Knowledge of Prenatal Healthcare among Pregnant Women in Boyer-Ahmad and Dena County of Kohgiluyeh and Boyer-Ahmad Province, Iran
Bibliographic record
Abstract
INTRODUCTION AND OBJECTIVE: Prenatal care knowledge is critical for pregnant women's use of antenatal services. The aim of the study was to assess the extent of prenatal healthcare knowledge among pregnant women of the Boyer-Ahmad and Dena County of Kohgiluyeh and Boyer-Ahmad Province, Iran. METHODS: A cross-sectional survey was conducted between April and June 2013. Pregnant women who came for delivery to the only available public hospital were interviewed by trained research assistants. Interview questions were designed to assess their knowledge on five broad categories of prenatal care practices of immunization, diet, supplementation, antenatal checkups and warning signs. Collected information was converted into numerical scores and average score for each individual was calculated. Independent-samples t-test, analysis of variance and multiple comparison tests were used to compare scores among groups with different demographic and socioeconomic status. RESULTS: A total of 400 pregnant women with 66.8% illiterate or lowly educated and an average age of 28.5 ± 6.1 years participated in the study. The average care knowledge score was 16.8 out of a maximum of 30. The highest awareness was observed on immunization (54.4%) and the lowest for prenatal checkup (20.3%).The average knowledge scores were significantly different among age groups, educational level, number of gravidity, type of occupation, place of residence and time of starting of prenatal care. There were no significant differences between women with and without obstetric complications. CONCLUSION: Not surprisingly, the level of education was the most significant factor influencing women's knowledge of parental healthcare, reinforcing the need for the improvement in literacy and expansion of health education among pregnant women using various educational methods.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".