Starkey Research & Clinical Blog

The Fabric of Tomorrow

In Informed Dreaming, we explored the impact of the rate of scientific discovery and technology change on research in general and on hearing aid research in particular. From here will begin to look more closely at how some of that change will manifest itself in the everyday technologies of tomorrow. So let’s précis that roadmap.

There are two main technological forces in this story – computing power and connectivity. These are quite literally the backbone from which many other profoundly influential players will derive their power. If there was only one dominant idea, it would be ubiquitous computing – a term coined by the brilliant computer scientist Mark Weiser in 1991 in his influential Scientific America article “The Computer for the 21st Century.” As head of computer science at Palo Alto Research Center in Palo Alto, he envisaged a future where our world was inextricably interwoven with a technological fabric of networked “smart” devices. Such a network has the capability to manage our environments from the macro down to a detailed, individualized level – everything from the power grid to the time and temperature of that morning latte.

But these devices are also inputs to the system – detectors and sensors feeding a huge river of information into the central core, or cloud as we now know it. Many of these are already worn by people (mobile phones, smart watches, activity monitors etc. all uploading to the cloud) and the sophistication and bio-monitoring capability of these wearables is increasing by the week. Moreover, many of these sensors are stationary but have highly detailed knowledge about their transactions – cashless transactions record the person the time the place and the goods, tapping on and off public transport, taking a taxi, an Uber, a flight, a Facebook post, street closed-circuit television security systems, your IP address, cookies and the browser trail, etc.

Notwithstanding the issues of privacy (if indeed that still exists), this provides an inkling of the data flowing into the cloud – no doubt only the very tip of this ginatic iceberg. Big Data is here and it is here to stay, and although Google is King, these particular information technologies are but babies.

I was fortunate enough to attend the World Wide Web conference in 1998 where Tim Berners-Lee, the man who invented the World Wide Web while working at CERN in 1989, began promoting the idea of the Semantic Web – a means by which machines can efficiently communicate data between each other. In the ensuing years, much work has gone into developing the standards and implementing the systems. In that time however, two other massive developments have also occurred that may overshadow or subsume these efforts: On the one hand – natural language processing has matured using both text and audio in the forms of Siri, Google Talk and Cortana to mention just a few. On the other hand, driven by huge strides in cognitive neuroscience, processing power and advanced machine learning, we are witnessing a rebirth of Artificial Intelligence (AI) and the promise of so-called Super Intelligence.

So just how can we design listening (hearables) technologies, hearing aids in particular, that can capitalize on these profound developments? Well, let’s take a sneak peek at what a future hearing aid might look like in this brave new world.

Imagine a hearing aid that can listen to the world around the wearer and break down that complex auditory scene into the key relevant pieces – sorting the meaningful from the clutter. A hearing aid that can also listen into the brain activity of the listener and identify the wearer’s focus of attention and enhance the information from that source as it is coded by the brain. A hearing aid that in fact, is not a hearing aid but a device that people wear all the time as a communication channel for other people and machines, for their entertainment, as a brain and body monitor that also maps their passage through space. Such a device provides support in adverse listening conditions to the normally hearing and the hearing impaired alike – it simply changes modes of operation as appropriate.

Possibly the most surprising thing about this scenario is that, in advanced research laboratories around the world (including Starkey Research), the technologies that would enable such a device exist RIGHT NOW. Of course they are not developed to provide the level of sophisticated sensing and control that are required to give life to this vision, nor are they in a form that people can put in their ears. But they do exist and if we have learned anything from watching the progress of science and technology over the last few decades, their emergence as the Universal Hearable Version 1.0 will likely happen even sooner than we might sensibly predict from where we now stand.


Informed Dreaming for a Better Hearing Tomorrow

Part of my day job is to dream – not to daydream but to dream in a disciplined and focused way! I call this informed dreaming, and I believe it is essential for some of the other parts of my job. Because what I do is invent the future. Not the whole future – just a little slice. But this is a very important slice of the future. As Senior Director of Research at Starkey Hearing Technologies, envisioning the future is an essential part of designing the listening technology for tomorrow.

Hearing aids have undergone amazing changes over the last couple of decades. The move to digital ushered in a new age. Enabling technologies such as multiband compression, feedback cancellation, noise reduction, speech enhancement, environment classification and a host of other signal processing technologies that have significantly extended listening capability.

Wireless was the next major stepping stone, allowing direct communication and control from smart phones, the development of enhanced directional technologies, binaural linking and preservation of spatial cues, and new forms of noise reduction. The well is far from dry.

But what’s the next big step? Good research — research that takes the solutions to the next level and has a time horizon beyond the immediate capabilities of current platforms and technologies. Ten or even five years out, we have to imagine the capabilities of the technological environments in which our new devices will land. This is where the informed dreaming comes in. Predicting the future is a perilous business but an essential component of the sorts of applied research that we do at Starkey.

So what might this future world look like? The Greek philosopher Heraclitus (also known as “The Obscure” or the “weeping philosopher”) wrote that the only constant was change – quoted by Plato as saying that “you could not step twice into the same river.” Heraclitus could have never imagined how fast that river could flow – a torrent, a rapid that sweeps all before it! Today, the landscape, the very course of the river changes before our eyes.

What we do in research now is based on the science and research of millions of scientists across the world. One estimate of the size of today’s scientific knowledge is the number of peer reviewed articles, which according to the influential scientific journal Nature last year totalled 1.8 million peer reviewed articles published cross 28,000 scientific journals. More to the point, this number is increasing with a compound growth rate of 9 percent a year – this means that the scientific knowledge is doubling every nine years! It shouldn’t surprise us then that in 10 years’ time, like Dorothy, we might suspect that “Toto, I’ve a feeling we’re not in Kansas anymore.”

Over the next few weeks this blog will explore technology and social changes that are extremely relevant to our mission to transform the lives of millions of people whose hearing is challenged. Beethoven, the musical genius who bridged and defined the Classical to the Romantic periods of western music, wrote to his brothers at the onset of his own deafness.  For him it was the crippling social impairment, the loss of his ability to communicate with those he cared for and loved, that drove him to contemplate suicide. It wasn’t his inability to hear the notes of the piano that made him most desperate (although he lamented this most keenly). The great insult to his life was the social isolation that deafness forced upon him. He could still hear his music in his mind. He could only guess at the rest. Fortunately for us, he chose a more philosophical route. In 1802, he wrote

“Forced already in my 28th year to become a philosopher, O it is not easy, less easy for the artist than for anyone else – Divine One thou lookest into my inmost soul, thou knowest it, thou knowest that love of man and desire to do good live therein.”  (see HERE for a scan of the original letter and a translation)

His brothers (Carl and Johann) never received his letter – it was found amongst his papers after his death, but it is a most poignant statement of the catastrophe that hearing impairment visits upon all humankind.

It is critical that we understand the possibilities that the raging river of scientific discovery can provide to remove this veil of isolation, this inability to communicate that forces itself upon otherwise engaged and productive individuals.

Over the next few weeks, this blog will introduce us to the Internet of Things – a near future state, where not only are the things in the world connected and communicating but include a huge range of sensors and data gathering devices that provide a rich and detailed real-time picture of the world. This blog will touch on Big Data, the Semantic Web, Artificial Intelligence and Super Intelligence. We are already immersed in some of this and the only uncertainty is not “if” but “when.” Wearables and hearables, biosensors that touch the skin or dwell beneath the skin, tattoos that transmit, jewellery that knows the focus of the mind’s eye and much more!

My challenge and the challenge of my team, is to understand how we leverage these technologies and this tumultuous torrent of scientific discovery to improve the lives of millions.


Modern Remote Microphones Greatly Improve Speech Understanding in Noise

Rodemerk, K. & Galster, J. (2015).  The benefit of remote microphones using four wireless protocols. Journal of the American Academy of Audiology, 1-8.

Wireless hearing aids have made remote microphones more accessible, affordable, and easier to use. As a result, use of these systems has become more common. Most hearing aid developers now offer remote microphones that transmit at different wireless frequencies than the comparatively traditional FM system. Some of these system pair directly with hearing aids via 900MHz or 2.4GHz wireless protocols, whereas others communicate via a receiver boot that is physically attached to the hearing aids, or an intermediate device that is worn around the neck or on the lapel, most of these intermediate act as a relay that receives a Bluetooth audio signal from the remote microphone, translating it to a wireless signal that can be received by the hearing aid. The goal of all of these systems is to provide the benefits of a clean speech input; including the ability to overcome distance, reverberation and noise to provide a consistently high-quality speech signal to the listener.

The purpose of the current study was to compare the performance of four commercially available hearing aid/remote microphone systems and to assess their benefits for hearing aid users.  Sixteen hearing-impaired individuals participated in the study. There were ten females and six males and their mean age was 68.5 years with a range from 52-81 years. All subjects had bilateral, symmetrical, sensorineural hearing loss. Ten participants were experienced hearing aid users and six were non-users, though hearing aid experience was not specifically examined in this study.

