Perbedaan Skor Nyeri pada Anak dengan Pemberian Madu Setelah Dilakukan Tindakan Pemasangan Infus
Bibliographic record
Abstract
Intravenous fluid therapy in a child in the emergency room may lead to prolonged trauma and is a procedure that can cause anxiety, fear and uncomfortable pain. Handling of pain in children can be done with non-pharmacological techniques that are by giving a sweet taste of honey, wherein honey contains flavonoid content that can inhibit the pain. The purpose of this study was to know differences in pain scores after the installation of infusion between groups of children given honey and not given honey. The research design used in the form of quasi-experiment with nonequivalent control group type, post-only design, with the number of samples were 34 people who met the inclusion criteria. The sample was divided into two groups: the intervention group who received honey peroral (17 respondents) and the control group who did not get honey peroral (17 respondents), with age of respondent 1-6 years. Pain scores were evaluated with Children's Hospital of the Eastern Ontario Pain Scale (CHEOPS). A statistical test was using Mann-Whitney test with 95% (α=0,05 ) incidence rate. The result showed that there was a difference in child pain score in intervention group and control group with p-value=0.000. It can be concluded that there was an effect of giving honey to pain score, wherein the intervention group the pain score was lower than the control group, meaning that honey can reduce the pain response in children.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".