Changing Knowledge, Principles, and Technology in Contemporary Clinical Audiological Practice: A Narrative Review
Abstract
:1. Introduction
2. Review
2.1. Assessment
- What does the person consciously detect or recognise?
- What is neurologically detected regardless of conscious cognitive input?
- What impact does the physical pathway of sound from the ear canal to the site of conversion into a neurological signal have on the sound that is detected?
2.2. Fitting and Programming of Devices
2.2.1. Hearing Aids
Audio Stages Implicated | Current Scientific Insights | Clinical Implications | Teleaudiology Applications |
---|---|---|---|
Sensory Neural Auditory Processing | Despite IHCs providing the primary source of signalling to the neurons, significant loss of IHCs does not cause a shift in the detectable threshold of tone-specific hearing. Loss of OHCs, however, need not be significant to lead to a detectable shift in thresholds [40]. | The threshold of hearing is not reflective of the diffractive effect on hearing performance in increasingly challenging environments, such as those with loud or competing noise. | Comparing test stimuli to provide a comprehensive portrayal of auditory factors could support gauging where the optimal benefit with fitting should be for individuals. |
Sensory Neural | Noise-induced damage primarily builds up at the synapse connecting the hair cell to the nerves [41]. Age-related loss is considered to have a cumulative effect on the integrity and function of synapses and their respective nerves across the auditory pathway over time. Short-term noise damage to a hair cell can be repaired at the cost of a long-term impact on the health of the associated synapse and nerves [40,42]. | Prompt testing and tracking of threshold shifts and recoveries are key in triaging the need for further medical intervention, and they provide a comprehensive time-sensitive profile of auditory health status over one’s lifespan. | Prompt data capture and responsiveness to acute/short-term changes in hearing can be provided. Teleaudiology-based capture can support the triggering of medical and clinical processes in local services. |
Current Scientific Insights | Clinical Implications | Teleaudiology Applications |
---|---|---|
A single nerve cell collates the signals derived from multiple IHCs and OHCs before triggering a larger joint signal, which then travels up the nerve cells towards the next junction in the pathway. The characteristics of the combined signal are shaped by the contributing signals from the OHCs and IHCs, among other factors [59]. The implication of varying proportions of IHCs and OHCs before triggering a collective signal provides variety in the characteristics of any nerve signal, e.g., portraying intensity and frequency. Therefore, ‘minor’ auditory damage to the function of IHCs and OHCs that does not produce clinically measurable threshold changes may still be detected within the auditory system. | Tinnitus is an internally generated effect that is traditionally difficult to capture with objective measures. Current objective testing methods can, however, capture evidence of the related effects on speech recognition performance, i.e., above-average performance in quiet and below-average performance in noise, in the absence of changes in thresholds. Together, these data can indicate the presence of the compensatory amplification mechanisms that underlie issues such as tinnitus [17,60]. | Subjective measurements, i.e., patient-reported experience/outcome measures (PREMs/PROMs), such as ecological momentary assessments (EMAs), can be captured via hearing-aid-supporting apps [18]. Teleaudiology-enabled EMAs can help complement clinically derived objective data [31] and, in turn, help support clinical decision-making for rehabilitation planning and monitoring. |
