Literature DB >> 33883425

Predicting Hearing Aid Satisfaction in Adults: A Systematic Review of Speech-in-noise Tests and Other Behavioral Measures.

Alyssa Davidson1,2, Nicole Marrone1, Bryan Wong1, Frank Musiek1.   

Abstract

OBJECTIVES: Adults with hearing loss report a wide range of hearing aid satisfaction that does not significantly correlate to degree of hearing loss. It is not clear which auditory behavioral factors do contribute to hearing aid satisfaction. While poor speech understanding in noise is known to contribute to dissatisfaction, there are many categories of this type of assessment. The purpose of this systematic review is to answer the question, "Are behavioral pre-fitting measures using speech and nonspeech materials related to hearing aid satisfaction among adults?"
DESIGN: Six electronic databases were searched to find peer-reviewed studies published before June 2020. The included studies reported on the relationship between auditory behavioral measures and hearing aid satisfaction alone or globally with other outcome domains among adults with hearing loss. Six types of behavioral prefitting measures were evaluated: speech recognition in quiet (% correct), speech recognition in noise (% correct), reception thresholds for speech-in-noise, speech-based subjective ratings, dichotic speech tests, and tests using nonspeech material. Each relevant study was independently reviewed by two reviewers. Methodological quality was evaluated in each included study using the American Speech-Language-Hearing Association's level of evidence ratings.
RESULTS: There were 1342 articles identified in the systematic review process. After duplicates were removed and specific inclusion criteria were applied, 21 studies were included. All studies included had a 0 to 4 methodological quality rating indicating weak to moderate internal validity. The tests that showed potential for clinical application due to significant correlations with satisfaction were the QuickSIN, the synthetic sentence identification, the hearing in noise test, and the acceptable noise level test. Audibility, as measured by degree of hearing loss, was not significantly correlated to hearing aid satisfaction in the 13 studies that reported on this measure.
CONCLUSIONS: Based on this review, results indicated that speech-in-noise tests had the highest associations to hearing aid satisfaction, suggesting a greater role for assessment of speech-in-noise perception in auditory rehabilitation. This is an important finding for clinical practice, given that audibility was not a significant factor in predicting satisfaction. Overall, the results from this review show a need for well-designed, high-quality, prospective studies assessing the predictive value of prefitting measures on hearing aid satisfaction with current hearing aid models.
Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.

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Year:  2021        PMID: 33883425     DOI: 10.1097/AUD.0000000000001051

Source DB:  PubMed          Journal:  Ear Hear        ISSN: 0196-0202            Impact factor:   3.570


  5 in total

1.  Factors Affecting the Use of Speech Testing in Adult Audiology.

Authors:  Bhavisha J Parmar; Saima L Rajasingam; Jennifer K Bizley; Deborah A Vickers
Journal:  Am J Audiol       Date:  2022-06-23       Impact factor: 1.636

Review 2.  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

3.  Hearing Aid Technology Settings and Speech-in-Noise Difficulties.

Authors:  Alyssa Davidson; Nicole Marrone; Pamela Souza
Journal:  Am J Audiol       Date:  2022-02-08       Impact factor: 1.636

Review 4.  Harnessing the Power of Artificial Intelligence in Otolaryngology and the Communication Sciences.

Authors:  Blake S Wilson; Debara L Tucci; David A Moses; Edward F Chang; Nancy M Young; Fan-Gang Zeng; Nicholas A Lesica; Andrés M Bur; Hannah Kavookjian; Caroline Mussatto; Joseph Penn; Sara Goodwin; Shannon Kraft; Guanghui Wang; Jonathan M Cohen; Geoffrey S Ginsburg; Geraldine Dawson; Howard W Francis
Journal:  J Assoc Res Otolaryngol       Date:  2022-04-20

5.  Profiling hearing aid users through big data explainable artificial intelligence techniques.

Authors:  Eleftheria Iliadou; Qiqi Su; Dimitrios Kikidis; Thanos Bibas; Christos Kloukinas
Journal:  Front Neurol       Date:  2022-08-26       Impact factor: 4.086

  5 in total

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