Starkey Research & Clinical Blog

A Pediatric Prescription for Listening in Noise

Crukley, J. & Scollie, S. (2012). Children’s speech recognition and loudness perception with the Desired Sensation Level v5 Quite and Noise prescriptions. American Journal of Audiology 21, 149-162.

This editorial discusses the clinical implications of an independent research study and does not represent the opinions of the original authors.

Most hearing aid prescription formulas attempt to balance audibility of sound with perception of loudness, while keeping the amplified sound within a patient’s dynamic range (Dillon, 2001; Gagne et al., 1991a; Gagne et al., 1991b; Seewald et al., 1985). Use of a prescriptively appropriate hearing aid fitting is particularly important for children with hearing loss. For the needs of language development, they benefit from a higher proportion of audible sound and broader bandwidth than diagnostically similar older children and adults (Pittman & Stelmachowicz, 2000; Stelmachowicz et al., 2000; Stelmachowicz et al., 2001; Stelmachowicz et al., 2004; Stelmachowicz et al., 2007).

Historically, provision of access to speech in quiet has been a primary driver in the development of prescription formulas for hearing aid.  However, difficulty understanding speech in noise is one of the primary complaints of all hearing aid users, including children. In a series of studies compared NAL-NL1 and DSL v4.1 fittings and examined children’s listening needs and preferences (Ching et al., 2010; Ching et al., 2010; Scollie et al., 2010) two distinct listening categories were identified: loud, noisy and reverberant environments and quiet or low-level listening situations. The investigators found that children preferred the DSL fitting in quiet conditions but preferred the NAL fitting for louder sounds and when listening in noisy environments. Examination of the electroacoustic differences between the two fittings showed that the DSL fittings provided more gain overall and approximately 10dB more low-frequency gain than the NAL-NL1 fittings.

To address the concerns of listening in noisy and reverberant conditions, DSL v5 includes separate prescriptions for quiet and noise. Relative to the formula for quiet conditions, the noise formula prescribes higher compression thresholds, lower overall gain, lower low-frequency gain and more relative gain in the high frequencies.  This study of Crukley and Scollie addressed whether the use of the DSL v5 Quiet and Noise formulae resulted in differences in consonant recognition in quiet, sentence recognition in noise and different loudness ratings.  Because of the lower gain in the noise formula, it was expected to reduce loudness ratings and consonant recognition scores in quiet because of potentially reduced audibility. There was no expected difference for speech recognition in noise, as the noise floor was considered the primary limitation to audibility in noisy conditions.

Eleven children participated in the study; five elementary school children with an average age of 8.85 years and six high school children with an average age of 15.18 years. All subjects were experienced, full-time hearing aid users with congenital, sensorineural hearing losses, ranging from moderate to profound.  All participants were fitted with behind-the-ear hearing aids programmed with two separate programs: one for DSL Quiet targets and one for DSL Noise targets. The Noise targets had, on average, 10dB lower low-frequency gain and 5dB lower high-frequency gain, relative to the Quiet targets. Testing took place in two classrooms: one at the elementary school and one at the high school.

Consonant recognition in quiet conditions was tested with the University of Western Ontario Distinctive Features Differences Test (UWO-DFD; Cheesman & Jamieson, 1996). Stimuli were presented at 50dB and 70dB SPL, by a male talker and a female talker. Sentence recognition in noise was performed with the Bamford-Kowal-Bench Speech in Noise Test (BKB-SIN; Niquette et al., 2003). BKB-SIN results are scored as the SNR at which 50% performance can be achieved (SNR-50).

Loudness testing was conducted with the Contour Test of Loudness Perception (Cox et al., 1997; Cox & Gray, 2001), using BKB sentences presented in ascending then descending steps of 4dB from 52dB to 80dB SPL. Subjects rated their perceived loudness on an 8-point scale ranging from “didn’t hear it” up to “uncomfortably loud” and indicated their response on a computer screen. Small children were assisted by a researcher, using a piece of paper with the loudness ratings, and then the researcher entered the response.

