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Record W3179556349 · doi:10.23880/nhij-16000224

Socio-Cultural Factors Affecting Pregnancy Outcomes in the Dangme West District of Ghana

2020· article· en· W3179556349 on OpenAlexaff
Adu J

Bibliographic record

VenueNursing & Healthcare International Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsSt. Joseph's Hospital
Fundersnot available
KeywordsChildbirthPregnancyMedicineFocus groupPovertyFunctional illiteracyDeveloping countryEnvironmental healthQualitative researchNursingFamily medicineEconomic growthBusinessPolitical science

Abstract

fetched live from OpenAlex

Background: Improvement in maternal healthcare services is crucial among nations as women are more vulnerable during pregnancy, especially in developing countries with poor health systems. This study assessed the socio-cultural factors that affect pregnancy outcomes in the Dangme West District of Ghana. Methods: Qualitative methods were employed using the Dangme West District. Data was collected using key informant interviews involving health professionals in the area of maternal health care and focus group discussions with women attending antenatal clinic in the district. Results: Findings from the study indicate that most women in the district attend antenatal clinics. They prefer delivering with Traditional Birth Attendants or in prayer camps to preserve their family tradition of not using health facilities during childbirth. Pregnancy outcomes are highly influenced by cultural traditions, with pregnant women avoiding nutritious foodstuffs such as eggs, certain types of fish, fatty meat, and some vegetables due to their beliefs, a situation resulting in pregnancy-related complications such as anaemia, premature delivery, and low birth weight. Key factors affecting maternal health outcomes include poverty, poor infrastructure in the district, nutrition, religious beliefs, illiteracy, and attitude of health professionals. Conclusions: This study reveals a range of socio-cultural factors that impact directly on maternal health outcomes and which need to be targeted through appropriate public health actions.

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)0.000
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 score0.124
Threshold uncertainty score0.360

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 integrity0.0000.001
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 head0.051
GPT teacher head0.377
Teacher spread0.327 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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