MétaCan
Menu
Back to cohort
Record W4205451544 · doi:10.31083/j.ceog4901021

Development of patient-centered outcomes for labour and birth: a qualitative study

2022· article· en· W4205451544 on OpenAlexafffund
Geoffrey E. Johnson, Lauren Kan, Jennifer Nguyen, Kim Campbell, Laura Ralph, Nicole Koenig, May Sanaee, Ciana Maher, Geoffrey W. Cundiff

Bibliographic record

VenueClinical and Experimental Obstetrics & Gynecology · 2022
Typearticle
Languageen
FieldMedicine
TopicMaternal and Perinatal Health Interventions
Canadian institutionsUniversity of AlbertaWomen's Health Research InstituteUniversity of British Columbia
FundersSt. Paul's Foundation
KeywordsThematic analysisMedicineReadabilityQualitative researchComprehensionFocus groupPerspective (graphical)NursingPatient satisfactionFamily medicineHealth careQuality (philosophy)

Abstract

fetched live from OpenAlex

Background: Current quality improvement models in obstetrics focus on prevention of adverse perinatal outcomes. The development of these metrics was based on expert opinion that did not account for patients’ values. The ultimate aim of our research is to develop performance indicators for labour and birth that reflect the patient perspective. Methods: A qualitative interview design was used to engage a convenience sample, of recent (<1 year) postpartum patients, in semi-structured interviews, where they shared their experiences of their recent birth. Patients were also asked to assess descriptions of adverse perinatal outcomes for readability and comprehension, towards developing accurate unbiased descriptions for a subsequent survey of patients to weight complications. Responses were recorded, transcribed, coded and analyzed using thematic analysis. thematic analysis. Results: Five themes emerged during the analysis: (1) desire for patient-centred care, (2) improved communication, (3) labour/birth, expectations and outcomes, (4) care team support during labour and birth, (5) continuing emotional and physical postpartum care. Conclusions: Patient-centred care and good health outcomes were the major values expressed by the patients in this study. Good communication and shared decision making led to patients describing their labour and birth as a satisfying experience. This study lays the foundation for developing a quality tool to measure the outcomes of birth and adverse outcomes from the patients’ perspective.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.124
GPT teacher head0.472
Teacher spread0.348 · 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 designObservational
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
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueClinical and Experimental Obstetrics & GynecologySame topicMaternal and Perinatal Health InterventionsFrench-language works237,207