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Record W2778239536

Factors Associated with Incidence of Induced Abortion in Hamedan, Iran.

2017· article· en· W2778239536 on OpenAlexaff
Hatam Hosseini, Amir Erfani, Marzieh Nojomi

Bibliographic record

VenuePubMed · 2017
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsNipissing University
Fundersnot available
KeywordsAbortionMedicineFamily planningLogistic regressionIncidence (geometry)DemographyFertilityUnintended pregnancyPregnancyReproductive healthObstetricsPopulationEnvironmental healthResearch methodology
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: There is limited reliable information on abortion in Iran, where abortion is illegal and many women of reproductive age seek clandestine abortion to end their unintended pregnancy. This study aims to examine the determinants of induced abortion in the city of Hamedan, Iran. METHODS: The study utilizes recent data from the 2015 Hamedan Survey of Fertility, conducted in a representative sample of 3,000 married women aged 15-49 years in the city of Hamedan, Iran. Binary logistic regression models are used to examine factors associated with the incidence of abortion. RESULTS: Overall, 3.8% of respondents reported having had an induced abortion in their life. Multivariate results showed that the incidence of abortion was strongly associated with women's education, type of contraceptive and family income level, after controlling for confounding factors. Women using long-acting contraceptive methods, those educated under high school diploma or postsecondary education, and those with high level of income were more likely to report having an induced abortion. CONCLUSION: The high incidence of abortion among less or more educated women and those with high income level signifies unmet family planning needs among these women, which must be addressed by focused reproductive health and family planning programs.

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)0.002
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 score0.020
Threshold uncertainty score0.246

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.117
GPT teacher head0.319
Teacher spread0.202 · 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

Citations20
Published2017
Admission routes1
Has abstractyes

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