For the purposes of the study, participants were fitted with three bilateral sets of hearing aids from three different hearing aid manufacturers, paired with four different remote microphone systems. One set of aids communicated directly with a remote microphone via a 900MHz signal, another set communicated directly with the remote microphone via a 2.4GHz signal. The third pair of aids worked with either an FM remote microphone transmitter and FM receiver boot or a remote microphone used with an intermediate Bluetooth receiver that transmitted information to the hearing aids via a magnetic wireless protocol: this set of hearing aids was used in two of the four remote microphone conditions in this study.

Speech recognition was assessed using the HINT test (Nilsson et al., 1994). The HINT sentences were presented with continuous, 55dB speech-shaped noise, delivered through four speakers surrounding the listener at 45, 135, 225 and 315 degrees. Sentence stimuli were presented at a 0-degree azimuth, at levels that were systematically varied to arrive at the level required to achieve a 50% correct score. Twenty sentences were presented in each listening condition and the order of manufacturer and listening conditions were randomized for each participant. Each listening condition was assessed at two talker-listener distances; with the listener seated 6 feet away from the talker loudspeaker and again at 12 feet away from the loudspeaker.

Speech recognition was assessed under four listening conditions:

1.         Unaided

2.         Hearing aid only – omnidirectional

3.         Remote microphone only (hearing aid microphones off)

4.         Remote microphone plus hearing aid microphones (equal contribution from remote and HA microphones)

For the remote microphone only conditions, all four remote microphone systems yielded speech recognition scores that were 11-15dB better than unaided and hearing aid only conditions. There were no significant differences among the four remote microphone systems. This pattern of results was consistent when the listener was seated six feet and twelve feet from the loudspeaker.

Similar results were found for the remote microphone plus hearing aid conditions, in that all four remote microphone conditions were better than the unaided or hearing aid alone conditions. However, only three of the four hearing aid/remote microphone systems were comparable to each other in this condition: the FM, Bluetooth, and 900MHz models. The 2.4GHz model yielded significantly poorer scores than the other systems when the hearing aid microphone was used in combination with the remote microphone. As in the remote microphone only condition, results for the remote microphone plus hearing aid condition were comparable for the listening distances of 6 feet and 12 feet.

All four of the remote microphone systems evaluated in this study improved speech recognition scores from 6 to 16dB, a range comparable to previous reports of performance with FM systems (Hawkins, 1984; Boothroyd, 2004; Lewis, 2008). These results indicate that hearing aid users who experience difficulty understanding speech in noisy environments could expect benefit from any of the systems that were evaluated in this study.  The talker-listener distances examined here are comparable to those examined in previous studies and represent typical situations in which hearing aid users might listen to other conversational participants in everyday situations.

This study showed that when the hearing aid microphone was turned on, providing equal contribution to the remote microphone, the speech recognition benefit was less than that measured with the remote streaming microphone alone, though there was still a significant improvement over unaided and hearing aid only conditions.  This is in agreement with previous studies that reported decreased FM benefit when the hearing aid microphone level was equal to the FM microphone, as compared to FM alone (Boothroyd & Iglehart, 1998). However, many remote microphones allow the hearing aid microphone level to be adjusted in the software. The optimal hearing aid microphone attenuation for remote microphone use requires further examination and may vary with environment and each patients goals for listening.

This study provides compelling support for the benefits of remote microphone systems and lays the groundwork for further examination of remote microphones and how they interact with hearing aid programming parameters and a variety of acoustic environments. Of clinical note was the fact that the research audiologists supporting data collection quickly learned the importance of counseling for successful use of remote microphones. For instance, it was apparent that many participants expected table top placement of a remote microphone would yield benefits similar to those experienced when the remote microphone was place near the talker’s mouth. This point of confusion was clarified through live demonstration of the remote microphone at the time of fitting, during which they will clearly hear that talker’s voice becomes much quieter as the remote microphone is moved away from the talker’s mouth. The remote microphone can be an extremely useful tool but prescription must be accompanied by sufficient counseling and in-office demonstration time.



Boothroyd, A. (2004). Hearing aid accessories for adults: the remote FM microphone. Ear and Hearing 25 (1), 22-23.

Boothroyd, A. & Iglehart, F. (1998). Experiments with classroom FM amplification. Ear and Hearing 19 (3), 202-217.

Hawkins, D. (1984). Comparisons of speech recognition in noise by mildly-to-moderately hearing-impaired children using hearing aids and FM systems. Journal of Speech and Hearing Disorders 49(4): 409-418.

Lewis, D. (2008). Trends in classroom amplification. Contemporary Issues in Communication Sciences and Disorders 35, 122-132.

Nilsson, M., Soli, S. & Sullivan, J. (1994). Development of the Hearing in Noise Test for the measurement of speech reception thresholds in quiet and in noise. Journal of the Acoustical Society of America 95(2), 1085-1099.

Rodemerk, K. & Galster, J. (2015).  The benefit of remote microphones using four wireless protocols. Journal of the American Academy of Audiology, 1-8.

The Christmas Party Problem: Guest Post from Dr. Simon Carlile

 A version of this blog first appeared as an article in the Australian Audiology Today Christmas edition.

One problem with Christmas parties is that there are so many of them and picking which ones to go to can be difficult. Something to influence your decision (other than the quality of the wine on offer) might be where the party is being held. The downtown club with disco music pounding away might be great if you want to dance the night away but that type of venue is not going to help you develop your network with witty conversation and one-liners. Of course, the real Christmas party challenge, even in less busy environments, is hearing and understanding what others are saying at such gatherings; a problem that is virtually insurmountable for those with even a moderate hearing loss.

The Original “Cocktail Party”

Colin Cherry was the first to coin the phrase “the cocktail party problem,” and it seems appropriate to paraphrase that term in regards to this Christmas issue. While most people reading this article have probably come across this term, not many will have the opportunity to read Cherry’s original paper – and what an interesting read it is! His brief, but very influential paper, “Some experiments on the recognition of speech with one and with two ears” first appeared in the Journal of the Acoustical Society in 1953 and is remarkable for a number of reasons.

First, in coining the term the “cocktail party problem,” the question for Cherry was “How do we recognize what one person is saying when others are speaking at the same time?” Two important ideas can be drawn from this, both of which relate to the fact that the conversational environment of the cocktail party involves multiple talkers rather than just one talker and background noise. The first idea is that some talkers will be conveying information that is of interest and also not of interest, i.e. conversation is a multisource listening challenge where focus must quickly switch between sources. The second idea is that many of the talkers’ voices will be what constitutes noise. This is important because the nature of the background sounds are important in terms of the type of masking needed to enable focusing on the sound of interest and the sorts of processing available to the auditory system to ameliorate that masking (see “A primer on masking” below).

Second, Cherry’s paper is mostly about selective attention in speech understanding, the role of the “statistics of language,” voice characteristics and the costs and time course of switching attention. In the Introduction he makes a very clear distinction between the kinds of perceptions that are studied using simple stimuli, such as clicks or pure tones, and the “acts of recognition and discrimination” that underlie understanding speech in the “cocktail party” environment. Cherry’s paper has been cited nearly 1,200 times, but interestingly enough, the greater proportion of those focused on detecting sounds on a background of other sounds used simple stimuli such as tones against broadband noise or other tones. Hardly the rich and complex stimuli that Cherry was talking about. Of course this was very much the bottom-up, reductionist approach of the physicists and engineers in Bell Labs and elsewhere who had had an immense influence on the development of our thinking about auditory perception, energetic masking in particular (See Box – “A primer on masking” and the discussion of the development of the Articulation Index).

An excellent and almost definitive review of this literature is provided by Adelbert Bronkhorst in 2000: “The Cocktail Party Phenomenon: A Review of Research on Speech Intelligibility in Multiple-Talker Conditions.” The research over that period focused on energetic unmasking. For instance: the head shadow producing a “better ear advantage” by reducing the masker level in the ear furthest from the source, the effects of binaural processing or the effects of the modulation characteristics of speech and other maskers. So, on the one hand, the high citation rate for Cherry’s paper is very surprising because there is very little in the original paper that relates to energetic masking. On the other hand, the appropriation of the term “the cocktail party problem” and the reconfiguring of the research question demonstrates the powerful influence of the bottom-up, physics-engineering approach to thinking about auditory perception. This had become the lens through which much thinking and research was viewed. To be fair though, Bronkhorst does point out in his review that there were some data in the literature involving speech-on-speech masking that were not well explained by energetic masking but that this had not been a particular focus of the research.


Informational Masking

The turn of the century was propitious for hearing science as it marked another turning point in our thinking about this “cocktail party” problem. In 1998, Richard Freyman and colleagues reported that differences in the perceived locations of a target and maskers (as opposed to actual physical differences in location) produced a significant unmasking for speech maskers but not for noise. Such a result was not amenable to a simple bottom-up explanation of energetic masking. Thus, Freyman appropriated the term “information masking” which had been previously used in experiments involving relatively simple stimuli. This was the first time it had been applied to something as complex and rich as speech. As we shall see in more detail later, the unmasking produced in this experiment depended on the active, top-down focus of attention. As previously mentioned, Bronkhorst had pointed out that others had noted speech interference of speech understanding seemed to amount to more than the algebraic sum of the spectral energy. Indeed, as early as 1969, Carhart and colleagues had referred to this as “perceptual masking” or “cognitive interference.” Along those lines, information masking in the context of the perceptual unmasking in Freyman’s and later similar experiments came to stand for everything that wasn’t energetic masking.

