Pengaruh Video Persalinan Normal terhadap Kecemasan Ibu Hamil Menghadapi Persalinan di Wilayah Kerja Puskesmas Pangaribuan Kecamatan Pangaribuan Kabupaten Tapanuli Utara
Bibliographic record
Abstract
Primigravida mothers in facing delivery would experience anxiety. Anxiety in pregnant women increases in the third trimester which can lead to complications for both the mother and the fetus. 80% of primigravida mothers experience anxiety just before delivery. Efforts that can be made to reduce anxiety can be by watching videos of normal childbirth. The aim of the study was to determine whether there was an effect of video of normal delivery on anxiety of pregnant women in facing childbirth in the Pangaribuan Health Centre, Pangaribuan District, North Tapanuli Regency in 2020.This study used a Quasi-Experimental Research type with the design used was One Group Pretest-Postest Design. The sample of this study were 10 pregnant women who were measured before and after the intervention watching normal childbirth videos. Based on the results the data analysis used univariate and bivariate analysis. Bivariate analysis using the Wilcoxon Rank Test, obtained a p value (Sig.2-tailed) of .006 <α: 0 .05, it can be concluded that there is an effect of Normal Delivery Videos on Anxiety of Pregnant Women Facing Childbirth in the Pangaribuan Health Centre, Pangaribuan District, District North Tapanuli 2020. These results conclude that there is a significant effect between normal delivery videos on the anxiety of pregnant women facing childbirth in the Pangaribuan Public Health Centre, Pangaribuan District, North Tapanuli . Suggestions for health care workers to provide more information to primigravida mothers about labor preparation to reduce feelings anxiety of pregnant women facing childbirth.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".