The hypotheses outlined above were generally supported by the results of the study. Consonant recognition scores in quiet were better at 70dB than 50dB for both prescriptions and there was no significant difference between the Quiet and Noise fittings. There was, however, a significant interaction between prescription and presentation level, showing that performance for the Quiet fittings was consistent at the two levels but was lower at 50dB than 70dB for the Noise fittings. The change in score from Quiet to Noise at 50dB was 4.2% on average, indicating that reduced audibility in the Noise fitting may have adversely affected scores at the lower presentation level. On the sentence recognition in noise test, BKB-SIN scores did not differ significantly between the Quiet and Noise prescriptions, with some subjects scoring better in the Quiet program, some scoring better in the Noise program and most not demonstrating any significant difference between the two. Loudness ratings were lower on average for the Noise prescription. When ratings for 52-68dB SPL and 72-80dB SPL were analyzed separately, there was no difference between the Quiet and Noise prescriptions for the lower levels but at 72dB and above, the Noise prescription yielded significantly lower loudness ratings.

Although the average consonant recognition scores for the Noise prescription were only slightly lower than those for the Quiet prescription, it may not be advisable to use the Noise prescription as the primary program for regular daily use, because of the risk of reduced audibility. This is especially true for pediatric hearing aid patients, for whom maximal audibility is essential for speech and language development. Rather, the Noise prescription is better used as an alternate program, to be accessed manually by the patient, teacher or caregiver, or via automatic classification algorithms within the hearing aid. Though the Noise prescription did not improve speech recognition in noise, it did not result in a decrement in performance and yielded lower loudness ratings, suggesting that in real world situations it would improve comfort in noise while still maintaining adequate speech intelligibility.

Many audiologists find that patients prefer a primary program set to a prescriptive formula (DSL v5, NAL-NL2 or proprietary targets) for daily use but appreciate a separate, manually accessible noise program with reduced low-frequency gain and increased noise reduction. This is true even for the majority of patients who have automatically switching primary programs, with built-in noise modes. Anecdotal remarks from adult patients using manually accessible noise programs agree with the findings of the present study, in that most people use them for comfort in noisy conditions and find that they are still able to enjoy conversation.

For the pediatric patient, prescription of environment specific memories should be done on a case-by-case basis. Patients functioning as teenagers might be capable of managing manual selection of a noise program in appropriate conditions. Those of a functionally younger age will require assistance from a supervising adult. Personalized, written instructions will assist adult caregivers to ensure that they understand which listening conditions may be uncomfortable and what actions should be taken to adjust the hearing aids. Most modern hearing aids feature some form of automatic environmental classification: ambient noise level estimation being one of the more robust classifications. Automatic classification and switching may be sufficient to address concerns of discomfort. However, the details of this behavior vary greatly among hearing aids. It is essential that the prescribing audiologist is aware of any automatic switching behavior and works to verify each of the accessible hearing aid memories.

Crukley and Scollie’s study supports the use of separate programs for everyday use and noisy conditions and indicates that children could benefit from this approach. The DSL Quiet and Noise prescriptive targets offer a consistent and verifiable method for this approach with children, while also providing potential guidelines for designing alternate noise programs for use by adults with hearing aids.

 

References

Cheesman, M. & Jamieson, D. (1996). Development, evaluation and scoring of a nonsense word test suitable for use with speakers of Canadian English. Canadian Acoustics 24, 3-11.

Ching, T., Scollie, S., Dillon, H. & Seewald, R. (2010). A crossover, double-blind comparison of the NAL-NL1 and the DSL v4.1 prescriptions for children with mild to moderately severe hearing loss. International Journal of Audiology 49 (Suppl. 1), S4-S15.

Ching, T., Scollie, S., Dillon, H., Seewald, R., Britton, L. & Steinberg, J. (2010). Prescribed real-ear and achieved real life differences in children’s hearing aids adjusted according to the NAL-NL1 and the DSL v4.1 prescriptions. International Journal of Audiology 49 (Suppl. 1), S16-25.

Cox, R., Alexander, G., Taylor, I. & Gray, G. (1997). The contour test of loudness perception. Ear and Hearing 18, 388-400.

Cox, R. & Gray, G. (2001). Verifying loudness perception after hearing aid fitting. American Journal of Audiology 10, 91-98.