Over the ensuing 15 years, many studies have been carried out examining the nature of information masking. A number of general observations can be made and some of these are drawn out in the “Primer” below. One very important shift however, was that the “cocktail party problem” became increasingly seen as a particular case of the general problem of auditory scene analysis (ASA). This is the problem of “acoustic superposition” where the energy from multiple concurrent sounds converges on a single encoder; in this case the cochlea of the inner ear. The first task of the auditory system then, is to work out which spectral components belong to which sound sources and to group them together in some way. The second task is how these now segregated components are joined up in time to provide a stream of information associated with a specific sound.


Auditory Scene Analysis

Albert Bregman did much to promote thinking in this area with the publication of Auditory Scene Analysis in 1992, marking a significant return of Gestalt thinking to the study of auditory perception. Although this part of the story is still being worked out, it is clear that much of the grouping and steaming processes underlying ASA are largely automatic, that is bottom-up, and they capitalize on the physical acoustics of sounding bodies – probably not surprising given that the auditory system evolved in a world of physically sounding bodies and “the cocktail party problem” is a common evolutionary challenge for nearly all terrestrial animals. The perceptual outcome of this process is the emergence of auditory objects that usually correspond to the individual physical sources. Indeed, many of the experimental approaches to understanding ASA involved stimuli which created perceptual objects that were in some way ambiguous and also looking at the illusions and/or confusions that such manipulation creates.

In the case of “the cocktail party problem”, the speech from each talker forms a specific stream and the problem becomes more about how we are able to select between each of the streams. In practical terms, the greater the differences between the talkers on some dimension (pitch, timbre, accent, rhythm, location etc.), the less likely we are to confuse the streams. That is, the greater stream variety, the more information unmasking we can expect.

This brings us to the key role of attention in understanding listening in a “cocktail party” scenario. Attention has been thought of as a type of filter that can be focused on a feature of interest, allowing for an up-regulation of the processing of information within that filter with a potential down-regulation of information outside the filter. A physical difference in some aspect of the auditory stream provides the hook onto which the listener can focus their attention. In recognizing the critical role that attention plays in understanding what is happening in a cocktail party scenario, it does move the discussion from “hearing” to “listening” and closer to Cherry’s goals of understanding the “acts of recognition and discrimination” that underlie the understanding of speech.


Auditory Attention

The neuroscience of auditory attention is in its infancy compared what we know about visual attention, although some tentative generalizations can be made:

Attention is a process of biased competition. The moment to moment focus of attention is dependent on competition between (1) top-down, voluntary or endogenous attentional control and (2) bottom-up, saliency driven or exogenous attention. The cognitive capacity to focus attention plays a key role in the sustained attention necessary to process the stream of information from a particular talker. There is evidence that we listen to only one auditory object at a time and selective attention is critical in enabling this. The exogenous competition introduced by concurrent sounds, particularly other talkers (the distractors) means more cognitive effort is required to sustain attention on a particular target of interest. The implication for an ageing population is that any reduction in cognitive capacity to sustain attention will increase the difficulty of understanding the stream of information from a single talker in the presence of other talkers.

Selective attention works at the level of perceptual objects as opposed to a particular physical dimension such as loudness or pitch. That is, attention focuses on the voice or the location of a particular talker (or both simultaneously – see below). While the attentional hook might be a difference on a particular perceptual dimension, the sum total of characteristics that make up the perceptual object are what becomes enhanced. Models of attention suggest that the competition for attention is played out in working memory and the players are the sensory objects contained in working memory at any particular point in time. Indeed, our conscious perception of the world relies on this process.

What this means, is when auditory objects are not well defined then the application of selective attention can be degraded. There are a number of circumstances where this can happen. For instance, when the stimuli themselves are ambiguous and don’t possess the relevant acoustical elements to support good grouping and streaming. Alternatively, the stimuli themselves may possess the necessary physical characteristics; however, poor encoding at the sensory epithelia and/or degraded neural transmission of the perceptual signal can result in a reduced fidelity or absence of the encoded features necessary for grouping or streaming. Implications for hearing impairment are that degradation of sensory encoding, such as that produced by broader auditory filters (critical bands) or poor temporal resolution, will weaken object formation and make the task of selective attention that much harder.

Attention acts as both a gain control and a gate. There is a growing body of evidence that indicates attention modulates the activity of neurones in the auditory system, not only at a cortical level but even earlier in the signal chain, possibly even at the level of the hair cells of the cochlea. In a number of recent and ground-breaking experiments, this process of up-regulation of the attended talker and down-regulation of the maskers has been convincingly demonstrated in the auditory cortex of people dynamically switching their attention between competing talkers (Mesgarani & Chang, 2012; Ding & Simon, 2013). Importantly, the strength of the selective cortical representation of the “attended-to” talker correlated with the perceptual performance of the listener in understanding the targeted talker over the competing talker.

The auditory system engages two different attentional system – one focused on the spatial location of a source and one focused on non-spatial characteristics of the source – which have two different cortical control systems. In a 2013 study, Adrian “KC” Lee and colleagues (Lee et al, 2013) had listeners change their attentional focus while imaging the brain. They found that the left frontal eye fields (FEF) became active before the onset of a stimulus when subjects were asked to attend to the location of a to-be-heard sound. This is part of the so-called dorsal attention pathway thought to generally support goal-directed attention. On the other hand, when asked to attend to a non-spatial attribute of the stimulus such as the pitch, a different pattern of pre-stimulus activation was observed in the left posterior central sulcus, an area also associated with auditory pitch categorization. This suggests that for the hearing impaired, a loss of the ability to localize the source of a sound disables or degrades a significant component of the auditory attention system resulting in an increased reliance on the non-spatial attention system.

Returning to Colin Cherry’s paper, it appears that we have — to paraphrase T.S. Eliot —“arrived where we started and know the place for the first time.”

So much of what Cherry discussed in his seminal paper is where we now find our neuroscientific focus including: the statistics of language in terms of its phonetic and semantic characteristics; the focus of attention and how that is mediated by spatial location and/or vocal or other characteristics; the transitional probabilities of what is being said and so on. The difference now is that we have both the technical and analytical tools to get a handle on how these processes are represented in the brain. With an increasing understanding of the functional plasticity of the brain, we are at a point now where we are making advances in the understanding of human perception and cognition that will have significant ramifications for how we intervene, support and rehabilitate many of the disorders that manifest as hearing impairment.

Further Reading

Cherry, E.C. (1953). “Some experiments on the recognition of speech with one and with two ears” J Acoust Soc Am, 25:975

Bronkhorst, A. (2000). “The cocktail party phenomenon: A review of research on speech intelligibility in multiple-talker conditions” in Acustica 86:117-128.

Lee, A. K. C., et al. (2012). “Auditory selective attention reveals preparatory activity in different cortical regions for selection based on source location and source pitch.” Frontiers in Neuroscience 6: 190-190.

Mesgarani, N. and Chang, E. F. (2012). “Selective cortical representation of attended speaker in multi-talker speech perception.” Nature 485: 233-236.

Ding, N. and Simon, J. Z. (2012). “Emergence of neural encoding of auditory objects while listening to competing speakers.” Proceedings of the National Academy of Sciences of the United States of America 109: 11854-9.


Does hearing aid use slow cognitive decline?

Deal, J., Sharrett, A., Albert, M., Coresh, J., Mosley, T., Knopman, D., Wruck, L. & Lin, F. (2015). Hearing impairment and cognitive decline: A pilot study conducted within the Atherosclerosis Risk in Communities Neurocognitive Study. American Journal of Epidemiology 181 (9), 680-690.

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

Recent evidence has suggested that cognitive decline and hearing impairment may have more of a connection beyond simple co-occurrence in the older population. Certainly, as individuals age, they become more likely to exhibit reduced cognitive function and also more likely to have hearing loss. It has been proposed that hearing loss may be correlated with temporal lobe and whole brain atrophy (Lin & Albert, 2014; Peelle, et al., 2011; Lin et al., 2014).  Whether the two conditions are related to a shared underlying cause is not known, but a number of studies have indicated that hearing loss may put older individuals at higher risk of cognitive decline (Lin, 2011; Lin et al., 2011; Lin, et al., 2013). The effect of hearing loss on cognition may be mediated by social isolation and loneliness or increased listening effort required to process speech via an impaired peripheral auditory system (McCoy, et al., 2005; Tun, et al., 2009). Conversely, cognition affects every-day communication and recent research has shown that hearing aid users with reduced cognitive capacity may have poorer speech recognition ability in noise, be more susceptible to the effects of distortion and noise and may also take a longer time to adapt to new hearing aids (Lunner, 2003; Lunner et al., 2009; Ng et al., 2014)

The work of Deal and colleagues aimed to determine whether older individuals with hearing loss show poorer cognitive performance and experience a more rapid rate of cognitive decline than those with normal hearing. Subjects were recruited from a population originally recruited in 1987-1989 for a longitudinal study called Atherosclerosis Risk in Communities (ARIC). Of the 15,792 ARIC subjects, 253 participated in this study on cognition and hearing, with a mean age of 76.9 years. Approximately 39% of the subjects were men, 61% were women.  At the 2013 session, 48% of the total participants reported ever smoking, 34% had diabetes and 71.9% had hypertension.  About 60% of the subjects had fewer than 12 years of education and 40% had more than 12 years of education.

