Home Email this page Print this page Bookmark this page Decrease font size Default font size Increase font size
Noise & Health  
 CURRENT ISSUE    PAST ISSUES    AHEAD OF PRINT    SEARCH   GET E-ALERTS    
 
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Email Alert *
Add to My List *
* Registration required (free)  
 


 
   Abstract
  Introduction
  Methods
  Results
  Discussion
  Conclusion
   References
   Article Tables
 

 Article Access Statistics
    Viewed200    
    Printed6    
    Emailed0    
    PDF Downloaded9    
    Comments [Add]    

Recommend this journal

 


 
  Table of Contents    
ORIGINAL ARTICLE  
Year : 2022  |  Volume : 24  |  Issue : 114  |  Page : 166-172
Influence of Auditory Training on Acceptable Noise Level Scores in Elderly Persons with Hearing Impairment

Department of Speech and Hearing, Manipal College of Health Professionals, MAHE, Manipal, India

Click here for correspondence address and email
Date of Submission23-Nov-2020
Date of Decision23-Oct-2021
Date of Acceptance27-Oct-2021
Date of Web Publication16-Sep-2022
 
  Abstract 


Objective: To study the Influence of Auditory Training on acceptable noise level (ANL) scores in elderly persons with hearing impairment. Design: Quasi-experimental study design. Study sample: A total of 20 bilateral mild to moderately severe sensorineural hearing loss participants with “high” ANL scores were taken into the study and randomly allocated to experimental and control groups. In the time frame, the experimental group provided 12 sessions of speech in noise training with a hearing aid and the baseline measures were repeated in both groups. Results: The Acceptable noise level and Speech in Noise scores significantly improved post-training only in the experimental group. They also showed a significant difference “Client Oriented Scale of Improvement (COSI)” scale in the domain “Conversation in Noise”. Conclusions: Acceptable noise level is susceptible to training similar to that of speech in noise score. It provides hope to the individuals who are poor candidates to the hearing aids.

Keywords: Acoustic stimulation, hearing aids, hearing impairment, questionnaire, signal to noise ratio, speech perception

How to cite this article:
Nakshathri MK, Mohan KM, Greeshma. Influence of Auditory Training on Acceptable Noise Level Scores in Elderly Persons with Hearing Impairment. Noise Health 2022;24:166-72

How to cite this URL:
Nakshathri MK, Mohan KM, Greeshma. Influence of Auditory Training on Acceptable Noise Level Scores in Elderly Persons with Hearing Impairment. Noise Health [serial online] 2022 [cited 2022 Oct 4];24:166-72. Available from: https://www.noiseandhealth.org/text.asp?2022/24/114/166/356131



  Introduction Top


Hearing loss is the most common sensory deficit among the aged population. Age-related hearing loss (ARHL) is known as presbycusis[1] and is characterized by inaudibility, difficulty to discriminate and identify sounds, inability to sustain a conversation in challenging situations such as speech babble or background noise.[2] Assessment of speech perception in noise and acceptance of background noise level is crucial in such population that plays a vital role in diagnosis, rehabilitation as well as prognostic indicators. Speech in noise and acceptable noise levels are one example of that.

Speech in noise is a monoaural low redundancy speech test developed by Killion et al.[3] It identifies the individual’s neural processing abilities related to speech perception particularly in the aged population as well as hearing aid candidacy evaluation. Literature reports that individuals with reduced Speech in noise performance are considered to be poor hearing aid beneficiaries and candidates.[4],[5] Speech in noise test also assists in predicting an individual’s performance in the background noises, assessing the required signal-to-noise ratios, selection of hearing aid technology, and hearing aid programming. Speech in noise is also used in the auditory training program to improve the performance of hearing aid users.[6] Sweetow and Sabes[6] reported that training on a speech-in-babble task, the participants performed better in a Speech in Noise task compared to their pre-training, which might bring some changes in hearing aid benefits.

