The Effect of Counselling Intervention during Antenatal Care on the Knowledge and Attitude about Danger Signs in Pregnancy: A Cross-Sectional Study in Takalar Regency
Bibliographic record
Abstract
Objective: This study was to examine the effects of counselling delivered during antenatal care on the knowledge and attitudes of pregnant women about danger signs in pregnancy.Methods: This was a pre-experimental design using one group pre- and post-test only. This study was conducted in Takalar, specifically within Sanrobone Community Health Service working area. Takalar is located in South Sulawesi Province Indonesia and this area is coastal with the majority of people working as a fisherman. Participants of this study were pregnant women living in the villages which are included in the working area of Sanrobone Community Health Service.Results: The study shows that counselling improved knowledge and attitude of pregnant women about danger signs in pregnancy (p=0.011 and p=0.025, respectively). The number of pregnant women with good knowledge and positive attitude increased after the intervention (43.8% vs 93.8%, 62.5% vs 93.8%, respectively).Conclusions: In can be concluded that intervention by means of counselling can improve the knowledge and attitude of pregnant women about danger signs in pregnancy. Therefore, it is important to implement the counselling program delivered by health workers in Community Health Service in order to mitigate the risk of maternal mortality.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".