ArticleNoise & health
Influence of Gaussian White Noise on Medical Students' Capacity to Accurately Identify Pulmonary Sounds.
Article in Noise & health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThe effect of background noise on auscultation accuracy for different lung sound classes under standardised conditions, especially at lower to medium levels, remains largely unexplored. This article aims to evaluate the impact of three levels of Gaussian white noise (GWN) on the ability to identify three classes of lung sounds. METHODS AND MATERIALS: A pre-post pilot study assessing the impact of GWN on a group of students' ability to identify lung sounds was conducted. The three intensities were applied to the three classes of lung sounds: no GWN, signal-to-noise ratio (SNR), SNR-40 (medium level) and SNR-20 (high). This resulted with three exams, each containing nine questions. Fifty-two participants underwent a 4-day training programme and were tested on their identification of lung sound classes under the three levels of GWN, but seven subjects were excluded for not completing all three assessments. Statistical analysis was performed on 45 subjects, using non-parametric tests to analyse the data. A P-value of 0.05 was considered statistically significant.
resultsThe GWN did not impact the overall lung sound identification capacity of medical students, with consistent scores of 66.7% across the three noise levels for all three lung sound classes combined. However, when considering sound classes separately, GWN affected the identification of normal (NAS) and discontinuous (DAS), but not continuous (CAS) types. Exam scores for NAS varied significantly across the three noise levels, with respective scores of 66.7%, 100% and 66.7%. Scores for DAS also varied, revealing 66.7%, 33.3% and 66.7%.
conclusionThis study introduces a standardised simulation-based approach to investigate the effect of GWN on the accuracy of auscultation amongst medical students. Findings indicate that whilst CAS sounds are robust to background noise, the identification of NAS and DAS sounds can be compromised. The medium noise levels (SNR-40) of noise pollution had the greatest effect on the DAS lung sounds.
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