Speech perception is of prime importance in hearing aid acceptance, usage specifically in the background noise. Individuals with hearing impairment either have to identify the signal in the presence of background noise or withstand the maximum noise for better performance. In these aspects, Nabelek et al.[7] developed the acceptable noise level (ANL) test that intended to address the individual’s performance in the background noise and predicts the hearing aid benefit by categorizing score into three levels: low (<7 dB), mid (7–13 dB), and high (>13 dB). Individuals with “low” ANLs are likely to become successful hearing aid user, whereas an individual who has “high” ANLs are unlikely to be successful hearing aid users. People with “mid” ANLs may or may not be successful hearing aid users.[8]

ANL test differs from Speech in Noise test mainly in terms of mechanism and it is least sensitive to certain audiological and non-audiological factors such as age, gender, loudness tolerance, hearing aid experience,[7],[9] degree of hearing loss,[7],[10],[11] unaided and aided conditions,[8],[12] types of noises,[7] monaural versus binaural performance,[13] medications, attention deficits, speech presentation level,[10],[14],[15] and technologies involved in hearing aid[12],[16],[17] except music, where it was better.[18]

With regard to training, unlike Speech in Noise, ANL lacks research evidence of its influence. There exists one recent study[19] that attempted systematic desensitization training on acceptable noise levels that facilitated an individual’s ability in accepting a higher level of background noise. However, a systematic desensitization program is different from that of the formal auditory training procedure. Hence, there arises a need to study whether auditory training can influence ANL score and change its sensitivity. Further, a study in this domain can change the audiologist’s perspectives on ANL, hearing aid selection, and counseling. Finally, the research findings can be a gateway to future research.


  Methods Top


Research design

A quasi-experimental, pre- and post-test study design was used for the present study. Ethical clearance was obtained from the Institutional Ethics Committee, Kasturba Hospital of the Manipal Academy of Higher Education, Manipal with reference number IEC 203/2018. In addition, the study was registered at Clinical Trial Registration India with the following reference number: (CTRI/2018/07/015099). All the participants signed the written consent form before taking part in the study.

Participants

Participants were 17 males and three females whose age ranged from 55 to 73 years with Mean[X] =62.8, Standard deviation [SD] = 4.08 years. All the participants had bilateral symmetrical mild to moderately severe sensorineural hearing impairment and baseline ANL score >15 dBHL. These participants were fitted with hearing aids and randomly assigned to the control group that received no treatment and the experimental group that underwent listening training. The experimental (trained) group was composed of 10 participants (8 males and 2 female) with Mean age [X] =61.6, Standard deviation [SD] =4.08 years and control group (9 males and 1 female) with Mean age [X] = 62.1, Standard deviation [SD] = 4.58 years. Both the experimental and control group participants satisfied the following inclusion criteria: all were native Kannada speakers and proficient speakers of Kannada language, degree of loss not exceeding moderate category, normal middle ear functioning, no neurological, motor, and mental health anomalies or associated syndromes that may hinder understanding and realization of the proposed tasks. Also, all participants passed the Montreal Cognitive Assessment screening test with scores of above 26 indicating intact cognitive abilities. [Table 1] displays the demographic details of all the participants. The experimental group received 12 sessions of listening (Speech in Noise) training between the pre- and post-training sessions with each session lasting 45 min. The control group was tested at the time interval equivalent to the experimental group, that is, 12 days interval between baseline testing and testing 2.
Table 1 Displays the demographic details, speech identification scores, and tympanometric results of the participants

Click here to view


Procedure

The experiment took place in two phases. The first phase involved the measurement of participants’ hearing thresholds, baseline ANL, and Speech in Noise (Kannada) score, and randomizing the participants into control and experimental group; the second phase involved the auditory (listening) training and post-training ANL and Speech in Noise evaluations. All the evaluations were conducted in an acoustically treated two-room setup with the ambient noise levels maintained well within the permissible levels {ANSI Standard S3.1- (1999)}.

