Literature DB >> 16646276

Homogeneity of the 18 QuickSIN lists.

Rachel A McArdle1, Richard H Wilson.   

Abstract

The purpose of this study was to determine the list equivalency of the 18 QuickSIN (Quick Speech in Noise test) lists. Individuals with normal hearing (n = 24) and with sensorineural hearing loss (n = 72) were studied. Mean recognition performances on the 18 lists by the listeners with normal hearing were 2.8 to 4.3 dB SNR (signal-to-noise ratio), whereas the range was 10.0 to 14.3 dB SNR for the listeners with hearing loss. The psychometric functions for each list showed high performance variability across lists for listeners with hearing loss but not for listeners with normal hearing. For listeners with hearing loss, Lists 4, 5, 13, and 16 fell outside of the critical difference. The data from this study suggest nine lists that provide homogenous results for listeners with and without hearing loss. Finally, there was an 8.7 dB difference in performances between the two groups indicating a more favorable signal-to-noise ratio required by the listeners with hearing loss to obtain equal performance.

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Mesh:

Year:  2006        PMID: 16646276     DOI: 10.3766/jaaa.17.3.2

Source DB:  PubMed          Journal:  J Am Acad Audiol        ISSN: 1050-0545            Impact factor:   1.664


  12 in total

1.  Sensorineural Hearing Loss Diminishes Use of Temporal Envelope Cues: Evidence From Roving-Level Tone-in-Noise Detection.

Authors:  U-Cheng Leong; Douglas M Schwarz; Kenneth S Henry; Laurel H Carney
Journal:  Ear Hear       Date:  2020 Jul/Aug       Impact factor: 3.570

2.  Right-Ear Advantage for Speech-in-Noise Recognition in Patients with Nonlateralized Tinnitus and Normal Hearing Sensitivity.

Authors:  Yihsin Tai; Fatima T Husain
Journal:  J Assoc Res Otolaryngol       Date:  2017-11-27

3.  Working memory training to improve speech perception in noise across languages.

Authors:  Erin M Ingvalson; Sumitrajit Dhar; Patrick C M Wong; Hanjun Liu
Journal:  J Acoust Soc Am       Date:  2015-06       Impact factor: 1.840

4.  The effects of short-term computerized speech-in-noise training on postlingually deafened adult cochlear implant recipients.

Authors:  Erin M Ingvalson; Brienne Lee; Pamela Fiebig; Patrick C M Wong
Journal:  J Speech Lang Hear Res       Date:  2012-06-28       Impact factor: 2.297

5.  Age-Related Changes in Temporal Resolution Revisited: Electrophysiological and Behavioral Findings From Cochlear Implant Users.

Authors:  Bruna S S Mussoi; Carolyn J Brown
Journal:  Ear Hear       Date:  2019 Nov/Dec       Impact factor: 3.570

6.  Auditory and Cognitive Factors Associated with Speech-in-Noise Complaints following Mild Traumatic Brain Injury.

Authors:  Eric C Hoover; Pamela E Souza; Frederick J Gallun
Journal:  J Am Acad Audiol       Date:  2017-04       Impact factor: 1.664

Review 7.  APSO Standards: Implementing Hearing Aid Needs Assessments and Measuring Related Outcomes.

Authors:  Michelle L Arnold; Victoria A Sanchez
Journal:  Semin Hear       Date:  2022-07-26

8.  Speech Recognition in Noise for Adults With Normal Hearing: Age-Normative Performance for AzBio, BKB-SIN, and QuickSIN.

Authors:  Jourdan T Holder; Laura M Levin; René H Gifford
Journal:  Otol Neurotol       Date:  2018-12       Impact factor: 2.311

9.  The Characteristics of Adults with Severe Hearing Loss.

Authors:  Pamela Souza; Eric Hoover; Michael Blackburn; Frederick Gallun
Journal:  J Am Acad Audiol       Date:  2018-09       Impact factor: 1.664

10.  Subcortical rather than cortical sources of the frequency-following response (FFR) relate to speech-in-noise perception in normal-hearing listeners.

Authors:  Gavin M Bidelman; Sara Momtaz
Journal:  Neurosci Lett       Date:  2021-01-23       Impact factor: 3.046

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