The Effect of Using Murottal Quran Therapy on Low Birth Weight Infants
Bibliographic record
Abstract
The birth of infants with low birth weight in Indonesia is still quite high. This condition largely causes neonatal mortality which is currently ranked the 10th highest in the world. Baby with Low birth weight may have health problems that will influence their life. The current health technology development has been able to improve the resistance of infants, although some previous research has explained that the medical and nursing procedures can cause stress in infants with low birth weight. Stress conditions in infants can lead to excessive use of energy so that it can lose a baby’s weight. Murottal therapy is one form of music therapies that can be used to reduce stress, decrease pain and stabilize physiological conditions such as vital signs and oxygen saturation. This study aimed at knowing the effect of Murrotal Therapy on the weight gain of premature infants. The research design was quasi experiment using pre post test control group design. The sampling technique used was consecutive sampling. 94 low birth weight infants who were being treated in perinatology taken as the sample of this study. Intervention was given for 30 minutes in the morning and afternoon for 7 days in row. The result of the research showed that there was an increase in infant weight that was 72.87 grams in the intervention group and the statistical test results revealed that there was a significant weight gain between the intervention group and the control group (p = 0.023). Therefore it can be concluded that the use of Murrotal Alquran Theraphy gave an effect on the infants’ weight gain, thus it is suggested to use this theraphy as part of nursing interventions for low birth weight infants in perinatology.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".