MétaCan
Menu
Back to cohort
Record W2046560660 · doi:10.1155/2014/649567

Unmet Need for Family Planning in Nepal during the First Two Years Postpartum

2014· article· en· W2046560660 on OpenAlexaboutno aff
Suresh Mehata, Yuba Raj Paudel, Ranju Kumari Mehta, Maureen Dariang, Pradeep Poudel, Sarah Barnett

Bibliographic record

VenueBioMed Research International · 2014
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
Fundersnot available
KeywordsFamily planningMedicineFertilityPostpartum periodUnintended pregnancyPregnancyEnvironmental healthRural areaQuarter (Canadian coin)Family medicineDemographyPopulationGeography

Abstract

fetched live from OpenAlex

Contraceptive use during the postpartum period is critical for maternal and child health. However, little is known about the use of family planning and the determinants in Nepal during this period. This study explored pregnancy spacing, unmet need, family planning use, and fertility behaviour among postpartum women in Nepal using child level data from the Nepal Demographic and Health Surveys 2011. More than one-quarter of women who gave birth in the last five years became pregnant within 24 months of giving birth and 52% had an unmet need for family planning within 24 months postpartum. Significantly higher rates of unmet need were found among rural and hill residents, the poorest quintile, and Muslims. Despite wanting to space or limit pregnancies, nonuse of modern family planning methods by women and returned fertility increased the risk of unintended pregnancy. High unmet need for family planning in Nepal, especially in high risk groups, indicates the need for more equitable and higher quality postpartum family planning services, including availability of range of methods and counselling which will help to further reduce maternal, perinatal, and neonatal morbidity and mortality in Nepal.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.197

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.055
GPT teacher head0.409
Teacher spread0.354 · 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

Citations59
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueBioMed Research InternationalSame topicGlobal Maternal and Child HealthFrench-language works237,207