
GPT teacher head0.463
Teacher spread0.380 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations4
Published2022
Admission routes1
Has abstractyes

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