Influence of Gaussian White Noise on Medical Students' Capacity to Accurately Identify Pulmonary Sounds.

IF 1.3 4区 医学 Q3 AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY
Noise & Health Pub Date : 2024-10-01 Epub Date: 2024-12-30 DOI:10.4103/nah.nah_98_24
Haroldas Razvadauskas, Jurgita Razvadauskienė, Martynas Aliulis, Rūta Aliulytė, Albinas Naudžiūnas, Renata Paukštaitienė, Saulius Sadauskas
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引用次数: 0

Abstract

Background: The 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.

Results: The 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%.

Conclusion: This 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.

高斯白噪声对医学生准确识别肺音能力的影响
背景:在标准化条件下,背景噪声对不同肺音类别听诊准确性的影响,特别是在中低水平下,很大程度上仍未被探索。本文旨在评估三个级别的高斯白噪声(GWN)对识别三类肺音能力的影响。方法和材料:进行了一项评估GWN对一组学生识别肺音能力的影响的前后试点研究。三种强度分别应用于无GWN、信噪比(SNR)、信噪比40(中等)和信噪比20(高)三类肺音。这导致了三次考试,每次有9个问题。52名参与者接受了为期4天的培训计划,并测试了他们在三个级别的GWN下识别肺音类别的能力,但7名受试者因未完成所有三个评估而被排除在外。对45名受试者进行统计分析,采用非参数检验对数据进行分析。p值为0.05认为有统计学意义。结果:GWN对医学生的整体肺音识别能力没有影响,在三种噪音水平下,所有三种肺音类别的得分一致为66.7%。然而,当单独考虑声音类别时,GWN影响正常(NAS)和不连续(DAS)类型的识别,但不影响连续(CAS)类型的识别。NAS的考试分数在三种噪音水平上差异显著,分别为66.7%,100%和66.7%。DAS的得分也各不相同,分别为66.7%、33.3%和66.7%。结论:本研究引入了一种标准化的模拟方法来研究GWN对医学生听诊准确性的影响。研究结果表明,虽然CAS声音对背景噪声具有鲁棒性,但NAS和DAS声音的识别可能会受到损害。噪声污染的中等噪声水平(信噪比为40)对DAS肺音的影响最大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Noise & Health
Noise & Health AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY-PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
CiteScore
2.10
自引率
14.30%
发文量
27
审稿时长
6-12 weeks
期刊介绍: Noise and Health is the only International Journal devoted to research on all aspects of noise and its effects on human health. An inter-disciplinary journal for all professions concerned with auditory and non-auditory effects of occupational, environmental, and leisure noise. It aims to provide a forum for presentation of novel research material on a broad range of topics associated with noise pollution, its control and its detrimental effects on hearing and health. It will cover issues from basic experimental science through clinical evaluation and management, technical aspects of noise reduction systems and solutions to environmental issues relating to social and public health policy.
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