The ARIC subjects completed a battery of neuropsychological tests on in three domains – memory, language and processing speed/attention – in 1990-1992 and again in 1996-1998.  Memory was tested with the Delayed Word Recall Test (DWRT; Knopman et al., 1989), the Incidental Learning Test (Kaplan et al., 1991) and the Logical Memory Tests I and II (Wechsler, 1945). Language was examined using the Word Fluency Test (Benton et al., 1994), Animals Naming Test (Goodglass & Kaplan, 1983) and the Boston Naming Test (Saxton et al., 2000). Processing speed and attention were assessed with the Digit Symbol Substitution and Digit Span Backwards Tests (Wechsler, 1981) and Trail Making Tests I and II (Spreen & Strauss, 1991; Reitan, 1958). For the purpose of the present study, these neuropsychological tests were administered again in 2013.

Pure tone air conduction thresholds were obtained for all 2013participants and they were categorized according to degree of loss indicated by the pure tone average (PTA) in the better ear: normal (lower than 25dB), mild (26-40dB), moderate/severe (greater than 40dB).  Only 5 individuals had PTAs greater than 70dB, so these individuals were included in the moderate/severe group. Of the total population, 34% had moderate/severe hearing loss, 37% had mild hearing loss and 29% had normal hearing. Hearing aid users made up approximately 20% of the total subject population. Hearing aid use was loosely defined as the self-reported use of a hearing aid in either or both ears during the month prior to the experimental session.  The duration of hearing aid use ranged from less than 1 year to 48 years, with most aided participants reporting hearing aid use for a period of 3 to 7 years.

All of the groups showed a decline in cognitive performance over the 20 years of the study, but the hearing loss groups declined faster than the normal hearing group. The subjects with moderate/severe hearing loss were slightly older and slightly more likely to be male and to have hypertension. However, after correcting for these variables, the subjects with moderate/severe hearing loss still declined significantly faster than the normal hearing group.

Approximately 51% of the subjects with moderate/severe hearing loss wore hearing aids.  The individuals who did not wear hearing aids had significantly poorer performance on the cognitive tests and demonstrated a significantly faster rate of decline compared to those in the moderate/severe group who did wear hearing aids. The rate of 20-year memory decline for the unaided individuals in this group was twice the average rate of decline reported in national studies of cognitive change in older adults (Salthouse, 2010; Hayden et al., 2011).  In comparison, the hearing aid users in this study with moderate/severe hearing loss showed a rate of cognitive decline that was only slightly higher than the rate for subjects with normal hearing.

The authors point out that because hearing was not assessed at earlier experimental sessions, they cannot rule out the possibility that cognitive decline had a causative effect on the measured hearing loss. However, this is unlikely because they corrected for co-occurring diseases and conditions in their analysis. Furthermore, conditions affecting cognition are not known to have any effect on the peripheral auditory system and cognitive deficits were not expected to have influenced the validity of the audiometric test results.

Many have proposed that hearing loss may increase risk of cognitive decline, via increased social isolation, increased perceptual effort and changes in brain volume. Unaided hearing loss is known to increase the risk of social isolation, which in turn has been associated with increases in blood pressure and corticosteroid levels, which could in turn affect brain structure (Mick et al., 2014; Hawkley & Cacioppo, 2010). Similarly, several studies have indicated that hearing loss increased effortful listening, thereby increasing the cognitive demands required to process speech (Rabbitt, 1968; Tun et al., 2009; McCoy et al., 2005).

The outcomes of this study are in agreement with other reports in which hearing impaired individuals demonstrated poorer performance on cognitive tests and faster rates of cognitive decline (Lin, 2011; Lin et al., 2011; Lin, et al., 2013). Other reports also indicate a relationship between hearing loss and subsequent dementia over years of follow-up evaluations (Gallacher et al., 2012; Lin et al., 2011).  The current outcome that hearing aid use had a mitigating effect on cognitive performance and rate of decline is fascinating and supports the need for further investigation on the relationship between cognition and hearing loss.

Though this is an emerging area of study, the results reported here offer strong support for the proposal that the risk of cognitive decline by hearing loss may be reduced, at least partially, by the correction of peripheral hearing loss with hearing aids.  This underscores the importance of amplification for older individuals and clinicians should be prepared to counsel their patients that hearing aids are an effective way to improve communication, decrease social isolation and may slow or decrease the risk of cognitive decline. However, clinicians should be cautious not to suggest that hearing aids will prevent cognitive decline. Although the authors are careful not to claim a causal relationship between hearing loss and cognitive decline, it is clear that the two conditions are related and because hearing loss is easily treatable it may be one of the few ways in which individuals can proactively manage their risk of cognitive decline.


Benton, A., Hamsher, K., & Sivan, A. (1994). Multilingual Aphasia Examination 3rd ed. Iowa City, IA: AJA Associates.

Deal, J., Sharrett, A., Albert, M., Coresh, J., Mosley, T., Knopman, D., Wruck, L. & Lin, F. (2015). Hearing impairment and cognitive decline: A pilot study conducted within the Atherosclerosis Risk in Communities Neurocognitive Study. American Journal of Epidemiology 181 (9), 680-690.

Gallacher, J., Ilubaera, V. & Ben-Shlomo, Y. (2012). Auditory threshold, phonologic demand and incident dementia. Neurology 79(15), 1583-1590.

Goodglass, H. & Kaplan, E. (1983). The Assessment of Aphasia and Related Disorders 2nd ed. Philadelphia, PA: Lea and Febiger: 102, 31.

Hawkley, L. & Cacioppo, J. (2010).  Loneliness matters: a theoretical and empirical review of consequences and mechanisms. Annals of Behavioral Medicine 40(2), 218-227.

Hayden, K., Reed, B. & Manly, M. (2011). Cognitive decline in the elderly: an analysis of population heterogeneity. Age and Aging 40(6), 684-689.

Kaplan, E., Fein, D. & Morris, R. (1991). WAIS as a Neuropsychological Instrument. San Antonio, TX: The Psychological Corporation.

Knopman, D. & Ryberg, S. (1989). A verbal memory test with high predictive accuracy for dementia of the Alzheimer type. Archives of Neurology 46(2), 141-145.

Lin, F.  (2011). Hearing loss and cognition among older adults in the United States. The Journals of Gerontology A: Biological Sciences and Medical Sciences 66 (10), 1131-1136.

Lin, F. & Albert, M. (2014). Hearing loss and dementia – who is listening? Aging and Mental Health 18(6), 671-673.

Lin, F., Ferrucci, L. & Metter, E. (2011). Hearing loss and cognition in the Baltimore Longitudinal Study of Aging. Neuropsychology 25(6), 763-770.

Lin, F., Yaffe, K., & Xia, J. (2013). Hearing loss and cognitive decline in older adults. Journal of the American Medical Association Internal Medicine 173 (4), 293-299.

Lunner, T. (2003). Cognitive function in relation to hearing aid use. International Journal of Audiology 42, (Suppl. 1), S49-S58.

Lunner, T., Rudner, M. & Ronnberg, J. (2009). Cognition and hearing aids. Scandinavian Journal of Psychology 50, 395-403.

McCoy, S.L., Tun, P.A. & Cox, L.C. (2005). Hearing loss and perceptual effort: downstream effects on older adults’ memory for speech. Quarterly Journal of Experimental Psychology A, 58, 22-33.

Mick, P., Kawachi, I. & Lin, F. (2014). The association between hearing loss and social isolation in older adults. Otolaryngology Head Neck Surgery 150(3), 378-384.

Ng, E.H.N., Classon, E., Larsby, B., Arlinger, S., Lunner, T., Rudner, M., Ronnberg, J. (2014). Dynamic relation between working memory capacity and speech recognition in noise during the first six months of hearing aid use. Trends in Hearing 18, 1-10.

Peelle, J., Troiani, V. & Grossman, M. (2011). Hearing loss in older adults affects neural systems supporting speech comprehension. Journal of Neuroscience 31(35), 12638-12643.

Rabbitt, P. (1968). Channel-capacity, intelligibility and immediate memory. Quarterly Journal of Experimental Psychology 20(3), 241-248.

Reitan, R. (1958). Validity of the Trail Making Test as an indicator of organic brain damage. Perceptual and Motor Skills 8, 271-276.

Salthouse, T. (2010). Major Issues in Cognitive Aging. Vol. 49, New York, NY: Oxford University Press: 246.

Saxton, J., Rafcliff, G. & Munro, C. (2000).  Normative data on the Boston Naming Test and two equivalent 30-item short forms. Clinical Neuropsychology 14(4), 526-534.

Spreen, O. & Strauss, E. (1991). A Compendium of Neuropsychological Tests: Administration, Norms and Commentary. 2nd ed. New York, NY: Oxford University Press.

