Pengaruh kombinasi pijat oksitosin dan teknik marmet terhadap produksi ASI ibu postpartum primipara
Bibliographic record
Abstract
Background: One of the causes of death is infection. Breast milk is the main food for newborn babies because it contains protective nutrients that can prevent infectious diseases in babies. One effort to improve the quality of breast milk is to stimulate the release of the hormone prolactin through oxytocin massage.Objective: To analyze the effect of a combination of oxytocin massage and the marmet technique on breast milk production in primiparous mothers.Method: This research design is quasi-experimental, using a one-group pre- and post-design research method and a sampling technique using consecutive sampling. The research was conducted in Bandung Regency on primiparous breastfeeding mothers. Univariate analysis to see the frequency and normality of the data (Shapiro Wilk test) and bivariate analysis for this study used a paired sample t test for 1 group with the Wilcoxon test to see the significance between before and after the intervention.Results: The results showed that the average breast milk production before the intervention was given was 24,22 ml, while after the intervention was given, it increased to 95,47 ml. So there was an increase in breast milk production of 71,25 ml after being given a combination of oxytocin massage and the marmet technique three times. The T-test results obtained a p-value of 0,000 < α (0,05), so it can be concluded that there is a significant difference in breast milk production before and after the intervention.Conclusion: There is a significant difference in breast milk production before and after the combination of oxytocin massage and the marmet technique. So, it is hoped that the smooth release of a mother's breast milk can increase the success of exclusive breastfeeding.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".