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Record W4400621728 · doi:10.22374/cjmrp.v16i1.65

After the Unexpected: Ontario Midwifery Clients’ Experiences of Postpartum Hemorrhage

2024· article· en· W4400621728 on OpenAlexfundaboutno aff
Jenna Robertson, Sophia Kehler, Anna Meuser, Tasha MacDonald, Jenny Gilbert, Suzannah Bennett

Bibliographic record

VenueCanadian Journal of Midwifery Research and Practice · 2024
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsnot available
FundersAssociation of Ontario MidwivesWomen's College Hospital
KeywordsObstetricsMedicineNursingPsychology

Abstract

fetched live from OpenAlex

Background: The incidence of postpartum hemorrhage (PPH) varies worldwide. While there is abundant research to guide midwifery practice regarding the acute clinical management of PPH, there is less known about the psychological needs of clients and families following significant blood loss during birth, and no relevant research conducted in a Canadian setting. Methods: Analysis of qualitative data was conducted based on data from two focus groups and two online surveys with participants who had received midwifery care during at least one pregnancy and had experienced at least one PPH. Objective: The goal of this research was to describe the experiences of midwifery clients in Ontario who had suffered a PPH and to compare those findings to what is documented in existing literature. Findings: This study found a range of physical and emotional responses to the experience of PPH, ranging from no effect to short- or longer-term psychological trauma, which is consistent with a small but growing body of international studies. While the risk of delayed lactogenesis increases with PPH, most participants in this study reported no breastfeeding concerns. This study is unique in reporting on creative strategies families developed to cope with PPH. This article has been peer reviewed.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.346
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.068
GPT teacher head0.372
Teacher spread0.304 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations4
Published2024
Admission routes2
Has abstractyes

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