Systematic review of environmental noise in neonatal intensive care units
Bibliographic record
Abstract
AIM: To systematically review the literature on noise exposure within the neonatal intensive care unit/special care nursery settings, specifically to describe: noise characteristics, sources of noise and ways of measuring noise. METHODS: Systematic searches were conducted through databases Medline, Embase and PubMed. Studies were included if they met the inclusion criteria (1) reported noise characteristics; (2) reported noise exposure measurements; (3) in the neonatal intensive care unit/ special care nursery settings. Methods and key findings were extracted from included studies. Quality analysis was done using a modified version of the Newcastle-Ottawa Scale. RESULTS: We identified 1651 studies, screened 871, reviewed 112 and included 47. All reported NICU average equivalent sound levels were consistently louder than recommended guidelines (45 dB). The most consistent association with higher sound pressure levels were noise sources grouped under people congregation. Half of the studies did not use measuring devices adhering to international sound level meter (SLM) standards. CONCLUSION: All NICUs exceeded recommended accumulative sound levels. People were the most consistent source of noise. Sound pressure levels need to be consistently measured with devices adhering to international SLM standards in future studies.
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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 | 0.006 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".