Phase 1

Hearing evaluation

We initially examined all the participants’ ear canals for the wax and any foreign body that can influence the test result. Later, using Madsen Austra clinical audiometer and adapting modified Hughson–Westlake procedure,[20] the participants hearing thresholds were established in the audiometric frequencies [(AC 250 Hz to 8 kHz) and (BC 250 Hz to 4 kHz)]. Subsequently, the speech recognition threshold (SRT) and speech discrimination (SDS) scores were obtained using Kannada spondee words[21] and monosyllabic word list[22] successively at 20 and 40 dBSL. Finally, the UCL level was determined. Using Grason–Stadler (GSI) Tympstar version 2, the participant’s middle ear and acoustic reflexes were obtained. Followed by participants’ speech-in-noise and ANL scores were established. [Table 1] displays participants’ speech audiometric and tympanometric results of right and left ears and [Table 2] displays the participants’ pure tone audiometric test results.
Table 2 Displays the participants’ right and left ear pure tone audiometric thresholds in terms of its mean and standard deviation

Click here to view


Speech in Noise test

To establish Speech in Noise scores, we used material “Speech in Noise sentences in Kannada” developed by Avinash et al.[23] It consisted of a total of seven sentence lists and each list has seven sentences with five keywords in each of the sentences. From the list, six sentences were presented to the participants at their most comfortable level in the presence of speech-weighted noise by varying the signal-to-nose ratio from 25 to 0 dB randomly. In response, the participants were asked to repeat as they hear the sentences. Every correct keyword repetition assigned a score of 1 and SNR was calculated using the formula: SNR Loss = 25.5 − total number of words correct (dB).

Acceptable noise level scores

The participants were made to sit in the free field setup with a 0-degree azimuth to the speaker. The procedure began by determining the MCL by varying the cold running speech from soft to loud and vice versa until they find a suitable point that is most comfortable to them. While continuing the cold running speech at the MCL, the speech weighted background noise level (BNL) was introduced and adjusted in 5 dB steps until the participant is willing to “put up with” the background noise while listening to and following the speech. Finally, BNL minus MCL determines the ANL scores.

Hearing instrument selection and fitting

All the participants were fitted with WDRC (Wide Dynamic Range Compression) hearing aids of Starkey, Oticon, Bernafon, and Signia Company starting from four channels and above. Hearing aids were programmed according to the audiogram and activated all the necessary features enhancing signal-to-noise ratios. Later, insertion gain was performed using Audioscan Verifit 2 real-ear measurement instrument with the target gain placed close to 55, 65, and 80 dB input levels. Further, the participants were subjected to a listening check, where the listeners were assessed for the comfort of listening to sounds outside laboratory settings and the quality of listening. Later, all the participants filled the Client Oriented Scale of Improvement (COSI) developed by NAL (1997). It consists of five domains such as conversation in quiet, conversation in the noise, television, telephone, and increase in social contact. The participants were instructed to rate the hearing aids experience in terms of worse, no difference, slightly better, better, and much better wearing a hearing aid. Finally, the participants were made to choose the hearing that benefitted most and was comfortable.

Participant’s allocation

Chit-pull system was used to allocate participants into the control and the experimental groups. In this procedure, a number of chits representing the experimental and the control group were first placed in a container. All the selected participants drew chit from the container and were assigned to the group represented in the chit. Further, the experimental group underwent auditory (listening) training in phase 2 whereas the control group received no remediation.

Phase 2

Auditory (listening) training

The auditory training task involved listening in speech-in-noise. All the participants received 12 sessions, 1 hour per day, within 2 weeks.

Stimuli used

We used monosyllables, general words, and sentences for training. The general words list contained the commonly used words in day-to-day life and words picked from newspaper/story books/magazines). The sentences consisted of sentences developed for the quick speech-in-noise test by Avinash et al.[23] It had a seven-sentence list. Each list had seven sentences, making a total of 49 sentences. For training, we considered sentences from lists 2 to 7.

