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Record W4386252196 · doi:10.11124/jbies-22-00453

Postpartum experiences of women, birthing people, and their families during COVID-19: a qualitative systematic review protocol

2023· article· en· W4386252196 on OpenAlexaff
Danielle Macdonald, Chelsea Publow, Amanda Ross‐White, Megan Aston, Erna Snelgrove‐Clarke

Bibliographic record

VenueJBI Evidence Synthesis · 2023
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Impact on Reproduction
Canadian institutionsDalhousie UniversityQueen's UniversityCentre for Excellence in Mining Innovation
Fundersnot available
KeywordsCINAHLPsycINFOQualitative researchNursingPostpartum periodMEDLINEGrounded theoryPandemicMedicineGrey literaturePsychologyCoronavirus disease 2019 (COVID-19)Psychological interventionSociologyPregnancyPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of the review is to explore and understand the postpartum experiences of birthing people and their families during COVID-19. INTRODUCTION: Positive postpartum experiences are formative for the long-term health and well-being of parents and babies. However, the COVID-19 pandemic has complicated the transition to parenthood and existing postpartum challenges through evolving policies and practices, including visiting limitations, masking requirements, and reduced accessibility of supports. Understanding the impact of COVID-19 on the postpartum experiences of women, birthing people (people who give birth but may not identify as women), and their families through the synthesis of qualitative evidence can help inform public health and government directives in comparable future contexts. INCLUSION CRITERIA: Studies including women, birthing people, and their families who experienced postpartum during the COVID-19 pandemic will be considered. This review will include studies published after January 2020 that explore postpartum experiences up to 1 year following birth. We will examine 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 (Ovid), Embase (Ovid), CINAHL (EBSCOhost), PsycINFO (Ovid), and LitCovid. PsyArXiv and Google Scholar will be searched for gray literature. Studies will be assessed and appraised independently by 2 reviewers and disagreements will be resolved through discussion or with a third reviewer. Data extraction will be completed by 2 reviewers. The JBI tools and resources will be used for assessing confidence and meta-aggregation, including the creation of categories and synthesized findings. REVIEW REGISTRATION: PROSPERO CRD42022364030.

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)0.005
metaresearch head score (Gemma)0.112
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score0.896

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.112
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.404
Teacher spread0.367 · 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 designQualitative
Domainnot available
GenreEmpirical

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

Citations1
Published2023
Admission routes1
Has abstractyes

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