Detection of changes in signalling patterns can lead to compensatory post-cochlea amplification mechanisms that may initially be helpful in improving discrimination, for example, of speech in low-level noise, but the same mechanisms can become excessive and burdensome in other situations [61,62]. For example, compensation may lead to the amplification of natural spontaneous cellular/neural activity or the excessive amplification of sounds that can make the perception of loudness distorted. The signalling pathway from the cochlea to the top of the neurological communication tree, i.e., the auditory cortex, contains multiple points where signalling can be triggered to travel back down the pathway (top-down processing) to modify the signalling activity through a positive or negative feedback mechanism. This feedback signalling mechanism can be referred to as ‘top-down processing’, i.e., feedback to OHCs to further amplify or dampen their mechanical activity in response to a soundwave being detected. The effects of aging can impact the efficacy and integrity of neurological signalling, including in feedback pathways, creating an immense variety of characteristic changes in an individual’s hearing loss. | Testing methods using competing sound (noise) can reveal differing auditory performance according to whether the test method relies on cognitively dependent speech content and the intensity (volume) of testing, i.e., near the threshold vs. comfortable audibility. The implication of the type of test being used is that the day-to-day difficulties that a person experiences may not be well represented in a clinical context depending on the chosen assessment strategy. Models of how loudness is identified and processed by the auditory system would benefit from incorporating new insights related to the type and nature of damage in the auditory system and the varying impacts at different loudness levels [63]. | The growing array of testing methods that are available for clinical use with or without teleaudiology compatibility is increasing the potential volume of data to be collected, analysed, and used to inform clinical decision-making. Machine learning can aid in pattern recognition for the identification of predictive trends and key factors [42]. Deep neural networks can aid in building detailed maps for the increasingly complex and interconnected auditory system [26]. The continual addition of data and revision of parameters from research insights could lead to the identification of more effective ways to personalise audiological practices. The automation of data collection, teleaudiology-enabled improvements to clinical processes and workload planning, and teleaudiology-supported behavioural engagement with people wearing hearing aids can all contribute towards improving the success of audiological practices. |
2.2.2. Cochlear Implants
2.3. Rehabilitation
3. Limitations
4. Future Directions
Author Contributions
Funding
Conflicts of Interest
References
- Jerger, J. Ten Highlights from the History of Audiology. 2019. Available online: https://hearingreview.com/practice-building/practice-management/continuing-education/ten-highlights-history-audiology (accessed on 16 May 2024).
- Audiology Australia. Professional Practice Guide; Audiology Australia: Cremorne, Australia, 2022; p. 178. [Google Scholar]
- Audilogy Australia. Australian Teleaudiology Guidelines; Audiology Australia: Cremorne, Australia, 2022; p. 28. Available online: https://audiology.asn.au/standards-guidelines/teleaudiology-guidelines/ (accessed on 13 May 2024).
- American Academy of Audiology. American Academy of Audiology Clinical Practice Guidelines: Adult Patients with Severe-to-Profound Unliateral Sensorineural Hearing Loss; Clinical Practice Guidelines; American Academy of Audiology: Reston, VA, USA, 2015; p. 49. [Google Scholar]
- British Socoety of Audiology. Guidance Documents. 2023. Available online: https://www.thebsa.org.uk/guidance-and-resources/current-guidance/ (accessed on 16 May 2024).
- Rudmose, W. Automatic Audiometry. In Modern Developments in Audiology, 1st ed.; Jerger, J., Ed.; Academic Press: New York, NY, USA, 1963; p. 31. [Google Scholar]
- Rogers, C.R. Client-Centered Therapy; Its Current Practice, Implications, and Theory; Houghton Mifflin: Oxford, UK, 1951. [Google Scholar]
- Brice, S.; Almond, H. Behavior Change in Chronic Health: Reviewing What We Know, What Is Happening, and What Is Next for Hearing Loss. Int. J. Environ. Res. Public Health 2023, 20, 5605. [Google Scholar] [CrossRef]
- Brice, S.; Almond, H. Is Teleaudiology Achieving Person-Centered Care: A Review. J. Environ. Res. Public Health 2022, 19, 7436. [Google Scholar] [CrossRef]
- Eikelboom, R.H.; Bennett, R.; Brennan, M. Tele-Audiology: An Opportunity for Expansion of Hearing Healthcare Services in Australia. In Review of Telehealth Services; Ear Science Institute: Perth, Australia, 2021; p. 87. Available online: https://www.earscience.org.au/wp-content/uploads/2021/07/TeleAudiology-Report.pdf (accessed on 28 June 2024).