Signal-to-noise ratio

We used SNR varying from 0 to 25 dB.

Procedure

The participants wore their hearing aid and sat in a free-field setup, a double-wall sound-treated room. Via audiometer, we streamed the signal, and a speech-weighted noise through the speaker with SNR varied from 25 to 0 dB with 5 dB step size. In initial sessions, participants received training with monosyllables, words, and sentences with favorable SNRs to equally compete, and as the training progressed, we randomized the SNRs and stimuli. The training session did not follow any performance criteria to progress to more difficult SNR. In addition to training, all the participants received a home assignment to use the hearing aid in adverse listening situations at home and work environment.

After completing the training sessions, we repeated participants’ ANL and SPIN scores and COSI questionnaires to compare baseline. Similarly, the control group also received ANL and Speech in Noise tests and COSI with equivalent time intervals in a set time frame.

Descriptively the mean and standard deviation for the ANL and Speech in Noise raw scores were calculated. Repeated measures of ANOVA were used to analyze (1) Within-subject effect (comparison between pre and post), (2) Between the subject effect (between the groups), and also to check (3) interaction effect.


  Results Top


Acceptable Noise Level Scores

[Table 3] shows the mean and standard deviation of ANL and SPIN scores in the unaided and aided conditions. Paired t-test showed no significant difference between unaided and aided ANL scores with P-value = 0.08 whereas the unaided and aided Speech in Noise scores showed a statistically significant difference with P-value < 0.05.
Table 3 Unaided and aided Acceptable Noise Level and Speech in Noise Scores (SNR loss)

Click here to view


[Table 4] presents the aided pre- and post-mean ANL scores post-intervention. To test within the subject effects on ANL scores, repeated measures of ANOVA was adopted. Mauchly’s test indicated that the assumption of sphericity was violated (P < 0.05), therefore degrees of freedom were corrected using Greenhouse–Geisser estimates of sphericity (ε = 0.001). The experimental group showed a significant difference between pre- and post-ANL scores with value F (1.0, 90.0) = 14.400, P = 0.001. Comparison between the subjects, the pre- and post-ANL scores revealed that the mean differences of ANL scores were not statistically significant (F (1, 62.500) = 2.153, P = 0.160). Overall, the change in ANL scores from pre to post is different in both experimental and control groups is significant, F (1, 122.50) =19.600, P ≤ 0.05.
Table 4 Aided pre and post-training mean ANL scores

Click here to view


Speech in Noise (Kannada) Scores

[Table 5] presents the pre- and post-evaluation Speech in Noise (Kannada) scores of the experimental group and control groups. It is observed that the post-training SNR scores improved from 14.20 ± 4.58 to 9.30 ± 2.53 in the experimental group showing an improvement of 4.9 dB. In the control group, the values changed from 14.80 ± 2.34 to 14.40 with an improvement of only 0.4 dB.
Table 5 Aided pre and post-training mean Speech in Noise (Kannada) scores (SNR loss)

Click here to view


Repeated measures of ANOVA were adapted to check the significant differences and Mauchly’s test indicated that the assumption of sphericity had been violated (P < 0.05), therefore degrees of freedom were corrected using Greenhouse–Geisser estimates of sphericity (ε = 0.000). The results show that there was a significant difference between pre- and post-speech in noise (Kannada) scores in the experimental group, F (1.0, 70.225) = 80.770, P ≤ 0.005). Between the subjects, the pre and post-scores revealed no significant differences with value (F (1, 81.225) =3.807, p=.067). Though the Speech in Noise (Kannada) scores differed from pre to post in both groups, in the experimental group the results are significant with value F (1, 50.625) = 58.227, P ≤ 0.05).

