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How cognition might influence hearing aid-design, fitting, and outcomes

Pichora-Fuller, Kathleen

doi: 10.1097/01.HJ.0000364274.44847.dc

Kathy Pichora-Fuller, PhD, an Audiologist and a Cognitive Psychologist, is a Professor of Psychology at the University of Toronto and an Adjunct Scientist at the Toronto Rehabilitation Institute. Readers may contact Dr. Pichora-Fuller at Department of Psychology, University of Toronto, 3359 Mississauga Road N., Mississauga, ON, Canada L5L1C6; at 905/828-3865; or at

In 2003, several landmark papers about the relevance of cognition to success with hearing aids captured the attention of practicing audiologists, academic researchers, and industrial hearing aid developers.1-4 These papers kindled hopes that cognitive factors might provide the missing pieces that would solve many of the long-standing puzzles that have perplexed hearing healthcare professionals: Why are auditory measures such poor predictors of everyday listening experiences? How can two individuals with the same audiogram and the same hearing aid fitting have such different listening experiences? How can a given individual have such varied listening experiences depending on the communication situation?

These papers also raised many new questions in the minds of hearing healthcare professionals about whether or not cognitive measures should be incorporated into their testing routines and, if so, what would be the optimal measures and how would such measures be used in planning and/or assessing treatment.

Research conducted over the last six years on the connection between auditory and cognitive processing has provided new insights into the experiences of people who are hard of hearing, and approaches have been proposed for integrating cognitive concepts and measures into hearing aid design, fitting, and outcome measurement. Nevertheless, much work remains to be done before cognitive measures can be used in regular clinical practice. This paper provides a synopsis of where we have come and where we still need to go in exploring the role of cognitive factors in hearing rehabilitation.

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Among healthy adults without any known clinically significant cognitive impairments, those who perform more poorly on cognitive tests tend to perform more poorly also on tests of speech recognition in noise, whether or not they are wearing hearing aids.1,4,5 It is relatively easy to hear in ideal, quiet conditions, and cognitive abilities are not so important when speech is heard in quiet and it is easy to listen. But cognition becomes more important when speech is heard in background noise and listening requires effort.

Of course, high levels of noise will cause a drop in word recognition because important speech cues are masked. However, in noisy conditions that are less adverse, when word-recognition accuracy remains high (>80%) but listening is no longer easy, then cognition seems to explain differences in the degree of effort associated with a person's listening experience.6

Furthermore, some types of background noise are more challenging than others. Listening is more challenged when the background noise fluctuates than when it is steady over time. That is partly because listening in the dips of the fluctuations taxes the auditory system, but it is also because it is cognitively easier to ignore a steady background than one that is rapidly changing. Listening is also more challenged when the background is speech than when it is white noise or speech-shaped noise. For one thing, segregating voices taxes the auditory system when the signals are so similar. Also, because the competing speech is meaningful it distracts the listener, who inevitably divides his or her attention between the target speech and the distracting speech steams in a multi-talker situation.

Importantly, the results of research showing how cognition influences listening performance in challenging conditions seem to explain some of the experiences of our patients whose performance depends so much on the listening situation in ways that cannot be simply explained in terms of hearing thresholds in quiet, signal-to-noise ratios, or even masking.

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Listening is also more challenged when listeners are trying to do another task at the same time, such as walking or driving a car. Even if they hear the speech and can repeat it correctly, they will not remember it as well if they are multi-tasking7 or if the signal-to-noise ratio is challenging8-12 as they would if they heard the speech in ideal, quiet conditions.

Whether speech recognition is tested in quiet or in noise, traditional tests have been conducted in conditions in which the listener's only task is to listen and he or she is told what to listen to and where to listen. Not surprisingly, even if an individual's speech-recognition performance is excellent in more typical testing conditions, it can drop significantly when the listener is placed in a situation where he or she is uncertain as to where the target voice will be spatially located and therefore must switch attention among multiple voices positioned at different locations.13 Performance can also vary depending on how able the person is to divide attention among multiple sources, such as listening to speech and background music at the same time.14

In addition, the goals of listeners, whether to gain information or to establish and maintain social relationships, can also influence what they choose to listen to and how they listen to it. For example, a student in a classroom needs to listen for the purpose of taking notes about detailed information that might be examined. However, the same student will have different listening goals when chatting to peers at a party during the first term of university when the main goal is to meet new friends and re-connect to old friends. Whereas the details of the speech signal and a high level of focused concentration on the lecture are required in the classroom, the gist of what is being said and more broadly distributed attention to the group as a whole are probably more helpful in the party situation.15 Clearly, these differences in listening performance in the real world do depend on auditory factors, but cognitive factors can be critical when we use our hearing for the purposes of communication.

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So far we have considered how the experiences of a particular listener, involving both auditory and cognitive processing, may vary depending on the environment and the task. However, even within the cognitively normal population, it is well known that there are sub-clinical differences among individuals' cognitive abilities, such as working memory, speed of processing, and attention, that might affect spoken communication.16 For example, inter-individual differences in working memory are significantly related to how well people comprehend language, whether it is written or spoken.17

Of course, speech recognition crucially depends on speech being audible, so degree of hearing loss has a powerful influence on speech-recognition performance. But when adequate amplification is provided, then more than half of the variability in the performance of individuals with hearing loss is due to other factors, including age and cognitive factors.18-19 Those whose cognitive performance is poorer use hearing aids more and show greater benefits from them.1,3 Presumably, listeners who perform better on cognitive tests are better able to compensate by drawing on context and other non-auditory sources of information so they suffer less when there is background noise and they depend less on sound input than do those who are less able to use knowledge and cognitive skills to compensate for hearing problems.20,21