- Kim, S.H.; Kim, I.; Kim, H. Easing the Burden of Tinnitus: A Narrative Review for Exploring Effective Pharmacological Strategies. Cureus 2024, 16, e54861. [Google Scholar] [CrossRef]
- Boven, C.; Roberts, R.; Biggus, J.; Patel, M.; Matsuoka, A.J.; Richter, C.P. In-situ hearing threshold estimation using Gaussian process classification. Sci. Rep. 2023, 13, 14667. [Google Scholar] [CrossRef] [PubMed]
- Dillon, H.; Beach, E.F.; Seymour, J.; Carter, L.; Golding, M. Development of Telscreen: A telephone-based speech-in-noise hearing screening test with a novel masking noise and scoring procedure. Int. J. Audiol. 2016, 55, 463–471. [Google Scholar] [CrossRef]
- Blamey, P.J.; Blamey, J.K.; Saunders, E. Effectiveness of a teleaudiology approach to hearing aid fitting. J. Telemed. Telecare. 2015, 21, 474–478. [Google Scholar] [CrossRef] [PubMed]
- Parker, M.A. Identifying three otopathologies in humans. Hear. Res. 2020, 398, 108079. [Google Scholar] [CrossRef]
- DiNino, M.; Holt, L.L.; Shinn-Cunningham, B.G. Cutting through the Noise: Noise-Induced Cochlear Synaptopathy and Individual Differences in Speech Understanding Among Listeners with Normal Audiograms. Ear Hear. 2022, 43, 9–22. [Google Scholar] [CrossRef] [PubMed]
- Kim, J.M.; Rim, H.; Kim, S.; Kim, S.; Byun, J.; Yeo, S. Comparative study of SSNHL with and without tinnitus: Audiologic and hematologic differences. Acta Otolaryngol. 2023, 143, 589–595. [Google Scholar] [CrossRef]
- Vercammen, C. Audiogram and Audiogram Direct: Comparison of In-Clinic Assessments. Phonak Field Study News, June 2020; p. 6. [Google Scholar]
- Lester, J. Best Online Hearing Tests of 2023, According to Audiologists. Forbes Health. 2023. Available online: https://www.forbes.com/health/hearing-aids/best-online-hearing-test/ (accessed on 29 June 2023).
- Tye-Murray, N. A digital therapeutic and hearing health coach for enhancing first-time hearing aid experiences. Hear. Rev. 2021, 25, 25–26. Available online: https://hearingreview.com/practice-building/office-services/telehealth/hearing-health-coach (accessed on 15 March 2024).
- Dillon, H.; Day, J.; Bant, S.; Munro, K.J. Adoption, use and non-use of hearing aids: A robust estimate based on Welsh national survey statistics. Int. J. Audiol. 2020, 59, 567–573. [Google Scholar] [CrossRef] [PubMed]
- Franks, I.; Timmer, B.H.B. Reasons for the non-use of hearing aids: Perspectives of non-users, past users, and family members. Int. J. Audiol. 2023, 1–8. [Google Scholar] [CrossRef] [PubMed]
- Brice, S.; Lam, E. Comparing Teleaudiology and Traditional Audiology Client Journeys: What Counts and What to Consider. In Proceedings of the 3rd British Society of Audiology E-Conference, Online, 1–31 December 2019. [Google Scholar]
- Brice, S.; Tan, S.; Sly, D. Diagnostics underpinning digital health. In Digital Health: A Transformative Approach; Almond, H., Mather, C., Eds.; Elsevier: Amsterdam, The Netherlands, 2023; p. 328. ISBN 9780729598392. [Google Scholar]
- Brice, S.; Zakis, J. Ten Years of Teleaudiology in a Blended Model: What Can We Learn? In Proceedings of the Successes and Failures of Telehealth, Brisbane, Australia, 11 November 2022. [Google Scholar] [CrossRef]