Subjective satisfactory quality rating using COSI questionnaire

[Table 6] shows the pre- and post-subjective satisfactory scores, across the domains indicating “Change” versus “No Change” were analyzed for the significance. The conversation in noise domain, in the experimental group, 80% of them reported changes and 20% no changes in performance. Similarly, in the control group, only 20% reported changes. The odds ratio with 95% confidence interval showed a significant difference with a value of 16 (1.77, 143.15). Hence, the experimental group participants are 16 times more likely to improve their ability to converse in noise than when compared to the control group. No statistically significant changes were observed in other domains of COSI.
Table 6 Pre- and post-subjective satisfactory score using COSI questionnaire

Click here to view



  Discussion Top


ANL scores with and without hearing aid

ANL is a test that predicts hearing aid candidacy. The individuals with a higher ANL score (>13 dBHL) are less likely to benefit from hearing aid.[8] We witnessed a higher ANL score (15 dBHL) by all the participants both in unaided and aided conditions, further exhibiting no significant difference in performance between the groups. The higher ANL scores are attributed to participants’ age and duration of hearing loss influencing peripheral and central auditory mechanisms. The above findings suggested all the participants are poorer candidates for hearing aids, which did not change upon getting a hearing aid.[8],[12] However, the studies differed in the participant’s age range, which showed a negative relationship. Additionally, research also evidences the uncorrelation among age, unaided, and aided scores.[8],[24] Overall, higher the ANL scores, poorer the hearing aid performance, especially in noisy situations irrespective of participant’s age and hearing aids, which calls for a different line of approach such as auditory training.[25]

Effect of auditory training (Speech in noise training) on acceptable noise level scores

Auditory training is an intervention method that facilitates the residual auditory skill to enhance the communication ability of an individual with hearing impairment.[26] Speech in Noise training is one of the training components in auditory training adapted to enhance speech perception in noise. In the current study, the experimental group received Speech in Noise training and showed a significant reduction of 6 to 7 dB in ANL score compared to the control group, despite the previous literature demonstrating no correlation between speech recognition in noise abilities on ANL.[27] The above findings suggest that listening to speech in the presence of noise at variable SNR has a positive, influence in tolerating higher background noise levels. The findings are in agreement with Gordon-Hickey and Morlas[28] who observed a significant relationship between the signal-to-noise ratio and ANL.

The possible reason for Speech in Noise training interacting with ANL can be attributed to “OPERA” hypothesis, which proposes adaptive plasticity in speech processing network: anatomical overlap in the brain networks that process an acoustic feature used in both music and speech and attention activity that engage the neural network are associated with focussed attention.[29] Though the current study observed a significant difference in ANL scores by 6–7 dB post-speech in noise training, the scores still fell short by 3 dB to meet candidacy criteria. Research reports, to observe adequate benefits from auditory training, the duration of training should be provided at least two to three times per week for 5 to 15 weeks.[30] Hence, this might be one of the possibilities of falling short in scores.

Speech in noise (Kannada)

QuickSIN is an excellent tool for demonstrating hearing aid benefits.[31] In the current study, the aided Speech in Noise (Kannada) scores were less when compared to the unaided score.[8] Nebelek et al. also observed similar findings in the group of Full-time users, Part-time users, and Non-users—the mean unaided and aided Speech in Noise (Kannada) scores were different in all the groups. The result is also in line with the literature[5],[32] where they noted Speech in Noise (Kannada) scores were significantly better in the aided condition when compared to the unaided condition.

Effect of auditory training (speech in noise training) on Speech in Noise (Kannada) scores

The auditory training yielded positive results to the experimental group by significantly improving the speech in noise score from 14.20 ± 4.58 to 9.30 ± 2.53 in comparison to the control group. Research reports, obtaining 1 dB improvement in SNR has been estimated to result in 6% to 8% improvement in speech identification scores,[33],[34] the present study witnessed 5 to 6 dB improvement in SNR loss. The findings are in consensus with the literature,[35],[36],[37],[38],[39] wherein they reported significant improvement with training in the presence of noise among older adults with hearing impairment. Similarly, Rao et al.[40] and Anderson et al.[35] also reported Speech in Noise training improved HINT and QuickSIN scores. In summary, exercising listening speech in the presence of background noise is of great benefit to individuals with hearing impairment, especially for those who complain of it.

