Reproductive health and neonatal consequences of unintended childbearing among Saudi women
Bibliographic record
Abstract
Background: The incidence of unintended pregnancy is among the most essential health status indicators in the field of reproductive health. Women who have an unintended pregnancy are also at risk for unintended childbearing, which is associated with a number of adverse maternal behaviors and child health outcomes, including inadequate or delayed initiation of prenatal care, smoking and drinking during pregnancy, premature birth, and lack of breastfeeding, as well as negative physical and mental health effects on children. Aim of the study: The aim of the study is to identify the factors associated with unintended pregnancy and the neonatal outcomes of unintended pregnancy among Saudi women. Method: A comparative study conducted at two hospitals in Riyadh city. A non-probability convenient sample of 99 Saudi post-partum women age between (17 - 37) years and above, planned & unplanned pregnant women. A Structured interviewing questionnaire developed to collect data related to: Socio-Demographic characteristics, Reproductive Health and Pregnancy outcomes. Results: Unexpected result is that women with one child more frequently among women with unplanned pregnancies (10.1%) and less among women with planned pregnancies (5.1%), while women with two children more frequently among women with unplanned pregnancies (71%), and less for women with planned pregnancies (4.0%). There were no statistically significant differences between planned and unplanned pregnancies in the percentages of Number of antenatal care visits, live births and stillbirths, newborn birth weight or preterm births. Conclusion\recommendations: Reproductive health behaviors are threatening for maternal, and newborn especially in regard to antenatal follow-up awareness.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".