- Ratanjee-Vanmali, H.; Swanepoel, W.; Laplante-Levesque, A. Digital Proficiency Is Not a Significant Barrier for Taking Up Hearing Services with a Hybrid Online and Face-to-Face Model. Am. J. Audiol. 2020, 29, 785–808. [Google Scholar] [CrossRef] [PubMed]
- Wasmann, J.W.; Praget, L.; Eikelboom, R.; Swanepoel, W. Digital Approaches to Automated and Machine Learning Assessments of Hearing: Scoping Review. J. Med. Internet Res. 2022, 24, e32581. [Google Scholar] [CrossRef] [PubMed]
- Dou, Z.; Li, Y.; Deng, D.; Zhang, Y.; Pang, A.; Fang, C.; Bai, X.; Bing, D. Pure tone audiogram classification using deep learning techniques. Clin. Otolaryngol. 2024, 1–9. [Google Scholar] [CrossRef] [PubMed]
- Zaar, J.; Carney, L.H. Predicting speech intelligibility in hearing-impaired listeners using a physiologically inspired auditory model. Hear. Res. 2022, 426, 108553. [Google Scholar] [CrossRef] [PubMed]
- Healy, E.W.; Yoho, S.E.; Wang, Y.; Wang, D. An algorithm to improve speech recognition in noise for hearing-impaired listeners. J. Acoust. Soc. Am. 2013, 134, 3029–3038. [Google Scholar] [CrossRef] [PubMed]
- Christensen, J.H.; Whiston, H.; Lough, M.; Gil-Carvajal, J.C.; Rumley, J.; Saunders, G.H. Evaluating Real-World Benefits of Hearing Aids with Deep Neural Network-Based Noise Reduction: An Ecological Momentary Assessment Study. Am. J. Audiol. 2024, 33, 242–253. [Google Scholar] [CrossRef] [PubMed]
- Andersen, A.H.; Santurette, S.; Pedersen, M.S.; Alickovic, E.; Fiedler, L.; Jensen, J.; Behrens, T. Creating Clarity in Noisy Environments by Using Deep Learning in Hearing Aids. Semin. Hear. 2021, 42, 260–281. [Google Scholar] [CrossRef]
- Tanveer, M.A.; Skoglund, M.A.; Bernhardsson, B.; Alickovic, E. Deep learning-based auditory attention decoding in listeners with hearing impairment. J. Neural. Eng. 2024, 21, 036022. [Google Scholar] [CrossRef]
- Cohen, Y.E.; Bennur, S.; Christison-Lagay, K.; Gifford, A.M.; Tsunada, J. Functional organization of the ventral auditory pathway. In Phsyiology, Psychoacoustics and Cognition in Normal and Impaired Hearing; Van Dijk, P., Ed.; Springer Open: New York, NY, USA, 2016; pp. 381–388. [Google Scholar] [CrossRef]
- Chan, J.; Ali, N.; Najafi, A.; Meehan, A.; Mancl, L.R.; Gallagher, E.; Bly, R.; Gollakota, S. An off-the-shelf otoacoustic-emission probe for hearing screening via a smartphone. Nat. Biomed. Eng. 2022, 6, 1203–1213. [Google Scholar] [CrossRef] [PubMed]
- Grant, K.J.; Mepani, A.M.; Wu, P.; Hancock, K.E.; de Gruttola, V.; Liberman, M.C.; Maison, S.F. Electrophysiological markers of cochlear function correlate with hearing-in-noise performance among audiometrically normal subjects. J. Neurophysiol. 2020, 124, 418–431. [Google Scholar] [CrossRef] [PubMed]
- Andersson, K.E.; Andersen, L.S.; Christensen, J.H.; Neher, T. Assessing real-life benefit from hearing-aid noise management: SSQ12 questionnaire versus ecological momentary assessment with acoustic data-logging. Am. J. Audiol. 2021, 30, 93–104. [Google Scholar] [CrossRef] [PubMed]
