Elevated Sound Levels in the Neonatal Intensive Care Unit
Bibliographic record
Abstract
BACKGROUND: Premature and sick neonates may require weeks of hospitalization in a noisy neonatal intensive care unit (NICU) environment with sound levels that may reach 120 decibels. The American Academy of Pediatrics recommends a maximum sound level of 45 decibels. PURPOSE: To measure sound levels in a level III NICU and to describe contributing environmental factors. METHODS: Descriptive quantitative study. Sound levels were measured using a portable sound meter in an open-bay level III NICU. Contributing environmental factors were recorded and analyzed. RESULTS: Mean sound levels for day, evening, and night shifts were 83.5, 83, and 80.9 decibels, respectively. Each period of time exceeded the recommended guidelines 90% of the time and was almost double the American Academy of Pediatrics' recommendation. Multiple linear regression findings demonstrated significant factors associated with elevated sound levels including number of neonates, number of people, number of alarms, acuity level, and shift type. Observational data explain 14.5% of elevated sound levels. IMPLICATIONS FOR PRACTICE: An understanding of baseline sound levels and contributing environmental factors is the first step in developing strategies to mitigate excessive noise in the NICU. IMPLICATIONS FOR RESEARCH: Research should focus on effective and sustainable ways to reduce sound levels in the NICU, including inside the isolette, in order to provide an environment that is conducive to optimal growth and neurodevelopment for preterm and sick infants.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".