A Randomized Controlled Trial of Early Kangaroo Care for Preterm Infants: Effects on Temperature, Weight, Behavior, and Acuity
Bibliographic record
Abstract
Kangaroo care (KC) has been the intervention for preterm infants in numerous published studies. However, most well designed studies to date have used a one-group repeated measure design. This methodology is not as definitive as an experimental design. Because of the absence of a comparable control group, change between pretest and posttest may be due to any other environmental variables or normal variation of subjects (Kirk, 1995). This randomized controlled trial (RCT) was done to test the hypotheses that KC infants would have higher mean tympanic temperatures, less weight loss, more optimal behavioral states, and lower acuity (length of stay). Thirty-four eligible mother-infant dyads were randomly assigned to the KC or the control group by computerized minimization on the day following birth. Stratification variables included infant gender, birth weight, delivery method, and parity. KC infants compared to control infants had higher mean tympanic temperature (37.3 degrees C vs. 37.0 degrees C), more quiet sleep (62% vs. 22%), and less crying (2% vs. 6%) all at p=.000. No significant difference was found for weight loss and acuity (length of stay). These findings can be used for evidence-based nursing practice in Taiwan. With the knowledge attained from this RCT, nurses can educate and motivate mothers to keep their stable preterm infants warm by skin-to- skin contact inside their clothing, thereby encouraging self-regulatory feeding.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".