Journal of American Science 2010;6(10) Women’s Awareness of Danger Signs of Obstetrics Complications
Bibliographic record
Abstract
Abstract: An exploratory descriptive study was conducted at two Maternal and Child Health Centers (MCH) selected randomly in Albeheira Governorate to assess women’s awareness of danger signs of obstetric complications. The study subjects consisted of 200 pregnant women attending the previously mentioned setting for tetanus toxiod immunization during pregnancy was enrolled in the study. (100 from each) A structured interview schedule was developed by the researcher after reviewing of the relevant literature and used to collect the necessary data. It comprised the following parts: Part I: Socio-demographic data such as age, level of education, occupation and number of family members…etc Part II: Obstetric characteristics such as gravidity, parity, abortions, antenatal follow up and presence of any complications. etc. Part III: questions related to knowledge about signs of obstetric complications, complaining of any obstetric complication, what to do if the woman has any of these signs. The study revealed that slightly more than one quarter of the study subjects (26.5 %) were unaware of obstetric danger signs compared to almost the same proportion (26.0 %) that had good awareness about such signs, while 47.5 % of the study subjects exhibited fair awareness. Lack of awareness about obstetric danger signs was related younger age, low level of education, gravidity and parity, previous experiences with any obstetric complications and lack of antenatal care. This study reflects the need for strategic plane to increase the awareness to shape health seeking
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.026 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".