Subjective satisfactory quality rating using COSI

COSI is a clinical tool that documents the client’s improvements in hearing ability post-hearing aid fitting.[41] In the current study, it was adapted to measure satisfactory scores pre- and post-speech in noise training with a hearing aid. Post-training the participants reported improvement in all of the domains, however only the “Conversation in Noise” showed a significant difference in performance. Hence, speech in noise training showed a good correlation with improvement in “Conversation in Noise” domain of COSI.[42]

Even though there was a significant improvement in the “Conversation in Noise” domain, it did not significantly change the “Social Contact.” Social contact varies from individual to individual, and it depends on their lifestyle, which might have influenced the result of social contact. Social contact is also influenced by individual assertiveness; hence, working on building assertiveness along with auditory closure might influence the finding.

The current study findings are also in line with a self-reported questionnaire indicating the efficacy of the training among older adults with hearing impairment.[6] A study by Gil and Iorio[36] evaluated the subjective effectiveness based on formal auditory training using APHAB with various domains including ease of communication, background noise, aversiveness of sound, and reverberation condition. The outcome uncovered that there was a pattern toward statistical significance for the experimental group in the reverberation and background noise domain, whereas there was no difference noted in the control group. Hence, they concluded that formal auditory training has a significant effect on the subjective satisfactory score.

Strength

This is the first kind of study in the clinical population and it provides evidence that ANL is susceptible to training.

Clinical implication

  1. The auditory training has an influence on ANL.
  2. Speech in noise training; a component of auditory training can change the ANL candidacy.


Limitation

  1. Not adapting cross-check principles mainly in terms of objective evaluation (electrophysiological tests).
  2. Use of only auditory closure activities for training.
  3. Follow-up evaluation to test the sustained ability of training provided.


Future directions

  1. To evaluate the effect of other standardized auditory training/ music training on ANL in elderly persons with hearing impairment.
  2. Generation of objective evidence to evaluate the relation between ANL and auditory training.



  Conclusion Top


To conclude, Speech in Noise training at favorable and unfavorable SNR showed a positive influence on ANL, Speech in Noise (Kannada), and COSI (Conversation in Noise). Though both tests differ in their mechanism, training one can influence the other. However, further research is warranted to justify the findings more objectively. Further, hearing aid fitting and a few sessions of auditory training can be of greater support for the hearing impaired population, especially the older adults.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Huang Q, Tang J. Age-related hearing loss or presbycusis. European Archives of Oto-Rhino-Laryngol 2010;267:1179-91.  Back to cited text no. 1
    
2.
Karawani H, Bitan T, Attias J, Banai K. Auditory perceptual learning in adults with and without age-related hearing loss. Front Psychol 2016;6;2066.  Back to cited text no. 2
    
3.
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. The Journal of the Acoustical Society of America 2004;116:2395-405.  Back to cited text no. 3
    
4.
Preminger JE, Carpenter R, Ziegler CH. A clinical perspective on cochlear dead regions: intelligibility of speech and subjective hearing aid benefit. Journal of the American Academy of Audiology 2005;16;600-13.  Back to cited text no. 4
    
5.
Walden TC, Walden BE. Predicting success with hearing aids in everyday living. Journal of the American Academy of Audiology 2004;15;342-52.  Back to cited text no. 5
    
6.
Sweetow RW, Sabes JH. The need for and development of an adaptive listening and communication enhancement (LACE™) program. Journal of the American Academy of Audiology 2006;17:538-58.  Back to cited text no. 6
    
7.
Nabelek AK, Tucker FM, Letowski TR. Toleration of background noises: Relationship with patterns of hearing aid use by elderly persons. Journal of Speech, Language, and Hearing Research. 1991;34:679-85.  Back to cited text no. 7
    