- Bennett, R.J.; Kosovich, E.M.; Stegeman, I.; Ebrahimi-Madiseh, A.; Tegg-Quinn, S.; Eikelboom, R.H. Investigating the prevalence and impact of device-related problems associated with hearing aid use. Int. J. Audiol. 2020, 59, 615–623. [Google Scholar] [CrossRef] [PubMed]
- Tuckute, G.; Feather, J.; Boebinger, D.; McDermott, J. Many but not all deep neural network audio models capture brain responses and exhibit correspondence between model stages and brain regions. PLoS Biol. 2023, 21, e3002366. [Google Scholar] [CrossRef]
- Kujawa, S.G.; Liberman, M.C. Adding insult to injury: Cochlear nerve degeneration after “temporary” noise-induced hearing loss. J. Neurosci. 2009, 29, 14077–14085. [Google Scholar] [CrossRef]
- Shi, L.; Chang, Y.; Li, X.; Aiekn, S.; Liu, L.; Wang, J. Cochlear Synaptopathy and Noise-Induced Hidden Hearing Loss. Neural. Plasticit. 2016, 2016, 6143164. [Google Scholar] [CrossRef] [PubMed]
- Liberman, M.C.; Kujawa, S.G. Cochlear synaptopathy in acquired sensorineural hearing loss: Manifestations and mechanisms. Hear. Res. 2017, 349, 138–147. [Google Scholar] [CrossRef]
- Keidser, G.; Dillon, H.; Flax, M.; Ching, T.; Brewer, S. The NAL-NL2 prescription procedure. Audiol. Res. 2011, 1, e24. [Google Scholar] [CrossRef]
- Scollie, S.; Seewald, R.; Cornelisse, L.; Moodie, S.; Bagatto, S.; Laurnagaray, D.; Beaulac, S.; Pumford, J. The desired sensation level multistage input/output algorithm. Trends Amplif. 2005, 9, 159–197. [Google Scholar] [CrossRef]
- Lesica, N.A. Why Do Hearing Aids Fail to Restore Normal Auditory Perception? Trends Neurosci. 2018, 41, 174–185. [Google Scholar] [CrossRef] [PubMed]
- Lazard, D.S.; Lee, H.J.; Truy, E.; Giraud, A.L. Bilateral reorganization of posterior temporal cortices in post-lingual deafness and its relation to cochlear implant outcome. Human Brain Mapp. 2013, 34, 1208–1219. [Google Scholar] [CrossRef]
- Lazard, D.S.; Vincent, C.; Venail, F.; Van de Heyning, P.; Truy, E.; Sterkers, O.; Skarzynski, P.H.; Skarzynski, H.; Schauwers, K.; O’Leary, S.; et al. Pre-, per- and postoperative factors affecting performance of postlinguistically deaf adults using cochlear implants: A new conceptual model over time. PLoS ONE 2012, 7, e48739. [Google Scholar] [CrossRef] [PubMed]
- Blamey, P.; Artieres, F.; Başkent, D.; Bergeron, F.; Beynon, A.; Burke, E.; Dillier, N.; Dowell, R.; Fraysse, B.; Gallégo, S.; et al. Factors Affecting Auditory Performance of Postlinguistically Deaf Adults Using Cochlear Implants: An Update with 2251 Patients. Audiol. Neurotol. 2013, 18, 36–47. [Google Scholar] [CrossRef] [PubMed]
- Portelli, D.; Loteta, S.; Ciodaro, F.; Salvago, P.; Galletti, C.; Freni, L.; Alberti, G. Functional outcomes for speech-in-noise intelligibility of NAL-NL2 and DSL v.5 prescriptive fitting rules in hearing aid users. Eur. Arch. Oto-Rhino-Laryngol. 2024, 281, 3227–3235. [Google Scholar] [CrossRef] [PubMed]
- Johnson, E. 20Q: Same or different—Comparing the Latest NAL and DSL Earl Johnson. Audiology Online. 2012. Available online: https://www.audiologyonline.com/articles/20q-same-or-different-comparing-769 (accessed on 27 June 2024).