Tun, P., McCoy, S. & Wingfield, A. (2009). Aging, hearing acuity and the attentional costs of effortful listening. Psychology and Aging 24(3), 761-766.

Wechsler, D. (1945). A standardized memory scale for clinical use. Journal of Psychology 19(1), 87-95.

Wechsler, D. (1981). Wechsler Adult Intelligence Scale – Revised. New York, NY: The Psychological Corporation.

Listening is more effortful for new hearing aid wearers

Ng, E.H.N., Classon, E., Larsby, B., Arlinger, S., Lunner, T., Rudner, M., Ronnberg, J. (2014). Dynamic relation between working memory capacity and speech recognition in noise during the first six months of hearing aid use. Trends in Hearing 18, 1-10.

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

Numerous studies have illustrated the relationship between working memory, cognitive resources and speech perception and suggest that listeners with limited working memory or cognitive resources are more likely to struggle with speech recognition in noise (Gatehouse, et al., 2003; Lunner, 2003). Conversely, larger working memory capacity may allow more rapid and successful matching between speech inputs and stored lexical templates.  This concept is described by the Ease of Language Understanding (ELU) model, which proposes that cognitive processing demands vary according to the degradation of the speech signal in different environments (Ronnberg, 2003; Ronnberg et al., 2008). In quiet, favorable listening conditions, speech inputs are easily matched to stored representations and the processing is automatic. In difficult listening environments, more explicit processing is required to match inputs to stored representations. How efficiently this goal is achieved is dependent upon working memory capacity.

Using these concepts as underpinning, Ng and her colleagues proposed that working memory and cognitive processing may have more of an impact on speech recognition for new hearing aid users than for experienced hearing aid users. Hearing aids improve speech audibility and directional microphones and noise reduction can help preserve speech in adverse listening conditions, which should reduce the need for explicit working memory processing. However, if phonological representations stored in memory have been degraded by hearing loss over time, amplified speech perceived by new hearing aid users will not match their stored templates. Therefore, more explicit processing in working memory may be required to identify words. Over time, as the individual becomes acclimated to the amplified sound, stored templates may adapt and become more similar to their acoustic counterparts, reducing the working memory and cognitive load requirements for correct identification. Following this reasoning, Ng and her colleagues proposed that there would be a significant relationship between cognitive functioning and speech recognition in new, first-time hearing aid users but that the relationship would become weaker over time as stored speech representations based on amplified sound become more established.

To examine this hypothesis, 27 first-time hearing aid users were recruited from a pool of subjects at a Swedish university Audiology clinic. All had mild to moderately-severe sensorineural hearing loss and no previous experience with hearing aids. Nine of the subjects were fitted monaurally and 18 were fitted binaurally. Four participants had in-the-ear or canal instruments and 23 had behind-the-ear instruments. Most of the subjects became full-time hearing aid users and the rest were consistent, part-time users.

Approximately four months prior to being fitted with their hearing aids, subjects attended an experimental session at which they completed speech recognition in noise and cognitive testing. Four cognitive tests were administered: the Reading Span test, a physical matching task, a lexical decision making task and a rhyme judgment test. The Swedish version of the Reading Span test was used to assess working memory or listeners’ ability to process and store verbal information in a parallel task design (Ronnberg et al., 1989). After hearing a list of sentences, subjects were asked to recall either the first or final word of each sentence in the list.  The test was scored according to the total number of words correctly recalled. The physical matching test (Posner & Mitchell, 1967), which measured general processing speed, required participants to judge whether two examples of the same letter were visibly identical or different in physical shape (e.g., A-A vs. A-a). Scores were based on reaction time for correct trials. The lexical decision making task required subjects to judge whether a string of 3 letters presented on a screen was a real Swedish word. Scores were based on reaction time for correct trials. The rhyme judgment test required subjects to determine whether two words, presented on a screen, rhymed or not (Baddeley & Wilson, 1985). This test was intended to measure the quality of stored phonological representations and was scored based on percentage of correct judgments.

The speech recognition in noise test was conducted again at the hearing aid fitting appointment (0 months) and again at approximately 3 month intervals (3 months and 6 months). The investigators chose to evaluate speech recognition and its relationship to cognitive tests at these intervals based on previous reports suggesting that a familiarization period of 4-9 weeks was required to reduce cognitive load (Rudner et al., 2011).

The results of the speech recognition in noise test showed, not surprisingly, that aided SRT was significantly better than unaided SRT.  The change in SRT over time was also significant, in that the SRT measured at 6 months was significantly better than at 0 months. The 3 month SRT was not significantly different from the 0 month or 6 month tests.  Age and pure-tone-average (PTA) were significantly correlated with SRT at 0, 3 and 6 month tests. At 0 and 3 months, the cognitive measures of reading span, physical matching and lexical decision were all correlated with SRT. At 6 months, only the correlations between lexical decision and reading span were significant. These results indicate that the relationship between cognitive measures and speech recognition declined over the first 6 months of hearing aid use.  Regression analysis showed a similar pattern in that reading span and PTA were significant predictors of speech recognition at 0 months, but by 6 months, only PTA was a significant predictor.

The pattern of results in this study supports the authors’ proposal that for first-time hearing aid users, working memory and cognitive processing play a more important role in speech perception in noise immediately after fitting than they do after acclimatization. Their hypothesis that stored perceptual representations are altered by long-term hearing loss and are therefore mismatched with newly amplified speech inputs is supported by their clinical observations. First-time hearing aid users typically experience amplified speech as “tinny”, “metallic”, or in some way “artificial”.  For most new hearing aid users, this perception resolves within a few weeks or so, though others may require longer periods of use to become acclimated. As time goes on, new hearing aid users usually report that speech sounds more natural and the data presented here support the assertion that stored lexical representations, after becoming distorted from long-term hearing impairment, may be adapting based on consistently restored audibility of speech sounds.

The results of this study support the importance of cognitive functioning for speech perception in noise and suggest that new hearing aid users experience increased cognitive demands for understanding speech as compared to experienced hearing aid users. It follows that individuals who have limited working memory or impaired cognition may also experience longer acclimatization periods with their new hearing aids.

Clinicians are accustomed to counseling patients to wear their hearing aids consistently; for most of the day, every day.  The authors of this study did not examine the usage patterns of their subjects with reference to their hypothesis, but future studies should investigate the potential effects of limited hearing aid use on the relationship between cognition and speech recognition in noise. If full-time use results in a more rapidly waning relationship between these variables (indicating a more rapid decrease in cognitive load required for speech recognition) it would underscore the importance of consistent hearing aid use for new users, especially those with cognitive or working memory limitations.



Baddeley, A. & Wilson, B. (1985). Phonological coding and short term memory in patients without speech. Journal of Memory and Language 24(1), 490-502.

Gatehouse, S., Naylor, G., & Elberling, C. (2003). Benefits from hearing aids in relation to the interaction between the user and the environment. International Journal of Audiology 42 (Suppl. 1), S77-S85.

Hagerman, B. & Kinnefors, C. (1995). Efficient adaptive methods for measuring speech reception threshold in quiet and in noise. Scandinavian Audiology 24 (1), 71-77.

Lunner, T. (2003). Cognitive function in relation to hearing aid use. International Journal of Audiology 42, (Suppl. 1), S49-S58.

Lunner, T., Rudner, M. & Ronnberg, J. (2009). Cognition and hearing aids. Scandinavian Journal of Psychology 50, 395-403.

McCoy, S.L., Tun, P.A. & Cox, L.C. (2005). Hearing loss and perceptual effort: downstream effects on older adults’ memory for speech. Quarterly Journal of Experimental Psychology A, 58, 22-33.

Ng, E.H.N., Classon, E., Larsby, B., Arlinger, S., Lunner, T., Rudner, M., Ronnberg, J. (2014). Dynamic relation between working memory capacity and speech recognition in noise during the first six months of hearing aid use. Trends in Hearing 18, 1-10.

Posner, M. & Mitchell, R. (1967). Chronometric analysis of classification. Psychological Review 74(5), 392-409.

Ronnberg, J., Arlinger, S., Lyxell, B. & Kinnefors, C. (1989). Visual evoked potentials: Relation to adult speechreading and cognitive function. Journal of Speech and Hearing Research 32(4), 725-735.

Ronnberg, J. (2003). Cognition in the hearing impaired and deaf as a bridge between signal and dialogue: a framework and a model. International Journal of Audiology 42 (Suppl. 1), S68-S76.

Ronnberg, J., Rudner, M. & Foo, C. (2008). Cognition counts: A working memory system for ease of language understanding (ELU). International Journal of Audiology 47 (Suppl. 2), S99-S105.

Rudner, M., Ronnberg, J. & Lunner, T. (2011). Working memory supports listening in noise for persons with hearing impairment. Journal of the American Academy of Audiology 22, 156-167.


These factors lead to successful hearing aid use

Hickson, L., Meyer, C., Lovelock, K., Lampert, M. & Khan, A. (2014) . Factors associated with success with hearing aids in older adults. International Journal of Audiology 53, S18-S27.