Crandell, C. & Smaldino, J. (2000). Classroom acoustics for children with normal hearing and hearing impairment. Language, Speech and Hearing Services in Schools 31, 362-370.

Crukley, J. & Scollie, S. (2012). Children’s speech recognition and loudness perception with the Desired Sensation Level v5 Quite and Noise prescriptions. American Journal of Audiology 21, 149-162.

Dillon, H. (2001). Prescribing hearing aid performance. Hearing Aids (pp. 234-278). New York, NY: Thieme.

Jenstad, L., Seewald, R., Cornelisse, L. & Shantz, J. (1999). Comparison of linear gain and wide dynamic range compression hearing aid circuits: Aided speech perception measures. Ear and Hearing 20, 117-126.

Niquette, P., Arcaroli, J., Revit, L., Parkinson, A., Staller, S., Skinner, M. & Killion, M. (2003). Development of the BKB-SIN test. Paper presented at the annual meeting of the American Auditory Society, Scottsdale, AZ.

Pittman, A. & Stelmachowicz, P. (2000). Perception of voiceless fricatives by normal hearing and hearing-impaired children and adults. Journal of Speech, Language and Hearing Research 43, 1389-1401.

Scollie, S. (2008). Children’s speech recognition scores: The speech intelligibility index and proficiency factors for age and hearing level. Ear and Hearing 29, 543-556.

Scollie, S., Ching, T., Seewald, R., Dillon, H., Britton, L., Steinberg, J. & Corcoran, J. (2010). Evaluation of the NAL-NL1 and DSL v4.1 prescriptions for children: Preference in real world use. International Journal of Audiology 49 (Suppl. 1), S49-S63.

Scollie, S., Ching, T., Seewald, R., Dillon, H., Britton, L., Steinberg, J. & King, K. (2010). Children’s speech perception and loudness ratings when fitted with hearing aids using the DSL v4.1 and NAL-NL1 prescriptions. International Journal of Audiology 49 (Suppl. 1), S26-S34.

Seewald, R., Ross, M. & Spiro, M. (1985). Selecting amplification characteristics for young hearing-impaired children. Ear and Hearing 6, 48-53.

Stelmachowicz, P., Hoover, B., Lewis, D., Kortekaas, R. & Pittman, A. (2000). The relation between stimulus context, speech audibility and perception for normal hearing and hearing impaired children. Journal of Speech, Language and Hearing Research 43, 902-914.

Stelmachowicz, P., Pittman, A., Hoover, B. & Lewis, D. (2001). Effect of stimulus bandwidth on the perception of /s/ in normal and hearing impaired children and adults. The Journal of the Acoustical Society of America 110, 2183-2190.

Stelmachowicz, P. Pittman, A., Hoover, B. & Lewis, D. (2004). Novel word learning in children with normal hearing and hearing loss. Ear and Hearing 25, 47-56.

Stelmachowicz, P. Pittman, A., Hoover, B., Lewis, D. & Moeller, M. (2004). The importance of high-frequency audibility in the speech and language development of children with hearing loss. Archives of Otolaryngology, Head and Neck Surgery 130, 556-562.

Stelmachowicz, P., Lewis, D., Choi, S. & Hoover, B. (2007).  Effect of stimulus bandwidth on auditory skills in normal hearing and hearing impaired children.  Ear and Hearing 28, 483-494.

Can Aided Audibility Predict Pediatric Lexical Development?

Stiles, D.J., Bentler, R.A., & McGregor, K.K. (2012). The speech intelligibility index and the pure-tone average as predictors of lexical ability in children fit with hearing aids. Journal of Speech Language and Hearing Research, 55, 764-778.

This editorial discusses the clinical implications of an independent research study and does not represent the opinions of the original authors.

Despite advances in early hearing loss identification, hearing aid technology, and fitting and verification tools, children with hearing loss consistently demonstrate limited lexical abilities compared to children with normal hearing.  These limitations have been illustrated by poorer performance on tests of vocabulary (Davis et al., 1986), word learning (Gilbertson & Kamhi, 1995; Stelmachowicz et al., 2004), phonological discrimination, and non-word repetition (Briscoe et al., 2001; Delage & Tuller, 2007; Norbury, et al., 2001).