- McCormack, A.; Fortnum, H. Why do people fitted with hearing aids not wear them? Int. J. Audiol. 2013, 52, 360–368. [Google Scholar] [CrossRef] [PubMed]
- D’Onofrio, K.L.; Zeng, F.G. Tele-Audiology: Current State and Future Directions. Front. Digit Health 2021, 3, 788103. [Google Scholar] [CrossRef]
- Anderson, M.C.; Arehart, K.H.; Souza, P.E. Survey of Current Practice in the Fitting and Fine-Tuning of Common Signal-Processing Features in Hearing Aids for Adults. J. Am. Acad. Audiol. 2018, 29, 118–124. [Google Scholar] [CrossRef]
- Urbanski, D.; Hernandez, H.; Oleson, J.; Wu, Y. Toward a New Evidence-Based Fitting Paradigm for Over-The-Counter Hearing Aids. AJA 2021, 30, 43–66. [Google Scholar] [CrossRef]
- Convery, E.; Keidser, G.; Hickson, L.; Meyer, C. The Relationship Between Hearing Loss Self-Management and Hearing Aid Benefit and Satisfaction. Am. J. Audiol. 2019, 28, 274–284. [Google Scholar] [CrossRef]
- Mofsen, A.M.; Rodebaugh, T.L.; Nicol, G.E.; Depp, C.A.; Miller, J.P.; Lenze, E.J. When All Else Fails, Listen to the Patient: A Viewpoint on the Use of Ecological Momentary Assessment in Clinical Trials. JMIR Ment. Health 2019, 6, e11845. [Google Scholar] [CrossRef] [PubMed]
- Blamey, P. The Expected Benefit of Hearing Aids in Quiet as a Function of Hearing Thresholds. In Tele-Audiology and the Optimization of Hearing Healthcare Delivery, 1st ed.; IGI Global: Hershey, PA, USA, 2019; pp. 63–85. [Google Scholar]
- Jenstad, L.M.; Singh, G.; Boretzki, M.; DeLongis, A.; Fichtl, E.; Ho, R.; Huen, M.; Meyere, V.; Pang, F.; Stephenson, E. Ecological momentary assessment: A field evaluation of subjective ratings of speech in noise. Ear Hearing. 2021, 42, 1770–1781. [Google Scholar] [CrossRef] [PubMed]
- Hakizimana, P. The summating potential polarity encodes the ear health condition. Cell. Mol. Life Sci. 2023, 80, 163. [Google Scholar] [CrossRef] [PubMed]
- Hoben, R.; Easow, G.; Pevzner, S.; Parker, M.A. Outer Hair Cell and Auditory Nerve Function in Speech Recognition in Quiet and in Background Noise. Front Neurosci. 2017, 11, 157. [Google Scholar] [CrossRef] [PubMed]
- Vasilkov, V.; Caswell-Midwinter, B.; Zhao, Y.; de Gruttola, V.; Jung, D.; Liberman, M.C.; Maison, S.F. Evidence of cochlear neural degeneration in normal-hearing subjects with tinnitus. Sci. Rep. 2023, 13, 19870. [Google Scholar] [CrossRef] [PubMed]
- Salvi, R.; Sun, W.; Ding, D.; Chen, G.D.; Lobarinas, E.; Wang, J.; Radziwon, K.; Auerbach, B.D. Inner Hair Cell Loss Disrupts Hearing and Cochlear Function Leading to Sensory Deprivation and Enhanced Central Auditory Gain. Front. Neurosci. 2016, 10, 621. [Google Scholar] [CrossRef] [PubMed]
- Trevino, A.C.; Jesteadt, W.; Neely, S.T. Modeling the Individual Variability of Loudness Perception with a Multi-Category Psychometric Function. In Physiology, Psychoacoustics and Cognition in Normal and Impaired Hearing; Springer International Publishing: Cham, Germany, 2016. [Google Scholar]
- Eikelboom, R.H.; Jayakody, D.M.; Swanepoel, D.W.; Chang, S.; Atlas, M.D. Validation of remote mapping of cochlear implants. J. Telemed. Telecare 2014, 20, 171–177. [Google Scholar] [CrossRef] [PubMed]