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

There is a saying in real estate that the three most important factors determining property value are location, location, location.  A similar argument could be made for hearing aid fitting. Three of the most important factors in hearing aid success may be follow-up, follow-up, follow-up. Certainly, success cannot be expected without appropriate selection and verification, but thorough training, counseling and consultation after the fitting can have a huge impact on the comfort and perceived benefit of new hearing aids.

Hearing aid success can generally be defined as an outcome in which the patient wears the instruments regularly and reports benefit from them.  Knudsen et. al. (2010) reviewed several studies and a few factors emerged that were consistently related to success with hearing aids.  In general, the individuals most likely to do well were those who had positive attitudes about hearing aids prior to fitting and a greater degree of self-reported hearing difficulty (et al., 2010; Hickson et al., 1986, 1999; Cox et al., 2007).  In studies examining why people don’t use their hearing aids, the most commonly cited reasons were lack of perceived benefit and problems with the fit and comfort of the aids (McCormack & Fortnum, 2013).

A better understanding of how these factors interact will help clinicians guide their patients to become consistent, successful hearing aid users. Defining success as a combination of regular use and self-reported benefit, Hickson and her colleagues examined the association between audiological and non-audiological factors and successful hearing aid outcomes.  The audiological factors they studied were duration and degree of hearing loss, presence of tinnitus, style of hearing aid and insertion gain with hearing aids. Non-audiological factors were grouped into four categories: attitudes and cues to action, demographic characteristics, psychological factors and age-related factors.

One hundred and sixty adults over age 60 participated in the study, with a mean age of 73 years. All had hearing loss greater than 25dB HL and fewer than 2 years of experience with hearing aids. Of the 160 subjects, 75 were classified as unsuccessful hearing aid users and 85 were classified as successful users.  Unsuccessful users were defined as those who reported little or no use and/or benefit with their hearing aids.

Subjects participated in one session at which they completed audiological testing, real-ear measurements, cognitive testing, a case history and a general health questionnaire. Two weeks prior to the session they were given 8 self-report questionnaires to complete at home:

1.              Hearing Handicap Questionnaire (HAQ; Gatehouse & Noble, 2004)

2.              Self-Assessment of Communication (SAC; Schow & Nerbonne, 1982)

3.              Attitude to Hearing Aids Questionnaire (VanDenBrink, 1995)

4.              Measure of Audiologic Rehabilitation – Self-Efficacy for Hearing Aids (MARS-HA; West & Smith, 2007)

5.              Coping Strategy Indicator (CSI; Amirkhan, 1990)

6.              Locus of Control scales (Levenson, 1981; Presson et al., 1997)

7.              Auditory Lifestyle & Demand Questionnaire (ALDQ; Gatehouse et al., 1999)

8.              Social Activities Survey (SOCACT; Cruice et al., 2001)

Data analysis revealed that four factors were significantly related to hearing aid success. In order from strongest to weakest associations, these factors were positive support from others, hearing difficulties in everyday life, insertion gain (for 55dB input level) and the interaction between attitude toward hearing aids and advanced handling (e.g., identification of different components of a hearing aid and how confident the user was in manipulating the aids). Overall, hearing aid users were more likely to achieve success if they had support from friends and family, perceived greater difficulty hearing, their insertion gain matched target, they possessed a positive attitude about hearing aids and had greater confidence in their ability to use the hearing aids. Conversely, almost 25% of unsuccessful hearing aid users reported that their hearing aids didn’t help them hear better or were too noisy.  Less common responses from unsuccessful users were that they didn’t need hearing aids, had difficulty manipulating or adjusting to the aids or obtained no benefit from the aids.

The factor most strongly related to success was the support of significant others, as indicated by statements such as “The people around me think it was wise to obtain a hearing aid” or “The people around me think I hear better with my hearing aid”: underscoring the importance of involving spouses, family members or friends in the hearing aid fitting process, so that their observations and comments can be considered and discussed at the initial consultation, fitting and follow-up appointments.  Having support at the initial consultation also helps the potential hearing aid user realize their need for help. As many clinicians know, the hearing-impaired individual is often less aware of their communication difficulties than their close associates are. Friends and family members who support the need for and the observed success with hearing aids can be influential in the patient’s own motivation and perceived benefit.

Detailed discussion of test results and administration of hearing handicap questionnaires can also motivate potential hearing aid users to proceed with an evaluation and fitting. It is common for people with hearing loss to think that other people mumble or that the source of communication difficulty is external rather than related to their hearing loss. Seeing the configuration of the hearing loss, perhaps in the context of speech and familiar sounds can help them understand what they are missing. Hearing handicap questionnaires illuminate some of the familiar challenges that hearing impaired individuals experience. Clinicians are familiar with the scenario in which hearing impaired patients feel they don’t really have hearing loss because “they can still hear, they just don’t understand”.  Simply explaining the audiogram illustrates how their hearing differs from normal hearing can help them understand the implications of the loss and the need for amplification.

A positive attitude about hearing aids was related to increased use and perceived benefit. This is a harder goal to achieve, but should be addressed at the initial consultation and consistently thereafter. Every clinician has met patients who know a friend or neighbor who doesn’t like their hearing aids and it can be challenging to persuade skeptics that there is reason to expect improvement from hearing aids. It may be helpful to have testimonials from satisfied patients available on the clinic website or in written materials in the office.  I also find it helpful to simply assure people that with the quality of today’s hearing aid technology, there are very few problems that can’t be solved with thorough assessment, training and follow-up.

The issue of hearing aid stigma and negative associations is not an easy problem to overcome, but it has improved over time and will likely continue to improve. Clinicians should encourage successful hearing aid users to share their positive experiences with friends, family and co-workers, to act as advocates for the benefits of hearing aids. Similarly, friends and family of those who have experienced hearing aid success should spread the word whenever possible. The most powerful endorsements come from people who have experienced better communication with their own hearing aids. As a clinician, patients often tell me that hearing aids make their lives easier. Others tell me that they can’t imagine trying to function without their hearing aids. The more these hearing aid success stories circulate among the general public, the more motivated hearing-impaired individuals will be to pursue hearing aids for themselves.

Individuals who had greater confidence in their ability to use the hearing aids were more likely to be successful, regular users. This is another factor that can be addressed through training, guided practice, and clearly written materials. Many new patients are overwhelmed by the extent of information is covered during the hearing aid fitting; informing the patient that you have a plan for training during later visits will ease any anxiety with retaining all of the information shared at the time of the first fitting. Including friends or family members at the fitting also contributes to success as these individuals may contribute to use and care during the adjustment period.

The responses of the participants in this study illuminate many of the factors that affect hearing aid success. With an understanding of these factors and thorough follow-up care, clinicians can avoid or solve most problems and most hearing aid users should perceive benefit from their instruments. Because hearing aids are medical devices, they require comprehensive care from trained professionals. Time spent on fine tuning, training and counseling during the first few weeks after the fitting can have long-term impact on usage patterns, satisfaction and perceived benefit. Clinicians and experienced hearing aid users should share stories of positive outcomes to counterbalance negative perceptions so that new and potential users can embark upon hearing aid fittings with expectations of success.



Amirkhan, J. (1990). A factor analystically derived measure of coping: The coping strategy indicator. Journal of Personality and Social Psychology 59, 1066-1074.

Champion, V. & Skinner, C. (2008). The health belief model. In: K. Glanz, B.K. Rimer, K. Viswanath (eds.) Health Behavior and Health Education: Theory, Research and Practice. San Francisco: Jossey-Bass.

Cox, R. & Alexander, G. (1995). The abbreviated profile of hearing aid benefit. Ear and Hearing 16, 176-186.

Cox, R., Alexander, G. & Gray, G. (2007). Personality, hearing problems, and amplification characteristics: Controbituions to self-report hearing aid outcomes. Ear and Hearing 28, 141-162.

Cruice, M. (2001). Communication and quality of life in older people with aphasia and healthy older people. Ph.D. Dissertation, The University of Queensland, Australia.

Gatehouse, S., Elberling, C. & Naylor, G. (1999). Aspects of auditory ecology and psychoacoustic function as determinants of benefits from and candidature for non-linear processing in hearing aids. In: Kolding (ed.) 18th Danavox Synposium, 221-233.

Gatehouse, S. & Noble, W. (2004). The speech, spatial and qualities of hearing scale (SSQ). International Journal of Audiology 43, 85-99.

Glanz, K., Rimer, B. &National Cancer Institute – U.S. (2005). Theory at a glance a guide for health promotion practice: U.S. Department of Health and Human Services National Cancer Institute.

Hickson, L., Hamilton, L. & Orange, S. (1986). Factors associated with hearing aid use. Australian Journal of Audiology 8, 37-41.

Hickson, L. Timm, M., Worrall, L. & Bishop, K. (1999). Hearing aid fitting: Outcomes for older adults. Australian Journal of Audiology 21, 9-21.

Hickson, L., Meyer, C., Lovelock, K., Lampert, M. & Khan, A. (2014) . Factors associated with success with hearing aids in older adults. International Journal of Audiology 53, S18-S27.

Knudsen, L., Oberg, M., Nielsen, C., Naylor, G.  & Kramer, S. (2010).  Factors influencing help seeking, hearing aid uptake, hearing aid use and satisfaction with hearing aids: A review of the literature. Trends in Amplification 14, 127-154.