8.
Nabelek AK, Freyaldenhoven MC, Tampas JW, Burchfield SB, Muenchen RA. Acceptable noise level as a predictor of hearing aid use. Journal of the American Academy of Audiology 2006;17:626-39.  Back to cited text no. 8
    
9.
Crowley HJ, Nabelek IV. Estimation of client-assessed hearing aid performance based upon unaided variables. Journal of Speech, Language, and Hearing Research 1996;39:19-27.  Back to cited text no. 9
    
10.
Freyaldenhoven MC, Plyler PN, Thelin JW, Hedrick MS. The effects of speech presentation level on acceptance of noise in listeners with normal and impaired hearing. Journal of Speech, Language, and Hearing Research 2007;50:878-85.  Back to cited text no. 10
    
11.
Plyler PN, Bahng J, Von Hapsburg D. The acceptance of background noise in adult cochlear implant users. J Speech Lang Hear Res 2008; 51: 502–15.  Back to cited text no. 11
    
12.
Agarwal M, Manjula PA. Comparison across Degree of Hearing Loss, Noise Reduction in Hearing Aid and Personality Type (unpublished Master’s dissertation). Mysore: University of Mysore; 2008.  Back to cited text no. 12
    
13.
Freyaldenhoven MC, Plyler PN, Thelin JW, Burchfield SB. Acceptance of noise with monaural and binaural amplification. Journal of the American Academy of Audiology 2006;17;659-66.  Back to cited text no. 13
    
14.
Franklin CA, Thelin JW, Nabelek AK, Burchfield SB. The effect of speech presentation level on acceptance of background noise in listeners with normal hearing. Journal of the American Academy of Audiology 2006;17:141-6.  Back to cited text no. 14
    
15.
Tampas JW, Harkrider AW. Auditory evoked potentials in females with high and low acceptance of background noise when listening to speech. J Acoust Soc Am 2006;119:1548-61.  Back to cited text no. 15
    
16.
Mueller HG, Weber J, Hornsby BW. The effects of digital noise reduction on the acceptance of background noise. Trends Amplif 2006;10:83-93.  Back to cited text no. 16
    
17.
Wu YH, Stangl E. The effect of hearing aid signal-processing schemes on acceptable noise levels: perception and prediction. Ear Hear 2013;34:333-341.  Back to cited text no. 17
    
18.
Gordon-Hickey S, Moore RE. Influence of music and music preference on acceptable noise levels in listeners with normal hearing. J Am Acad Audiol 2007;18:417-27.  Back to cited text no. 18
    
19.
Pitchaimuthu A, Arora A, Bhat JS, Kanagokar V. Effect of systematic desensitization training on acceptable noise levels in adults with normal hearing sensitivity. Noise & Health 2018;20:83-9.  Back to cited text no. 19
    
20.
Carhart R, Jerger JF. Preferred method for clinical determination of pure-tone thresholds. J Speech Hear Disord 1959;24:330-45.  Back to cited text no. 20
    
21.
Rajashekar B. The development and standardization of a picture SRT for adults and children in Kannada. Journal of All India Institute of Speech and Hearing. 1978;9:26-26.  Back to cited text no. 21
    
22.
Mayadevi N. The development and standardization of a common speech discrimination test for Indians (unpublished master’s dissertation). Mysore: University of Mysore; 1974.  Back to cited text no. 22
    
23.
Avinash MC, Meti R, Kumar U. Development of sentences for quick speech-in-noise (QuickSIN) test in Kannada. J Indian Speech Hear Assoc 2010;24:59-65.  Back to cited text no. 23
    
24.
Crowley HJ. Unaided factors predicting client-assessed hearing aid performance, usage and satisfaction. (Doctoral dissertation). USA: The University of Tennessee; 1994.  Back to cited text no. 24
    
25.
Plyler PN. 20Q: Acceptable Noise Level Test − Supporting Research and Clinical Insights. 2015. Available from: https://www.audiologyonline.com/articles/20q-acceptable-noise-test-research-14692 [Accessed on 2015, July].  Back to cited text no. 25
    