- Takano, K.; Takano, K.; Kaizaki, A.; Kimura, A.; Nomura, K.; Yamazaki, N.; Shintani, T.; Himi, T. Telefitting of Nucleus Cochlear Implants: A Feasibility Study. Am. J. Audiol. 2021, 30, 16–21. [Google Scholar] [CrossRef] [PubMed]
- Holtmann, L.C.; Deuss, E.; Meyer, M.; Kaster, F.; Bastian, T.; Schleupner, M.; Hagedorn, E.; Lang, S.; Arweiler-Harbeck, D. Detection accuracy of soft tissue complications during remote cochlear implant follow-up. Cochlear Implant. Int. 2022, 23, 249–256. [Google Scholar] [CrossRef]
- Van der Mescht, L.; Le Roux, T.; Mahomed-Asmail, F.; De Sousa, K.C.; Swanepoel, D.W. Remote Monitoring of Adult Cochlear Implant Recipients Using Digits-in-Noise Self-Testing. Am. J. Audiol. 2022, 31, 923–935. [Google Scholar] [CrossRef]
- Maruthurkkara, S. Cochlear Implant Remote Assist: Clinical and Real-World Evaluation. Int. J. Audiol. 2024, 2, 1–11. [Google Scholar] [CrossRef] [PubMed]
- Barda, A.; Shapira, Y.; Fostick, L. Individual Differences in Auditory Training Benefits for Hearing Aid Users. Clin. Pr. 2023, 13, 1196–1206. [Google Scholar] [CrossRef] [PubMed]
- Stropahl, M.; Besser, J.; Launer, S. Auditory Training Supports Auditory Rehabilitation: A State-of-the-Art Review. Ear. Hear. 2020, 41, 697–704. [Google Scholar] [CrossRef] [PubMed]
- Reis, M.; McMahon, C.M.; Tavora-Vieira, D.; Humburg, P.; Boisvert, I. Effectiveness of Computer-Based Auditory Training for Adult Cochlear Implant Users: A Randomized Crossover Study. Trends Hear. 2021, 25, 23312165211025938. [Google Scholar] [CrossRef] [PubMed]
- Bardy, F.; Jacquemin, L.; Wong, C.L.; Maslin, M.R.D.; Purdy, S.C.; Thai-Van, H. Delivery of internet-based cognitive behavioral therapy combined with human-delivered telepsychology in tinnitus sufferers through a chatbot-based mobile app. Front. Audiol. Otol. 2024, 1, 1302215. [Google Scholar] [CrossRef]
- Abouzari, M.; Goshtasbi, K.; Sarna, B.; Ghavami, Y.; Parker, E.; Khosravi, P.; Mostaghni, N.; Jamshidi, S.; Saber, T.; Djalilian, H. Adapting Personal Therapies Using a Mobile Application for Tinnitus Rehabilitation: A Preliminary Study. Ann. Otol. Rhinol. Laryngol. 2021, 130, 571–577. [Google Scholar] [CrossRef] [PubMed]
- Kaldo, V.; Levin, S.; Widarsson, J.; Buhrman, M.; Larsen, H.C.; Andersson, G. Internet versus group cognitive-behavioral treatment of distress associated with tinnitus: A randomized controlled trial. Behav. Ther. 2008, 39, 348–359. [Google Scholar] [CrossRef] [PubMed]
- Humes, L.E.; Kinney, D.L.; Brown, S.E.; Kiener, A.L.; Quigley, T.M. The effects of dosage and duration of auditory training for older adults with hearing impairment. J. Acoust. Soc. Am. 2014, 136, EL224. [Google Scholar] [CrossRef] [PubMed]
- Tye-Murray, N.; Spehar, B.; Barcroft, J.; Sommers, M. Auditory Training for Adults Who Have Hearing Loss: A Comparison of Spaced Versus Massed Practice Schedules. J. Speech Lang. Hear. Res. 2017, 60, 2337–2345. [Google Scholar] [CrossRef] [PubMed]
- Van Wilderode, M.; Vermaete, E.; Francart, T.; Wouters, J.; van Wieringen, A. Effectiveness of Auditory Training in Experienced Hearing-Aid Users, and an Exploration of Their Health-Related Quality of Life and Coping Strategies. Trends Hear. 2023, 27, 23312165231198380. [Google Scholar] [CrossRef]
