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Web- and app-based tools for remote hearing assessment: a scoping review.
Ibrahim Almufarrij1,2, Harvey Dillon1,3, Piers Dawes1,4
1Manchester Centre for Audiology and Deafness, School of Health Sciences, University of Manchester, Manchester, UK.
Remote hearing assessment tools vary widely in functionality, with most lacking peer-reviewed validation. Accuracy and reliability remain largely unknown, hindering widespread adoption for hearing care.
Area of Science:
- Audiology and Hearing Science
- Digital Health and Telemedicine
Background:
- Remote hearing screening and assessment technologies offer potential to enhance access to and engagement with hearing healthcare services.
- A comprehensive review is needed to evaluate the current landscape of digital tools for hearing assessment.
Purpose of the Study:
- To identify and evaluate the functionality of remote hearing assessment tools available on smartphones and online platforms.
- To determine if these tools have undergone peer-reviewed evaluation.
- To report on the accuracy and quality of existing validation data for these remote assessment tools.
Main Methods:
- A systematic scoping review was conducted, adhering to PRISMA-Extension guidelines.
- 187 remote hearing assessment tools (utilizing tones, speech, self-report, or combinations) and 101 validation studies were included.
- Quality, functionality, bias, and applicability of each tool were assessed by at least two independent reviewers.
Main Results:
- Significant variability in functionality was observed among the assessed remote hearing assessment tools.
- Only 22% of the tools were peer-reviewed, and just 14 demonstrated acceptable functionality.
- The quality and results of validation studies varied considerably, often dependent on the tool's category.
Conclusions:
- The accuracy and reliability of most remote hearing assessment tools are currently undetermined.
- Tone-based tools offer approximate thresholds but face calibration and background noise challenges.
- Speech and self-report tools are less susceptible to environmental factors but typically do not provide pure-tone audiograms; language-independent materials may offer a universal solution for audiogram prediction.
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