Hubungan Prenatal Yoga, Nyeri Punggung dan Kualitas Tidur terhadap Kecemasan pada Ibu Hamil Trimester III
Bibliographic record
Abstract
Anxiety in pregnancy is an adverse risk factor for both mother and baby. At the Nagaswidak Public Health Center, out of 10 pregnant women, there were 8 third trimester pregnant women who experienced anxiety in facing the labor process. The purpose of this study was to determine the relationship between prenatal yoga, back pain and sleep quality on the anxiety of third trimester pregnant women. The research method used an analytical survey with a cross sectional approach with all third trimester pregnant women in the Nagaswidak Public Health Center area. The sampling technique was carried out by accidental sampling with a total sample of 44 respondents. Data collection using a questionnaire sheet. Data analysis using univariate analysis and bivariate analysis using chi square test. The results showed that there was a relationship between prenatal yoga, back pain and sleep quality with anxiety in third trimester pregnant women in the Nagaswidak Public Health Center working area in 2021. The conclusion is that there is a relationship between prenatal yoga , back pain and sleep quality on the anxiety of third trimester pregnant women at the Nagaswidak Health Center in 2021.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".