JMIR Publications

ABSTRACT

Background:

Over-exposure to occupational noise can lead to hearing loss. Occupational noise mapping is conventionally measured with a calibrated Sound Level Meter (SLM). With the rise of mobile applications, there is a growing number of sound level meter applications (apps) available on mobile phones. However, few studies have evaluated such apps for accuracy and usefulness to guide those with occupational noise detection needs in selecting a quality app.

Objective:

The purpose of this study was to evaluate the accuracy and usefulness of sound level meter mobile applications to guide workplace health and safety professionals to determine their suitability in assessing occupational noise exposure.

Methods:

Three iOS applications were assessed, namely the NIOSH Sound Level Meter, the Decibel X App, and the SoundMeter X apps. The selected apps were evaluated for accuracy compared to a conventional SLM in both simulated (laboratory) and real-world environments. The usefulness of the apps was then assessed by occupational health specialists using the Mobile App Rating Scale (MARS).

Results:

The NIOSH Sound Level Meter app accurately measured noise across a range of sound levels in both simulated and real-world settings. However, the Decibel X app, and SoundMeter X app consistently underestimated noise levels suggesting they may pose a risk for workers. The MARS scores were all above 3.0, indicating the usefulness of all three apps.

Conclusions:

Under the conditions of the study, the NIOSH SLM app had equivalent accuracy to the calibrated SLM and a degree of usefulness according to the MARS scale. This suggest that the NIOSH Sound Level Meter app may be suitable for mapping noise levels as part of a monitoring strategy in workplaces. However, it is important to understand its limitations. Mobile apps should be complementary to but not a replacement for conventional SLM when trying to determine occupational noise exposure risk assessment. Outcomes also suggest the MARS tool may have limited applicability to measurement-based apps and may be more suited to information-based applications that collect, record and store information.