26.
Boothroyd A. Adult aural rehabilitation: what is it and does it work?. Trends in Amplif 2007;11:63-71.  Back to cited text no. 26
    
27.
Valame DA, Thakkar M, Mehta N, Patel S. Monotic and dichotic acceptable noise levels in typically developing children and adolescents. Journal of Indian Speech Lang uage & Hearing Association 2017;31:72.  Back to cited text no. 27
    
28.
Gordon-Hickey S, Morlas H. Speech recognition at the acceptable noise level. J Am Acad Audiol 2015;26:443-50.  Back to cited text no. 28
    
29.
Patel AD. Why would musical training benefit the neural encoding of speech? The OPERA hypothesis. Front Psychol 2011;2:142.  Back to cited text no. 29
    
30.
Humes LE, Kinney DL, Brown SE, Kiener AL, Quigley TM. The effects of dosage and duration of auditory training for older adults with hearing impairment. Journal of the Acoustical Society of America 2014;136:EL224-EL230.  Back to cited text no. 30
    
31.
Taylor B. Speech-in-noise tests: how and why to include them in your basic test battery. The Hearing Journal 2003;56:40-42.  Back to cited text no. 31
    
32.
Mendel LL. Objective and subjective hearing aid assessment outcomes. American Journal of Audiology 2007;16:118-29.  Back to cited text no. 32
    
33.
Crandell CC. Individual differences in speech recognition ability: Implications for hearing aid selection. Ear and Hearing 1991;12(6 Suppl):100S-108S.  Back to cited text no. 33
    
34.
McArdle RA, Wilson RH, Burks CA. Speech recognition in multitalker babble using digits, words, and sentences. J Am Acad Audiol 2005;16:726-39.  Back to cited text no. 34
    
35.
Anderson S, White-Schwoch T, Choi HJ, Kraus N. Training changes processing of speech cues in older adults with hearing loss. Front Psychol 2013;7:97.  Back to cited text no. 35
    
36.
Gil D, Iorio MCM. Formal auditory training in adult hearing aid users. Clinics 2010;65:165-74.  Back to cited text no. 36
    
37.
Olson AD, Preminger JE, Shinn JB. The effect of LACE DVD training in new and experienced hearing aid users. J Am Acad Audiol 2013;24:214-30.  Back to cited text no. 37
    
38.
Stecker GC, Bowman GA, Yund EW, Herron TJ, Roup CM, Woods DL. Perceptual training improves syllable identification in new and experienced hearing aid users. Journal of Rehabilitation Research & Development 2006;43:537-52.  Back to cited text no. 38
    
39.
Sweetow RW, Sabes JH. Listening and communication enhancement (LACE). In Seminars in Hearing. Vol. 28, No. 02. New York, NY: Thieme Medical Publishers; 2007: p. 133-141.  Back to cited text no. 39
    
40.
Rao A, Rishiq D, Yu L, Zhang Y, Abrams H. Neural correlates of selective attention with hearing aid use followed by ReadMyQuips auditory training program. Ear Hear 2017;38:28-41.  Back to cited text no. 40
    
41.
Dillon H, James A, Ginis J. Client Oriented Scale of Improvement (COSI) and its relationship to several other measures of benefit and satisfaction provided by hearing aids. Journal- American Academy of Audiology 1997;8:27-43.  Back to cited text no. 41
    
42.
Yang JY, Zhang H, Chen J et al. The application of mandarin acceptable noise level and COS in hearing aid fitting for presbyacusis. J Clin Otorhinolaryngol Head Neck Surg 2016;30:1850-3.  Back to cited text no. 42
    

Top
Correspondence Address:
Greeshma R
Ayyanath (H), Palliyara, Trikkur (P. O.), Thrissur 680306
India
Kishan M Mohan
Department of Speech and Hearing, Manipal College of Health Professionals, MAHE, Manipal 576104
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/nah.nah_5_22

Rights and Permissions



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]



 

Top