ASSOCIATION BETWEEN KNOWLEDGE AND COMPLIANCE OF TAKING IRON/FOLIC ACID SUPPLEMENTS DURING PREGNANCY
Bibliographic record
Abstract
Objective: In Indonesia, pregnant women are recommended to take a minimum of 90 tablets of iron/folic acid (IFA), to prevent iron deficiency anemia. Our analysis aimed at examining the extent to which improved knowledge on IFA supplementation is associated with women’s compliance with taking a minimum of 90 IFA tablets during their last pregnancy in four districts in Indonesia.Methods: Data were derived from a cross-sectional study conducted in four districts, that is, Lebak and Pandeglang District (Banten Province) as well as Purwakarta and Subang District of West Java Province, Indonesia on June 2014. We used information from 436 mothers who delivered their baby in the last 6 months from the time of the survey and received at least 90 IFA tablets during her last pregnancy. Logistic regression analysis was used to examine the role of knowledge after controlling for confounders and other significant predictor on compliance with taking a minimum of 90 IFA tablets during pregnancy.Result: Significant association was found between knowledge of IFA supplements and compliance. Compared to women with poor knowledge of IFA supplementation, the odds of taking a minimum of 90 IFA tables increased by almost 100% in women with moderate knowledge (adjusted odd ratio [aOR]=1.96, 95% confidence interval [CI]: 1.17-3.30, p=0.011); and by more than four times (aOR=5.42, 95% CI: 1.76-16.68, p=0.003) in women with good knowledge of IFA supplementation. Other factors associated with compliance was attendance in at least four antenatal services (aOR=5.71, 95% CI: 1.28-25.53, p=0.023) and pregnant women experience of no side effects resulting from taking IFA tablets during pregnancy (aOR=2.70, 95% CI: 1.63-4.46, p<0.001).Conclusions: Efforts to increase women’s knowledge on IFA supplementation through community-based education will increase women’s compliance of taking IFA supplements. Strengthening counseling services on potential side effects of IFA supplementation and ways to manage them will also help to improve compliance.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".