Nurses’ Awareness of Preterm Neonates’ Sleep in the NICU
Bibliographic record
Abstract
INTRODUCTION: Fetus and neonate spend most of their time sleeping inside and outside the womb. Sleep is considered a crucial action of neonatal period similar to breathing and nutrition. It plays a key role in brain development. Today, it is shown that sleep plays a predominant role in body temperature regulation, energy saving and neuronal detoxification. Sleep is the most important behavioral state of neonates, particularly in preterm ones. Noise, light, invasive treatment and caring activities are among disturbing factors in the neonatal intensive care unit (NICU) that leave negative impacts on brain development through disturbing the sleep process. MATERIALS & METHODS: This descriptive study assessed all NICU nurses of Ali-ibn-Abitaleb hospital using the census sampling method. Demographic data was collected through a questionnaire with 10 questions about active sleep (AS) cycles, also referred to as REM, methods for inducing AS and AS specifications in neonates. The questionnaire was distributed between the nurses. After completion, data was analyzed using SPSS 16 and descriptive statistics method. FINDINGS: According to analyses, 24%, 20%, 48% and 92% of nurses gave correct answers to questions about AS cycle, AS in neonates, the role of sleep in saving energy and ideal noise level, respectively. CONCLUSION: According to results, nurses had a low level of knowledge towards neonatal sleep. All nurses need to know the importance of sleep in preterm neonates. The main role of inducing sleep is to protect the development of the neonates' brain in the NICU. Those nurses who spend a remarkable portion of their time for caring neonates in the NICU play a significant role in neonatal sleep care.
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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 | 0.008 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".