There are a number of variables that may predict hearing-impaired children’s performance on speech and language tasks, including the age at which they were first fitted with hearing aids and the degree of hearing loss.  Moeller (2000) found that children who received earlier aural rehabilitation intervention demonstrated significantly larger receptive vocabularies than those who received later intervention.  Degree of hearing loss, which is typically defined in studies by the pure-tone average (PTA) or the average of pure-tone hearing thresholds at 500Hz, 1000Hz, and 2000Hz (Fletcher, 1929), has been significantly correlated with speech recognition (Davis et al., 1986; Gilbertson & Kamhi, 1995), receptive vocabulary (Fitzpatrick et al., 2007; Wake et al., 2005), expressive grammar, and word recognition (Delage & Tuller, 2007) in some studies comparing hearing-impaired children to those with normal hearing.

In contrast, other studies have reported that pure-tone average (PTA) did not predict language ability in hearing-impaired children.  Davis et al. (1986) tested hearing-impaired subjects between five and18 years of age and found no significant relationship between PTA and vocabulary, verbal ability, reasoning, and reading.  However, all subjects scored below average on these measures, regardless of their degree of hearing loss.  Similarly, Moeller (2000) found that age of intervention affected vocabulary and verbal reasoning, but PTA did not.  Gilbertson and Kamhi (1995) studied novel word learning in hearing-impaired children ranging in age from  seven to 10 years and found that neither PTA nor unaided speech recognition threshold was correlated to receptive vocabulary level or word learning.

At a glance, it seems likely that degree of hearing loss should affect language development and ability, because hearing loss affects audibility, and speech must be audible in order to be processed and learned.  However, the typical PTA of thresholds at 500Hz, 1000Hz, and 2000Hz does not take into account high-frequency speech information beyond 2000Hz.  Some studies using averages of high-frequency pure-tone thresholds (HFPTA) have found a significant relationship between degree of loss and speech recognition (Amos & Humes, 2007; Glista et al., 2009).

Because most hearing-impaired children now benefit from early identification and intervention, their pure-tone hearing threshold averages (PTA or HFTPA) might not be the best predictors of speech and language abilities in every-day situations.  Rather, a measure that combines degree of hearing loss as well as hearing aid characteristics might be a better predictor of speech and language ability in hearing-impaired children.  The Speech Intelligibility Index (SII; ANSI,2007), a measure of audibility that computes  the importance of different frequency regions based on the phonemic content of a given speech test, has proven to be predictive of performance on speech perception tasks for adults and children (Dubno et al., 1989; Pavlovic et al., 1986; Stelmachowicz et al., 2000).  Hearing aid gain characteristics can be incorporated into the SII algorithm to yield an aided SII, which has been reported to predict performance on word repetition (Magnusson et al., 2001) and nonsense syllable repetition ability in adults (Souza & Turner, 1999).  Because an aided SII includes the individual’s hearing loss and hearing aid characteristics into the calculations, it better represents how audibility affects an individual’s daily functioning.

The purpose of the current study was to evaluate the aided SII as a predictor of performance on measures of word recognition, phonological working memory, receptive vocabulary, and word learning.  Because development in these areas establishes a base for later achievements in language learning and reading (Tomasello, 2000; Stanovich, 1986), it is important to determine how audibility affects lexical development in hearing-impaired children.  Though the SII is usually calculated based on the particular speech test to be studied, the current investigation used aided SII values based on average speech spectra.  The authors explained that vocabulary acquisition is a cumulative process, and they intended to use the aided SII as a measure of cumulative, rather than test-specific, audibility.

Sixteen hearing-impaired children with hearing aids (CHA) and 24 children with normal hearing (CNH) between six and nine years of age participated in the study.  All of the hearing-impaired children had bilateral hearing loss and had used amplification for at least one year.  All participants used spoken language as their primary form of communication.  Real-ear measurements were used to calculate the aided SII at user settings.  Because the goal was to evaluate the children’s actual audibility as opposed to optimal audibility, their current user settings were used in the experiment whether or not they met DSL prescriptive targets (Scollie et al., 2005).

