Download PDF
J Am Acad Audiol 2022; 33(07/08): 390-395
DOI: 10.1055/s-0042-1757443
Research Article

The Relationship between Speech Perception in Quiet and in Noise for Young Adults with Pure-Tone Thresholds ≤ 25 dB HL

Andrew J. Vermiglio
1   Department of Communication Sciences and Disorders, East Carolina University, Greenville, North Carolina
,
Hannah R. Osborne
1   Department of Communication Sciences and Disorders, East Carolina University, Greenville, North Carolina
,
Elizabeth Bonilla
1   Department of Communication Sciences and Disorders, East Carolina University, Greenville, North Carolina
,
Lauren Leclerc
1   Department of Communication Sciences and Disorders, East Carolina University, Greenville, North Carolina
,
Meagan Thornton
1   Department of Communication Sciences and Disorders, East Carolina University, Greenville, North Carolina
,
Xiangming Fang
2   Department of Biostatistics, East Carolina University, Greenville, North Carolina
› Author Affiliations
› Further Information
Also available at
    Permissions and Reprints

Abstract

Background The standard audiological protocol utilizes quiet measures. However, it has been noted that speech recognition in noise (SRN) testing provides information that cannot be inferred from quiet measures.

Purpose The purpose of this convergent validity study was to investigate the relationships between behavioral responses in quiet and in noise.

Research Design Bilateral pure-tone averages (BPTA) were calculated for thresholds from 500 to 6000 Hz. The Hearing in Noise Test (HINT) thresholds in quiet (HINT-Q) were also measured. SRN performances were determined using the HINT Noise Front (HINT-F) condition and the AzBio test. The HINT-F uses steady-state speech-shaped noise and the AzBio uses a 10-talker babble. All conditions were randomized.

Study Sample Fifty young, native English-speaking females with pure-tone thresholds less than or equal to 25 dB HL participated in this study. The average age of the participants was 20.5 years (standard deviation = 1.47).

Data Collection and Analysis Pearson correlation coefficients were used to quantify the relationships between all measures.

Results Statistically significant relationships were found between HINT-Q thresholds versus BPTA (0.5–6.0 kHz) (r = 0.62, p < 0.01) and between HINT-F thresholds versus AzBio (0 dB signal-to-noise ratio) scores (r = -0.41, p < 0.05). No significant relationships were found between any of the quiet versus noise measures.

Conclusion These results suggest that, for individuals with pure-tone thresholds less than or equal to 25 dB HL, SRN ability must be measured directly and not inferred from PTA or speech-in-quiet measures. It is possible, to a modest degree, to predict AzBio performances from the HINT-F thresholds, and vice versa.

Keywords

speech recognition in noise - speech perception - diagnostics

Clinical Implications

Clinicians should be aware that pure-tone thresholds and speech-in-quiet measures are not good predictors of SRN ability for individuals with pure-tone thresholds less than or equal to 25 dB HL. To some degree, HINT-Q thresholds may be inferred from BPTA, and vice versa, and HINT-F thresholds may be inferred from AzBio scores. Clinicians should also be aware of the convergent validity between SRN tests when selecting test protocols for clinical use.


Study Limitations

The results of this study may not be generalizable to older and younger participant groups or to participants with elevated pure-tone thresholds, a broader range of SRN performances, or a history of significant noise exposure.


This research was presented at the American Academy of Audiology 2020 Virtual Poster Hall.




Publication History

Received: 12 August 2020

Accepted: 16 August 2022

Article published online:
29 July 2024

© 2024. American Academy of Audiology. This article is published by Thieme.

Thieme Medical Publishers, Inc.
333 Seventh Avenue, 18th Floor, New York, NY 10001, USA

 