Levenson, H. (1981). Differentiating among internality, powerful others, and chance. In: H.M. Lefcourt (ed.) Research with the Locus of Control Construct: Assessment Methods. New York: Academic Press. pp. 15-63.

McCormack, A. & Fortnum, H. (2013).  Why do people fitted with hearing aids not wear them? International Journal of Audiology 52, 360-368.

Metselaar, M., Maat, B., Krijnen, P., Verschure, H. & Dreschler, W. (2008). Self-reported disability and handicap after hearing aid fitting and benefit of hearing aids: Comparison of fitting procedures, degree of hearing loss, experience with hearing aids and unilateral and bilateral fittings. European Archives of Otorhinolarygology, open access.

Presson, P., Clark, S. & Benassi, V. (1997). The Levenson locus of control scales: Confirmatory factor analyses and evaluation. Journal of Social Behavior and Personality 25, 93-104.

Stark, P. & Hickson, L. (2004). Outcomes of hearing aid fitting for older people with hearing impairment and their significant others. International Journal of Audiology 43, 390-398.

Schow, R. & Nerbonne, M. (1982). Communication screening profile: Use with elderly clients. Ear and Hearing 3, 135-147.

VanDenBrink, R. (1995). Attitude and illness behavior in hearing impaired elderly. Ph.D. dissertation, University of Groningen.

Ventry, I. & Weinstein, B. (1982). The hearing handicap inventory for the elderly: a new tool. Ear and Hearing 3, 128-134.

West, R. & Smith, S. (2007). Development of a hearing aid self-efficacy questionnaire. International Journal of Audiology 46, 759-771.

Cognitive Benefits of Digital Noise Reduction

Desjardins, J. & Doherty, K. (2014). The effect of hearing aid noise reduction on listening effort in hearing-impaired adults. Ear and Hearing 35 (6), 600-610.

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

Understanding speech in noise can be a challenge for anyone with hearing loss, but it is especially difficult for older listeners (Plomp, 1978; Duquesnoy, 1983; Dubno et al., 1984; Helfer & Freyman, 2008).  Older individuals also experience increased listening effort in noisy conditions as compared to younger listeners (Desjardins & Doherty, 2013).  Listening effort is often measured in a dual-task paradigm during which subjects perform a second task while simultaneously repeating speech in noise. Increased listening effort is reflected by the allocation of cognitive resources away from the secondary task, resulting in poorer performance. When this effect is considered with reference to everyday situations, increased listening effort could have repercussions for elderly individuals beyond communication, affecting their ability to multi-task which could have associated safety concerns.  Listening effort could also affect the risk of social isolation as elderly, hearing-impaired individuals may feel reluctant to exert the energy and effort required to interact with others in group situations.

In a review of the literature on speech recognition and cognitive abilities, Akeroyd (2008) found that hearing was the primary predictor of speech recognition performance, but working memory capacity was the second best predictor. Because speech perception is affected by peripheral auditory processing as well as cognitive functions like working memory and speed of processing, the measurement of speech recognition scores alone may not be sufficient to evaluate the potential benefits of noise reduction in hearing aids. To this end, some studies have examined the effects of noise reduction on listening effort and the allocation of cognitive resources. Ng et al. (2013) found that noise reduction improved working memory function for some subjects and Sarampalis et al. (2009) found that the use of noise reduction reduced listening effort, resulting in quicker visual reaction times and better word recall on secondary tasks.

The current study investigated the relationships among noise reduction, listening effort and speech recognition in middle-aged to older adults with hearing loss. A dual-task paradigm, with speech recognition in noise as the primary task and visual tracking as the secondary task, was used to evaluate listening effort. Working memory tends to decline with advancing age (Salthouse, 1994), as does the speed of perceptual processing (Salthouse, 1985; Wingfield et al., 1985), so measures of working memory and processing speed were also examined. Twelve subjects participated in the study, ranging in age from 50 to 74 years.  All had symmetrical, sensorineural hearing loss and were experienced hearing aid users. For the purpose of the study, subjects were fitted with behind-the-ear hearing aids and disposable canal earmolds, fitted to DSL v5 targets (Scollie et al., 2005). Hearing aids were programmed with two memories: in the first, all special signal processing features were disabled and in the second, noise reduction (Voice iQ2) was set to maximum.

Speech recognition in noise was examined using the R-SPIN Test (Bilger et al., 1984), which consists of eight lists of 50 sentences each. Half of the sentences on each list are high context and half are low-context.  The sentences were presented in two-talker babble (TTB), composed of two female talkers reciting nonsense sentences. TTB has significantly affected listening effort for older subjects in previous research (Desjardins & Doherty, 2013).  Prior to the dual task procedure, subjects performed a sentence recognition test in noise to determine the SNR required to achieve 76% performance and 50% performance.  Not surprisingly, subjects required more favorable SNRs to achieve 76% performance, with average SNRs of 4.4dB for 76% performance and 1.8dB for 50% performance. The individual SNRs were used later to derive four listening conditions for the dual task procedure:

1.              Moderate listening condition (more favorable SNR) with noise reduction

2.              Moderate listening condition without noise reduction

3.              Difficult listening condition (less favorable SNR) with noise reduction

4.              Difficult listening condition without noise reduction

Following the sentence blocks in the dual-task procedure, listeners were asked to rate their ease of listening. They were asked to rate how easy it was to listen to the sentences on a scale from 0-100, with 0 being “very, very difficult” and 100 being “very, very easy” (Geller & Margolis, 1984; Feuerstein, 1992).

Results for the R-SPIN speech recognition task revealed significantly higher scores in the moderate listening condition compared to the difficult listening condition. There was no main effect of noise reduction or any interaction between listening condition and noise reduction, indicating that noise reduction did not have a significant impact on speech recognition ability in noise. Scores for high-context sentences were significantly better than for low-context sentences, indicating that listeners used context to help them understand the sentences better. There was no interaction between context and listening condition.

Listening effort was measured with the dual-tasks of speech recognition in noise and visual tracking. Poorer performance on the visual tracking task indicated higher listening effort or the allocation of more cognitive resources toward speech recognition. Sentence recognition scores were not significantly different based on the four test conditions, but listening effort was affected by test condition.  Without noise reduction, listening effort was significantly higher for the difficult listening condition than for the moderate condition. With noise reduction, there was no significant difference in listening effort between the moderate and difficult listening conditions. In other words, noise reduction reduced listening effort in the difficult listening condition, but did not have a significant effect in the moderate condition. Perhaps surprisingly, listening effort did not vary depending on sentence context. Secondary task performance remained consistent during high and low context sentences, despite the fact that speech recognition scores were significantly better for high context sentences.

Self-perceived ease of listening ratings showed that subjects rated the moderate listening condition as significantly easier than the difficult condition. There was no significant difference in their ease of listening ratings based on noise reduction, nor was there an interaction between noise reduction and listening condition. These results indicated that the subjects did not feel that noise reduction made listening easier, despite the fact that their measured listening effort was significantly reduced with noise reduction, at least in the difficult listening condition.

There were no significant effects between working memory or processing speed on listening effort, with or without noise reduction. There was, however, a significant trend for subjects with faster processing speeds to show reduced listening effort with noise reduction activated, but this occurred only for the difficult listening condition.

The results of this study are in agreement with prior reports, in that noise reduction did not significantly improve significant speech recognition scores in noise. Noise reduction did, however, reduce listening effort in the difficult listening condition with the poorer signal-to-noise ratio. This is in agreement with Sarampalis et al. (2009) who reported listening effort reduction only in the more difficult listening condition of -6dB SNR.  Though working memory and processing speed did not significantly affect listening effort in this study, there was a trend showing subjects with faster processing were able to derive more benefit from noise reduction in the difficult listening situation. Prior studies have shown relationships between working memory, processing speed and listening effort, so this is an area that requires further study.

Desjardins and Doherty’s study provides further evidence that tests of listening effort may be a reasonable tool for evaluating the benefits of noise reduction. The authors point out that the ability of noise reduction to reduce listening effort in noisy conditions could have implications for multi-tasking, which could in turn affect safety in some scenarios.  For instance, an older hearing-impaired person, driving a car while talking to a passenger, may unwittingly divert cognitive resources toward the task of understanding conversation, thus potentially reducing their ability to respond to other stimuli related to driving. If noise reduction helps reduce the cognitive demand required for speech recognition in this scenario, in theory there would be more cognitive resources available for driving and attending to surrounding activity.

Concerns like this are particularly important when considering hearing aid fittings for older patients.  Hearing loss increases with advancing age, while working memory and processing speed are known to decline with age.  Therefore, older individuals are more likely to be challenged by the cognitive demands of multi-tasking while at the same time facing additional obstacles like poorer hearing and speech recognition ability and impaired vision.  Though the maximum noise reduction settings used in this study are not usually used in clinical fittings, it may be appropriate to use higher noise reduction settings for older hearing aid users, especially those with known cognitive processing deficits. Directional microphones and automatic noise programs with low-frequency gain reduction may provide additional benefit.  In counseling sessions, clinicians should discuss potential multi-tasking difficulties and the need to reduce distractions in order to optimize speech recognition ability. The importance of properly fitted hearing instruments to facilitate speech communication during simultaneous tasks should also be emphasized, especially at early appointments when hearing loss is diagnosed and hearing aids are being considered. This is particularly relevant to situations in which older, hearing-impaired listeners may be executing other tasks like driving, walking on stairs or through parking lots or streets, in which safety is a concern.