Subjects participated in tasks designed to assess four lexical domains.  Word recognition was measured by the Lexical Neighborhood Test and Multisyllabic Lexical Neighborhood Test (LNT and MLNT; Kirk & Pisoni, 2000).  These tests each contain “easy” and “hard” lists, based on how frequently the words occur in English and how many lexical neighbors they have.  Children with normal lexical development are expected to show a gradient in performance with the best scores on the easy MLNT and poorest scores on the hard LNT.  Non-word repetition was measured by a task prepared specifically for this study, using non-words selected based on adult ratings of “wordlikeness”.  In the word recognition and non-word repetition tasks, children were simply asked to repeat the words that they heard.  Responses were scored according to the number of phonemes correct for both tasks.  Additionally, the LNT and MLNT tests were scored based on number of words correct.  Receptive vocabulary was measured by the Peabody Picture Vocabulary Test (PPVT-III; Dunn & Dunn, 1997) in which the children were asked to view four images and select the one that corresponds to the presented word.  Raw scores are determined as the number of items correctly identified and norms are applied based on the subject’s age.  Novel word learning was assessed using the same stimuli from the non-word repetition task, after the children were given sentence context and visual imagery to teach them the “meaning” of the novel words.  Their ability to learn the novel words was evaluated in two ways: a production task in which they were asked to say the word when prompted by a corresponding picture and an identification task in which they were presented with an array of four items and were asked to select the item that corresponded to the word that was presented.

On the word recognition tests, the children with hearing aids (CHA) demonstrated poorer performance than the children with normal hearing (CNH) for measures of word and phoneme accuracy, though both groups demonstrated the expected gradient, with performance improving in parallel fashion from the hard LNT test through the easy MLNT test.  There was a correlation between aided SII and word recognition scores, but PTA and aided SII were equally good at predicting performance.

On the non-word repetition task, which requires auditory perception, phonological analysis, and phonological storage (Gathercole, 2006), CHA again demonstrated significantly poorer performance than CNH, and CNH performance was near ceiling levels.  PTA and aided SII scores were correlated with non-word repetition scores.  Beyond the effect of PTA, it was determined that aided SII accounted for 20% of the variance on the non-word repetition task, which was statistically significant.

The receptive vocabulary test yielded similar results; CHA performed significantly worse than CNH and both PTA and aided SII accounted for a significant proportion of the variance.

The only variable that predicted performance on the word learning tasks was age, which only yielded a significant effect on the word production task.  On the word identification task, both the CHA and CNH groups scored only slightly better than chance and there were no significant effects of group or age.

As was expected in this study, children with hearing aids (CHA) consistently showed poorer performance than children with normal hearing (CNH), with the exception of the novel word learning task.  The pattern of results suggests that aided audibility, as measured by the aided SII, was better at predicting performance than degree of hearing loss as measured by PTA.  Greater aided SII scores were consistently associated with more accurate word recognition, more accurate non-word repetition, and larger receptive vocabulary.

Although PTA or HFPTA may represent the degree of unaided hearing loss, because the aided SII score accounts for the contribution of the individual’s hearing aids, it is likely a better representation of speech audibility and auditory perception in everyday situations.  The authors point out that depending on the audiometric configuration and hearing aid characteristics, two individuals with the same PTA could have different aided SIIs, and therefore different auditory experiences.

The results of this study underscore the importance of audibility for lexical development, which in turn has significant implications for further development of language, reading, and academic skills.  Therefore, the early provision of audibility via appropriate and verifiable amplification appears to be an important step in the development of speech and language.  The SII, which is already incorporated into some real-ear systems or is available in a standalone software package, is a verification tool that should be considered a standard part of the fitting protocol for pediatric hearing aid patients.

 

References

American National Standards Institute (2007). Methods for calculation of the Speech Intelligibility index (ANSI S3.5-1997[R2007]). New York, NY: Author.

Amos, N.E. & Humes, L.E. (2007). Contribution of high frequencies to speech recognition in quiet and noise in listeners with varying degrees of high-frequency sensorineural hearing loss. Journal of Speech, Language and Hearing Research 50, 819-834.

