Remote characterization of auditory and cognitive processing
Previous research has demonstrated that remote testing of suprathreshold auditory function using distributed technologies can produce results that closely match those obtained in laboratory settings with a specialized, calibrated equipment. This work has facilitated internet-based recruitment of participants and the validation of various behavioral measures that provide valuable insights into auditory function. These measures include aspects of auditory processing, self-reported hearing difficulties, and cognition. In this study, we used the portable psychophysics assessment tool (PART) along with online participant recruitment to test a wide variety of audition-relevant measures in those with (n = 92) and without (n = 100) self-reported hearing loss. We assessed each measure’s ability to discriminate between these two groups, as well as their reliability and multi-variate relationships. We found that several measures of auditory processing effectively differentiated between the groups. All previously tested measures showed similar test–retest reliabilities with this online approach. Additionally, multi-variate relationships, including cognition and self-reported hearing, were strikingly consistent across groups. In sum, this work further validates remote testing as a reliable general methodology.
Authors
- Aaron R. Seitz (ORCID: https://orcid.org/0000-0003-4936-9303)
- G. Christopher Stecker (ORCID: https://orcid.org/0000-0003-1442-9839)
- Audrey A. Carrillo
- Tess K. Koerner (ORCID: https://orcid.org/0000-0002-8861-0262)
- E. Sebastian Lelo de Larrea-Mancera (ORCID: https://orcid.org/0000-0001-8626-5621)
- William J. Bologna (ORCID: https://orcid.org/0000-0003-1851-6892)
- Katherine N. Menon
- Eric C. Hoover (ORCID: https://orcid.org/0000-0002-1187-9925)
- Frederick J. Gallun (ORCID: https://orcid.org/0000-0002-4145-2199)
Institutions
- Northeastern University (US)
- Boys Town (US)
- Oregon Health & Science University (US)
- Boys Town National Research Hospital (US)
- Towson University (US)
- University of Maryland, College Park (US)
Publication Details
- Journal
- The Journal of the Acoustical Society of America
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1121/10.0035231
- Primary Topic
- Neural Networks and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00