Examining the effects of a targeted noise reduction program in a neonatal intensive care unit
Bibliographic record
Abstract
OBJECTIVES: To determine whether implementation of a noise reduction policy followed by the addition of direct audit and feedback reduces noise levels in a tertiary-level neonatal intensive care unit (NICU). STUDY DESIGN: Noise level data was collected in three phases: (1) baseline (preintervention), (2) immediately postimplementation of our noise reduction policy, (3) postunveiling of direct audit and feedback mechanism. SETTING: A level 3 NICU in Ontario, Canada. INTERVENTIONS: Noise reduction policy and a direct audit and feedback mechanism. MAIN OUTCOME MEASURES: Average noise level. RESULTS: The baseline level of noise in our unit consistently exceeds guidelines with an average baseline noise of 49 dB (±1.4). Our intervention resulted in a significant reduction in noise levels for one of the four areas in our NICU [-1.06 dB (-1.52, -0.6)], with a trend towards reduction in a second area (-0.21 dB (-0.6, 0.18)). Unexpectedly, two other areas experienced a significant increase in noise (2.05 dB (1.18, 2.94); 0.85 dB (0.11, 1.59)). CONCLUSIONS: The baseline noise in the NICU consistently exceeds guidelines, but reductions in noise levels are achievable. Nonetheless, more work is needed to find the optimal NICU design and noise reduction strategy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".