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<p>Mobile sound level applications have been proposed as potential adjuncts for conventional sound level meters (SLM) in noise measurement. However, their performance remains uncertain in the manufacturing industry setting. This study was aimed to determine the validity, reliability, and agreement of the NIOSH SLM app in measuring noise in the manufacturing industry with reference to conventional SLM. A total of 93 samples were collected from five machineries. An iPhone 12 Pro and an iPhone 12 mini, each installed with the latest version of NIOSH SLM app, were tested against the conventional SLM (as gold standard). Three noise parameters, namely the average noise level (i.e., LA<sub>eq</sub>), maximum sound level (i.e., L<sub>Max</sub>) and 8-hour time-weighted average (i.e., TWA-8&#xa0;h) were measured by all devices. Concurrent validity was assessed using Pearson’s correlation coefficient while two-way mixed effects intraclass correlation coefficient (ICC 3,1) was used to assess the intra-rater reliability. The agreement in the noise parameters measured was assessed using the Bland-Altman plot. The NIOSH SLM app demonstrated high concurrent validity, as measured by Pearson’s correlation (<i>p</i> &lt; 0.001) and moderate-to-good reliability, as measured by ICC 3,1 (<i>p</i> &lt; 0.001) in all three noise parameters measured. The LA<sub>eq</sub> and TWA-8&#xa0;h measured by the NIOSH SLM app were in agreement with the conventional SLM, with the exception of L<sub>Max</sub>. The NIOSH SLM app is valid and reliable in measuring noise when compared to conventional SLM. Two out of three noise parameters measured by NIOSH SLM app were agreeable to that measured by the conventional SLM.</p>

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NIOSH sound level meter application as an adjunct in noise measurement in manufacturing industry

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月29日

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  • Zhi Qing Ooi,
  • Sheng Qian Yew,
  • Azizah Zafira,
  • Nur Alya Asyqin Irwan Syarzizi,
  • Chan Hui Ying,
  • Mohammad Fuad Mohammad Affader

摘要

Mobile sound level applications have been proposed as potential adjuncts for conventional sound level meters (SLM) in noise measurement. However, their performance remains uncertain in the manufacturing industry setting. This study was aimed to determine the validity, reliability, and agreement of the NIOSH SLM app in measuring noise in the manufacturing industry with reference to conventional SLM. A total of 93 samples were collected from five machineries. An iPhone 12 Pro and an iPhone 12 mini, each installed with the latest version of NIOSH SLM app, were tested against the conventional SLM (as gold standard). Three noise parameters, namely the average noise level (i.e., LAeq), maximum sound level (i.e., LMax) and 8-hour time-weighted average (i.e., TWA-8 h) were measured by all devices. Concurrent validity was assessed using Pearson’s correlation coefficient while two-way mixed effects intraclass correlation coefficient (ICC 3,1) was used to assess the intra-rater reliability. The agreement in the noise parameters measured was assessed using the Bland-Altman plot. The NIOSH SLM app demonstrated high concurrent validity, as measured by Pearson’s correlation (p < 0.001) and moderate-to-good reliability, as measured by ICC 3,1 (p < 0.001) in all three noise parameters measured. The LAeq and TWA-8 h measured by the NIOSH SLM app were in agreement with the conventional SLM, with the exception of LMax. The NIOSH SLM app is valid and reliable in measuring noise when compared to conventional SLM. Two out of three noise parameters measured by NIOSH SLM app were agreeable to that measured by the conventional SLM.