  • References

  • 1 Carlson KD, Herdman AO. Understanding the impact of convergent validity on research results. Organ Res Methods 2012; 15 (01) 17-32
    CrossrefGoogle Scholar
  • 2 APA. Convergent Validity. APA Dictionary of Psychology 2018 [cited 2019 September 2, 2019]; Accessed Sep 2, 2022, at: https://dictionary.apa.org/convergent-validity
    Google Scholar
  • 3 Vermiglio AJ, Bulla E, Skinner J. et al. A convergent validity study: Listening in Spatialized Noise-Sentences (LiSN-S) test and the Hearing in Noise Test (HINT). Int J Audiol 2021; 60 (01) 27-34
    CrossrefPubMedGoogle Scholar
  • 4 American Speech-Language-Hearing Association. (2005). Guidelines for manual pure-tone threshold audiometry.
  • 5 American Speech-Language-Hearing Association. (2004). Preferred practice patterns for the profession of speech-language pathology.
  • 6 Stevens G, Flaxman S, Brunskill E, Mascarenhas M, Mathers CD, Finucane M. Global Burden of Disease Hearing Loss Expert Group. Global and regional hearing impairment prevalence: an analysis of 42 studies in 29 countries. Eur J Public Health 2013; 23 (01) 146-152
    CrossrefPubMedGoogle Scholar
  • 7 Vermiglio AJ, Soli SD, Freed DJ, Fisher LM. The relationship between high-frequency pure-tone hearing loss, hearing in noise test (HINT) thresholds, and the articulation index. J Am Acad Audiol 2012; 23 (10) 779-788
    Article in Thieme ConnectPubMedGoogle Scholar
  • 8 WHO. World Report on Hearing. Geneva: World Health Organization; 2021
    Google Scholar
  • 9 Carhart R. Basic principles of speech audiometry. Acta Otolaryngol 1951; 40 (1-2): 62-71
    CrossrefPubMedGoogle Scholar
  • 10 Jerger JF, Hayes D. The cross-check principle in pediatric audiometry. Arch Otolaryngol 1976; 102 (10) 614-620
    CrossrefPubMedGoogle Scholar
  • 11 Holder JT, Levin LM, Gifford RH. Speech recognition in noise for adults with normal hearing: age-normative performance for AzBio, BKB-SIN, and QuickSIN. Otol Neurotol 2018; 39 (10) e972-e978
    CrossrefPubMedGoogle Scholar
  • 12 Spahr AJ, Dorman MF, Litvak LM. et al. Development and validation of the AzBio sentence lists. Ear Hear 2012; 33 (01) 112-117
    CrossrefPubMedGoogle Scholar
  • 13 Schafer EC, Pogue J, Milrany T. List equivalency of the AzBio sentence test in noise for listeners with normal-hearing sensitivity or cochlear implants. J Am Acad Audiol 2012; 23 (07) 501-509
    Article in Thieme ConnectPubMedGoogle Scholar
  • 14 Saunders GH, Haggard MP. The clinical assessment of obscure auditory dysfunction–1. Auditory and psychological factors. Ear Hear 1989; 10 (03) 200-208
    CrossrefPubMedGoogle Scholar
  • 15 Middelweerd MJ, Festen JM, Plomp R. Difficulties with speech intelligibility in noise in spite of a normal pure-tone audiogram. Audiology 1990; 29 (01) 1-7
    CrossrefPubMedGoogle Scholar
  • 16 Dickson ED, Simpson JF. et al. A new method of testing the hearing efficiency of aviation candidates. J Laryngol Otol 1946; 61 (03) 139-203
    CrossrefPubMedGoogle Scholar
  • 17 Fry DB. A suggestion for a new method of testing hearing in aviation candidates. J Laryngol Otol 1942; 57 (01) 11-13
    CrossrefGoogle Scholar
  • 18 Nilsson M, Soli SD, Sullivan JA. Development of the hearing in noise test for the measurement of speech reception thresholds in quiet and in noise. J Acoust Soc Am 1994; 95 (02) 1085-1099
    CrossrefPubMedGoogle Scholar
  • 19 Vermiglio AJ. The American English hearing in noise test. Int J Audiol 2008; 47 (06) 386-387
    CrossrefPubMedGoogle Scholar
  • 20 Bench J, Kowal A, Bamford J. The BKB (Bamford-Kowal-Bench) sentence lists for partially-hearing children. Br J Audiol 1979; 13 (03) 108-112
    CrossrefPubMedGoogle Scholar
  • 21 Soli SD, Wong LL. Assessment of speech intelligibility in noise with the Hearing in Noise Test. Int J Audiol 2008; 47 (06) 356-361
    CrossrefPubMedGoogle Scholar
  • 22 Vermiglio AJ, Velappan K, Heeke P. et al. The relationship between speech recognition in noise and non-speech recognition in noise test performances: Implications for central auditory processing disorders testing. J Commun Disord 2019; 77: 31-43
    CrossrefPubMedGoogle Scholar
  • 23 Keith R. SCAN-3 for Adolescents and Adults: Tests for Auditory Processing Disorders. San Antonio, TX: Pearson Education, Inc.; 2009
    Google Scholar
  • 24 Niquette P, Arcaroli J, Revit L, Parkinson A, Staller S, Skinner M, Killion M. (2003, March). Development of the BKB-SIN Test. In annual meeting of the American Auditory Society; Scottsdale, AZ:
    Google Scholar
  • 25 Killion MC, Niquette PA, Gudmundsen GI, Revit LJ, Banerjee S. Development of a quick speech-in-noise test for measuring signal-to-noise ratio loss in normal-hearing and hearing-impaired listeners. J Acoust Soc Am 2004; 116 (4 Pt 1): 2395-2405
    CrossrefPubMedGoogle Scholar
  • 26 Carhart R, Jerger JF. Preferred method for clinical determination of pure-tone thresholds. J Speech Hear Disord 1959; 24: 330-345
    CrossrefGoogle Scholar
  • 27 Liberman MC, Epstein MJ, Cleveland SS, Wang H, Maison SF. Toward a differential diagnosis of hidden hearing loss in humans. PLoS One 2016; 11 (09) e0162726
    CrossrefPubMedGoogle Scholar
  • 28 Anderson S, Skoe E, Chandrasekaran B, Kraus N. Neural timing is linked to speech perception in noise. J Neurosci 2010; 30 (14) 4922-4926
    CrossrefPubMedGoogle Scholar
  • 29 Billings CJ, McMillan GP, Penman TM, Gille SM. Predicting perception in noise using cortical auditory evoked potentials. J Assoc Res Otolaryngol 2013; 14 (06) 891-903
    CrossrefPubMedGoogle Scholar
  • 30 Wilson RH. ed. The Audiology Primer for Students and Health Care Professionals. 3rd edition. Mountain Home, TN: Department of Veterans Affairs; 2009: 86
    Google Scholar
  • 31 Vermiglio AJ, Soli SD, Fang X. An argument for self-report as a reference standard in audiology. J Am Acad Audiol 2018; 29 (03) 206-222
    Article in Thieme ConnectPubMedGoogle Scholar
  • 32 Vermiglio AJ, Fang X. The World Health Organization (WHO) hearing impairment guidelines and a speech recognition in noise (SRN) disorder. Int J Audiol 2022; 61 (10) 818-825
    CrossrefPubMedGoogle Scholar