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Record W3209413912 · doi:10.1177/08445621211052141

Canadian Women's Experience of Postnatal Care: A Mixed Method Study

2021· article· en· W3209413912 on OpenAlexafffundvenueabout
Justine Dol, Brianna Hughes, Gail Tomblin Murphy, Megan Aston, Douglas McMillan, Marsha Campbell‐Yeo

Bibliographic record

VenueCanadian Journal of Nursing Research · 2021
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsIzaak Walton Killam Health CentreNova Scotia Health AuthorityDalhousie University
FundersCanadian Institutes of Health Research
KeywordsMedicineComputer sciencePsychologyObstetrics

Abstract

fetched live from OpenAlex

BACKGROUND: The postnatal period remains unstandardized in terms of care and postnatal visits with a dearth of information on the experience from Canadian women. PURPOSE: To explore (1) with whom and how often women receive postnatal follow-up visits and (2) the postnatal care experiences of Canadian mothers. METHODS: Using a cross-sectional design, women who had given birth within the past 6 months were recruited to complete an online survey. Frequencies were computed for quantitative outcomes and thematic analysis was used for qualitative responses. RESULTS: A total of 561 mothers completed the survey. Women saw on average 1.9 different postnatal healthcare providers, primarily family doctors (72.4%). 3.2% had no postnatal visits and 37.6% had 4 or more within 6 weeks. 76.1% women were satisfied with their postnatal care. Women's satisfactory care in the postnatal period was associated with in-person and at home follow-ups, receiving support, and receiving timely, appropriate care for self and newborn. Unsatisfactory care was associated with challenges accessing care, experiencing gaps in follow-up visits, and having unsatisfactory assessment for their own recovery. CONCLUSION: There is considerable variation in the timing and frequency of postnatal visits. While many women are experiencing satisfactory care, women are still reporting dissatisfaction and are facing challenges.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.088
GPT teacher head0.458
Teacher spread0.370 · 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 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

Citations14
Published2021
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Journal of Nursing ResearchSame topicMaternal Mental Health During Pregnancy and PostpartumFrench-language works237,207