Briscoe, J., Bishop, D.V. & Norbury, C.F. (2001). Phonological processing, language and literacy: a comparison of children with mild-to-moderate sensorineural hearing loss and those with specific language impairment. Journal of Child Psychology and Psychiatry 42, 329-340.

Davis, J.M., Elfenbein, J., Schum, R. & Bentler, R.A. (1986). Effects of mild and moderate hearing impairments on language, educational and psychosocial behavior of children. Journal of Speech and Hearing Disorders 51, 53-62.

Delage, H. & Tuller, L. (2007). Language development and mild-to-moderate hearing loss: Does language normalize with age? Journal of Speech, Language and Hearing Research 50, 1300-1313.

Dubno, J.R., Dirks, D.D. & Schaefer, A.B. (1989). Stop-consonant recognition for normal hearing listeners and listeners with high-frequency hearing loss. II: Articulation index predictions. The Journal of the Acoustical Society of America 85, 355-364.

Dunn, L.M. & Dunn, D.M. (1997). Peabody Picture Vocabulary Test – III. Circle Pines, MN: AGS.

Fitzpatrick, E., Durieux-Smith, A., Eriks-Brophy, A., Olds., J. & Gaines, R. (2007). The impact of newborn hearing screening on communications development. Journal of Medical Screening 14, 123-131.

Fletcher, H. (1929). Speech and hearing in communication. Princeton, NJ: Van Nostrand Reinhold.

Gilbertson, M. & Kamhi, A.G. (1995). Novel word learning in children with hearing impairment. Journal of Speech and Hearing Research 38, 630-642.

Glista, D., Scollie, S., Bagatto, M., Seewald, R., Parsa, V. & Johnson, A. (2009). Evaluation of nonlinear frequency compression: Clinical outcomes. International Journal of Audiology 48, 632-644.

Kirk, K.I. & Pisoni, D.B. (2000). Lexical Neighborhood Tests. St. Louis, MO:AudiTEC.

Magnusson, L., Karlsson, M. & Leijon, A. (2001). Predicted and measured speech recognition performance in noise with linear amplification. Ear and Hearing 22, 46-57.

Moeller, M.P. (2000). Early intervention and language development in children who are deaf and hard of hearing. Pediatrics 106, e43.

Norbury, C.F., Bishop, D.V. & Briscoe, J. (2001). Production of English finite verb morphology: A comparison of SLI and mild-moderate hearing impairment. Journal of Speech, Language and Hearing Research 44, 165-178.

Pavlovic, C.V., Studebaker, G.A. & Sherbecoe, R.L. (1986). An articulation index based procedure for predicting the speech recognition performance of hearing-impaired individuals. The Journal of the Acoustical Society of America 80, 50-57.

Scollie, S.D., Seewald, R., Cornelisse, L., Moodie, S., Bagatto, M., Laurnagary, D. & Pumford, J. (2005). The desired sensation level multistage input/output algorithm. Trends in Amplification 9(4), 159-197.

Souza, P.E. & Turner, C.W. (1999). Quantifying the contribution of audibility to recognition of compression-amplified speech. Ear and Hearing 20, 12-20.

Stanovich, K.E. (1986). Matthew effects in reading: Some consequences of individual differences in the acquisition of literacy. Reading Research Quarterly 21, 360-407.

Stelmachowicz, P.G., Hoover, B.M., Lewis, D.E., Kortekaas, R.W. & Pittman, A.L. (2000). The relation between stimulus context, speech audibility and perception for normal hearing and hearing-impaired children. Journal of Speech, Language and Hearing Research 43, 902-914.

Stelmachowicz, P.G., Pittman, A.L., Hoover, B.M. & Lewis, D.E. (2004 ). Novel word learning in children with normal hearing and hearing loss. Ear and Hearing 25, 47-56.

Tomasello, M. (2000). The item-based nature of children’s early syntactic development. Trends in Cognitive Sciences 4, 156-163.

Wake, M., Poulakis, Z., Hughes, E.K., Carey-Sargeant, C. & Rickards, F.W. (2005). Hearing impairment: A population study of age at diagnosis, severity and language outcomes at 7-8 years. Archives of Disease in Childhood 90, 238-244.