It is also interesting that those whose cognitive performance is better seem to have greater awareness of and ability to describe subtle differences among hearing aid processing options.4 It is even more striking that those with higher cognitive performance seem better able than those with lower cognitive performance to learn to listen to the sound of a new hearing aid, at least if the aid has fast-acting, multi-band, wide-dynamic range compression and it is used when the competing noise is modulated.22-24 However, their cognitive advantage may be most important during the acclimatization period.25

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The 2003 studies on cognition and success with hearing aids inspired some scientists and clinicians to think about the possibility of using cognitive measures to assess candidacy for hearing aid options such as fast-acting, multi-band, wide dynamic range compression.22-23 However, others suggested that cognitive measures might be more valuable as a new type of outcome measure.9

Although speech tests were once used to select one hearing aid as the best in a set of hearing aids, it has been decades since these tests have been sufficiently sensitive to be of much value in helping clinicians decide which hearing aid fitting would be best for a particular client. In many first-time hearing aid fittings, speech scores are at or near ceiling when testing is conducted in quiet, and even tests in noise may not help to differentiate between hearing aid options.

Nevertheless, we know that clients may notice differences among devices and they report that listening sometimes requires effort even if they have apparently near-perfect performance on aided speech tests. We would like to find more reliable ways of determining which technology would be best for patients, and cognitive measures could be a promising new way to measure outcomes. For example, even when word recognition is accurate, if listening requires more explicit cognitive processing,24 then listening effort might be indexed by measures of working memory span, with higher spans in a given condition providing evidence that listening in that condition was easier than listening in another condition where working memory span was lower for the same person.9

Attempts to use cognitive measures to evaluate success with hearing aid fittings and to distinguish among hearing aid options have only just begun. For example, in a dual-task situation, cognitive measures, including memory for the target words and reaction times on a secondary visual task, have been used successfully to show that listening effort is reduced when noise-reduction algorithms are used in hearing aids, even though such differences are not observable using typical speech testing in quiet or in noise.26 Indeed, leading scientists working on the development of hearing aids are actively exploring how the design of future hearing aids can be guided by a better understanding of the cognitive aspects of listening, and how hearing aids might actually be beneficial to a person's auditory performance as well as cognitive performance.26-28

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The significant correlations between cognition and success with newly fitted, complex, fast-acting hearing aids beg for an explanation of the nature of the connection. One possible explanation is that those with better cognitive abilities have an advantage in re-learning how to map sound to meaning.9 Indeed, during perceptual learning of distorted speech, young adult listeners with normal hearing use areas of their brain that are believed to be involved in semantic processing and working memory.29 It also seems that changes in how the cortical areas of the brain process speech in noise may account for some of the perceptual difficulties of older listeners.30

Whether changes in brain plasticity occur over the course of an experiment in a young adult or over the course of decades in an older adult, it seems reasonable that changes in brain organization play a role in how individuals acclimatize to hearing aids. It may be that persons with higher cognitive abilities more readily engage areas of the brain so that adjustment to complex new hearing aids is facilitated. It is intriguing to consider that people who have lower cognitive abilities may be the ones who would benefit most from more structured learning experiences during hearing rehabilitation.

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Accepting that it might be a good idea to try to measure cognition, either to guide the planning of rehabilitation or to evaluate its outcomes, what measures would we use? So far, it seems that tests of working memory, especially tests involving the sequencing of information, are the best candidates.5,9,31 Future research may show that we could also gain valuable new insights into listening performance by using tests that tap auditory attention, such as by measuring word recognition in dual-task conditions with varying levels of listening effort,26 or in a multi-talker display with varying degrees of certainty about the spatial location of the target talker.32

As we move toward tests that better approximate the conditions of everyday listening, future developments will likely take us into more extensive use of virtual reality simulations that enable us to create different well-controlled but more realistic listening environments in the clinic. At the same time, we will also need to move toward using more realistic materials and tasks, such as multi-talker conversation or multi-tasking scenarios such as listening while walking.

One drawback of traditional speech tests, or even tests incorporating memory or attention, is that that they are “off-line” measures. That is, by the time the person repeats the word, considerable time has elapsed and most of the auditory and cognitive processing has been completed. Such tests tell us if the person heard or remembered the word correctly, but they do not tell us which auditory and cognitive circuits were used in the brain to arrive at the answer.

Different routes, some more cognitively demanding or inefficient than others, may be used to access a word, depending on the listening conditions and the expertise of the listener. Brain imaging can provide information about the areas of the brain that are activated, but this technique on its own does not yet have the time resolution to capture fast changes that might be occurring as a person listens. Tests of speed of processing or reaction time provide some information about how much processing took place if we assume that more processing takes more time. However, it is still difficult to know exactly what kind of processing was being slowed or speeded in various conditions.33

In an effort to learn more about the kind of processing being done in the brain “online” as the listener follows speech as it unfolds, researchers are using techniques such as evoked response potentials, eye-movement tracking, and monitoring of pupil dilation. While these online measures may be very useful for research, it is hard to imagine that the typical person being fitted with hearing aids would be evaluated in this way.

To be clinically feasible, new tests will need to be proven to provide important information for decisions regarding treatment, and they will have to be acceptable to both patients and clinicians in terms of being sufficiently fast, easy, and comfortable. We still have some way to go before new tests will be ready for non-research use, but we have made great progress over the last six years in tackling these issues.

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© 2009 Lippincott Williams & Wilkins, Inc.