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Record W4383498773 · doi:10.24124/2023/59403

Mothers’ experiences of team-based antenatal care in rural British Columbia

2023· dissertation· en· W4383498773 on OpenAlexaffabout
Amanda Green

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsUniversity of VictoriaUniversity of Lethbridge
Fundersnot available
KeywordsNursingContext (archaeology)Maternity carePerspective (graphical)Qualitative researchMedicineContinuity of careHealth carePsychologyFamily medicineSociologyPolitical science

Abstract

fetched live from OpenAlex

Introduction: The health care system in British Columbia places priority on providing teambased primary maternity care. Participation of mothers in planning their care is an essential component of team-based care. Therefore, it is important to understand mothers’ experiences of team-based maternity care. Background: An integrated literature review resulted in 12 articles focused on mothers’ experiences with antenatal care delivered by a team of providers. Evidence highlighted the positive impact of team-based speciality antenatal care. Mother’s experiences of community team-based antenatal care were a notable gap in the literature. Objective: To explore antenatal care experiences of mothers living in rural British Columbia, where team-based antenatal care is known to exist. Method: To understand the perceptions of mothers' experiences of team-based antenatal care a qualitative methodology was used. An interpretive description approach combined semi-structured interviews with eight mothers purposively selected from two rural communities. Findings: Mothers played a key role in shaping the continuity of their care. Mothers collaborated with their providers across three types of continuity expressed within a team-based antenatal care context: management, informational, and relational. Building the relationship between the mother and a consistent provider (relational continuity) required clinical coordination (management continuity) and clear communication (informational continuity). From the mother's perspective, a specific team composition did not rate as highly as the connection to a consistent provider with whom they had respectful and trusting relationship. For all eight mothers a nurse and physician team-combination promoted continuity and patient-centeredness. Specifically, a primary care maternity nurse role supported stability in the mother's antenatal care. Gaps in continuity arose from experiences of antenatal care during the Covid-19 global pandemic and in the mothers’ mental wellness and pelvic floor health. Conclusion: When the mothers shared responsibility for continuity in care this strengthened the mother-provider partnership, regardless of which discipline was providing care. Mothers appreciated the continuity of carer – a provider who could develop a relationship with them during their antenatal care. The mothers valued providers who worked as part of a network, collaborating with a range of interdisciplinary providers to support the mothers’ antenatal care needs. Clinical Implications: There is merit in expanding discussions on the value a consistent provider working alongside mothers in rural team-based primary maternity care brings to mothers’ experiences of and engagement with antenatal care. Future research on how both continuity of care and continuity of a carer can support sustainable team-based antenatal care to improve outcomes is warranted in all community contexts.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.410
Threshold uncertainty score0.824

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.014
GPT teacher head0.327
Teacher spread0.312 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes2
Has abstractyes

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