MétaCan
Menu
Back to cohort
Record W3005498676 · doi:10.1891/1078-4535.26.1.e25

Quality of Antenatal Care Services in a Developing Country: A Cross-Sectional Survey

2020· article· en· W3005498676 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCreative Nursing · 2020
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsCross-sectional studyDeveloping countryQuality (philosophy)Environmental healthMedicinePublic healthHealth careFamily medicineNursingEconomic growth

Abstract

fetched live from OpenAlex

The global adult lifetime risk of maternal mortality is 1 in 180; in Pakistan, it is 1 in 170; in developed regions, 1 in 4,900 (Alkema et al., 2016; Filippi, Chou, Ronsmans, Graham, & Say, 2016; World Health Organization [WHO], 2015). The differences in maternal mortality between developed and developing countries are mainly due to the quality of antenatal care (ANC) available in the two groups of countries. The purpose of this study was to assess the structural and procedural quality of ANC services provided and to assess satisfaction levels of women receiving ANC services in two large hospitals in Islamabad, Pakistan. A cross-sectional survey was conducted at the hospitals' outpatient maternal and child health clinics, with a random sample of 138 women. The overall quality of ANC was rated as good (61%), average (17.5%), or poor (17.5%). The findings suggest a need to cultivate quality of care at public health facilities, train health workers in communication skills, and build technical capacity by continuing education and supportive supervision to train health-care providers to follow standard protocols for provision of quality ANC services.

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.

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)0.000
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 score0.003
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.072
GPT teacher head0.407
Teacher spread0.335 · 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