- Meister, H. Speech audiometry, speech perception, and cognitive functions: English version. HNO 2017, 65 (Suppl. 1), 1433–1458. [Google Scholar] [CrossRef] [PubMed]
- Carlile, S.; Keidser, G. Conversational Interaction Is the Brain in Action: Implications for the Evaluation of Hearing and Hearing Interventions. Ear Hear. 2020, 41, 56S–67S. [Google Scholar] [CrossRef] [PubMed]
- Holmes, E.; Griffiths, T.D. ‘Normal’ hearing thresholds and fundamental auditory grouping processes predict difficulties with speech-in-noise perception. Sci. Rep. 2019, 9, 16771. [Google Scholar] [CrossRef] [PubMed]
Clinical Guidelines: | Assessment | Fitting of Devices | Rehabilitation |
---|---|---|---|
Audiology Australia: Professional Practice Guidelines [2] | Domain 4: identifying ear and hearing conditions | Domain 5: rehabilitation support 5.6–8 technological aids | Domain 5: rehabilitation support 5.1–5.4 and 5.14 |
Audiology Australia: Australian Teleaudiology Guidelines [3] | Clinical guidance: hearing screening and audiological assessment | Hearing and assistive devices—fittings, adjustment, and aftercare | Hearing and assistive devices—fittings, adjustment, and aftercare |
American Academy of Audiology: Standards of Practice for Audiology [4] | Standard II identification (screening) and Standard III evaluation/(diagnosis) | Standard IV Treatment A. 1 | Standard IV Treatment A. 2 |
British Society of Audiology: Various Guidance Documents [5] | Tympanometry and acoustic reflex thresholds, pure tone air and bone conduction threshold audiometry with and without masking, and assessment of speech understanding in noise in adults with hearing difficulties | BAA BSA Remote Fitting Guidance | Adult rehabilitation—common principles in audiology services |
Location | Stage |
---|---|
(1) Sound sources | Environmental |
(2) Soundwaves travel through air | Environmental |
(3) Outer ear (pinna) | Conductive |
(4) Outer ear (ear canal and ear drum) | Conductive |
(5) Middle ear | Conductive |
(6) Inner ear (basilar membrane) | Conductive |
(7) Inner ear (hair cells) | Sensory |
(8) Inner ear (nerve cells) | Neural |
(9) Inner ear (shared neurons) | Neural |
(10) Brain (temporal lobe) | Auditory processing |
(11) Brain (cognitive complexity) | Auditory processing |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Brice, S.; Zakis, J.; Almond, H. Changing Knowledge, Principles, and Technology in Contemporary Clinical Audiological Practice: A Narrative Review. J. Clin. Med. 2024, 13, 4538. https://doi.org/10.3390/jcm13154538
Brice S, Zakis J, Almond H. Changing Knowledge, Principles, and Technology in Contemporary Clinical Audiological Practice: A Narrative Review. Journal of Clinical Medicine. 2024; 13(15):4538. https://doi.org/10.3390/jcm13154538
Chicago/Turabian StyleBrice, Sophie, Justin Zakis, and Helen Almond. 2024. "Changing Knowledge, Principles, and Technology in Contemporary Clinical Audiological Practice: A Narrative Review" Journal of Clinical Medicine 13, no. 15: 4538. https://doi.org/10.3390/jcm13154538
APA StyleBrice, S., Zakis, J., & Almond, H. (2024). Changing Knowledge, Principles, and Technology in Contemporary Clinical Audiological Practice: A Narrative Review. Journal of Clinical Medicine, 13(15), 4538. https://doi.org/10.3390/jcm13154538