Social isolation is a concern for older adults with hearing loss. The National Council on Aging ( reports that hearing loss can reduce participation in social activities, reduce self-confidence, cause depression and strain relationships with family and friends. Hearing loss is also known to increase mental fatigue, making hearing-impaired listeners feel “exhausted” and fatigued from conversational interaction (Hornsby, 2013). Older adults who treat their hearing loss with hearing aids are less likely to experience these negative effects. It is plausible to assert that factors affecting listening effort could also affect the risk of social isolation, as the increased effort and fatigue required in group interactions could be too daunting for some individuals.  The beneficial effect of noise reduction on listening effort is encouraging and should be considered for hearing aid fittings with older adults at risk of social isolation and depression.



Akeroyd, M. (2008). Are individual differences in speech reception related to individual differences in cognitive ability? A survey of twenty experimental studies with normal and hearing-impaired adults. International Journal of Audiology 47 (Suppl 2), S53-S71.

Bilger, R., Nuetzel, M., Rabinowitz, W. & Rzeczkowski, C. (1984). Standardization of a test of speech perception in noise. Speech and Hearing Research 27, 32-48.

Desjardins, J. & Doherty, K. (2013). Age-related changes in listening effort for various types of masker noises. Ear and Hearing 34, 261-272.

Desjardins, J. & Doherty, K. (2014). The effect of hearing aid noise reduction on listening effort in hearing-impaired adults. Ear and Hearing 35 (6), 600-610.

Dubno, J., Dirks, D. & Morgan, D. (1984). Effects of age and mild hearing loss on speech recognition in noise. Journal of the Acoustical Society of America 76, 87-96.

Duquesnoy, J. (1983). The intelligibility of sentences in quiet and noise in aged listeners. Journal of the Acoustical Society of America 74, 1136-1144.

Feuerstein, J. (1992). Monaural versus binaural hearing: Ease of listening, word recognition and attentional effort. Ear and Hearing 13, 80-86.

Geller, D. & Margolis, R. (1984). Magnitude estimation of loudness I: Application to hearing aid selection. Journal of Speech and Hearing Research 27, 20-27.

Helfer, K. & Freyman, R. (2008).  Aging and speech on speech masking. Ear and Hearing 29, 87-98.

Hornsby, B. (2013). The effects of hearing aid use on listening effort and mental fatigue associated with sustained speech processing demands. Ear and Hearing 34(5), 523-534.

Ng, E., Rudner, M. & Lunner, T. (2013). Effects of noise and working memory capacity on memory processing of speech for hearing aid users. International Journal of Audiology 52, 433-441.

Plomp, R. (1978). Auditory handicap of hearing impairment and the limited benefit of hearing aids. Journal of the Acoustical Society of America 68, 1616-1621.

Salthouse, T. (1994). The aging of working memory. Neuropsychology 8(4), 535-543.

Salthouse, T. (1985). A Theory of Cognitive Aging. New York, NY: North-Holland.

Sarampalis, A., Kalluri, S. & Edwards, B. (2009). Objective measures of listening effort: Effects of background noise and noise reduction. Journal of Speech, Language and Hearing Research 52, 1230-1240.

Scollie, S., Seewald, R. & Cornelisse, L. (2005).  The desired sensation level multistage input/output algorithm. Trends in Amplification 9, 159-197.

Wingfield, A., Poon, L. & Lombardi, L. (1985). Speed of processing in normal aging: Effects of speech rate, linguistic structure and processing time. Journal of Gerontology 40, 579-585.

Woods, W., Nooraei, N. & Galster, J. (2010). Real-world listening preference for an optimized digital noise reduction algorithm. Hearing Review 17(9), 38-43.


Hearing Aid Use is Becoming more Accepted

Rauterkus, E. & Palmer, C. (2014). The hearing aid effect in 2013. Journal of the American Academy of Audiology 25, 893-903.

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

Years ago, one of my patients quoted an aphorism, “Your hearing loss is more noticeable than your hearing aid”. At the time, it wasn’t always applicable. Hearing aids were larger and more visible in the ear and whistling feedback was harder to control, often resulting in embarrassment for the wearer. Today’s hearing aids are smaller, discreet, and comfortable, with effective feedback management. Still, there remains concern among many current and potential hearing aid users about a negative stigma associated with hearing aid use. Despite numerous potential benefits like improved communication ability and decreased stress, listening effort and fatigue, hearing impaired individuals quite frequently postpone or avoid amplification because they believe that wearing hearing aids will cause others to label them as old or less capable.

These negative associations have collectively been described as the hearing aid effect. Blood, Blood and Danhauer (1977) coined this term during a study in which 25 college students were shown photographs of 12 teenage males with and without hearing aids. The participants were asked to judge the boys in the photographs in terms of intelligence, achievement, personality, and appearance. On all attributes, the participants rated the boys in the photographs lower when they were wearing hearing aids versus when they were not.  Since their initial study, other reports showed a similar hearing aid effect (Blood, et al., 1978; Danhauer et al., 1980; Brimacombe & Danhauer, 1983).  Studies in which children rated other children showed strong and consistently negative judgments of individuals with hearing aids, on attributes such as intelligence and attractiveness (Dengerink & Porter, 1984; Silverman & Klees, 1989).  In contrast, some studies in which adults rated other adults did not find a hearing aid effect (Iler et al., 1982; Johnson & Danhauer, 1982; Mulac et al., 1983).

In general, a review of several reports from 1977 through 1985 indicates that hearing aid stigma at that time may have been changing slowly for the better.  A much more recent study (Clucas, et al., 2012) essentially reported the opposite of the typical hearing aid effect, in which 181 medical students rated photographs of a young male wearing a hearing aid as more worthy of respect than the photographs of the same young male without the hearing aid.

Through the years, hearing aids have become smaller and more discreet. Feedback reduction, automatic features and improved performance in noise have allowed hearing aid users to function better in everyday situations, calling less attention to their hearing loss. Ear level devices like earbuds for MP3 players and Bluetooth headsets have become widely used and visible. The Americans with Disabilities Act (ADA) has promoted equal participation of disabled individuals, including those with hearing loss. Public figures have openly discussed their hearing loss and hearing aid use, including Presidents Ronald Reagan and Bill Clinton and musicians like Pete Townsend and Neil Young. All of these factors have likely had a positive influence on public perception of hearing loss and hearing aids and may have reduced the negative stigma so prevalent in earlier reports.

The hearing aid effect, however, has not been re-examined in the same paradigm as the original report, so it is unknown how today’s perceptions might compare to the defining work. Rauterkus and Palmer’s study asked young adults to view and evaluate photographs of young men with and without hearing aids, in an effort to replicate the methods of earlier studies and derive an understanding of the hearing aid effect today.

Twenty-four graduate students in an MBA program were recruited to evaluate photographs of 5 young men, from age 15-17 years. The young men were photographed in 5 different configurations:

1. Wearing a standard BTE hearing aid coupled to a standard earmold and tubing

2. Wearing an open-fit BTE hearing aid coupled to a slim tube and dome

3. Wearing a CIC hearing aid that was not visible in the photo

4. Wearing earbud headphones as would be used with an MP3 device

5. Wearing a Bluetooth ear-level telephone headset

In the pictures, the young man was seated, reading a book. All photographs were taken from the rear left side of the young man, so that the left side and back of his head was visible and ear level devices could clearly be seen. All of the men in the pictures wore the same clothing so that differences would not affect the judgments of the participants.

No participant viewed the same man in more than one device configuration. Each photograph was shown on a page above a list of 8 attributes: attractive, young, successful, hard-working, trustworthy, intelligent, friendly, and educated. Participants were asked to rate the man in the picture on each attribute on a scale of 1-7.  These 8 attributes were selected because they were the most common attributes to have been rated in previous studies of the hearing aid effect.

The results showed no significant difference in ratings among the five young men in the photographs. Therefore, the data for all of the photographs were combined for data analysis.  There was a significant difference in the judgment of age between the photographs of the CIC user and the earbud user, with the CIC user being judged as significantly older than the earbud user.  Because the CIC instruments were not visible in the photographs, this difference is likely to be related to an association between younger people wearing earbuds to listen to music, as opposed to a negative judgment on the use of CIC instruments.  There was a significant difference in trustworthiness between the BTE user and Bluetooth device user, with the Bluetooth headset user deemed significantly less trustworthy. The authors’ findings clearly indicate that the participants did not have adverse reactions to the photographs of hearing aid users and did not demonstrate the hearing aid effect found in earlier studies.

The work of Rauterkus and Palmer suggests the hearing aid effect has diminished or even reversed. A welcome message for hearing care professionals, but we must also understand self-perception of hearing aid use. One could speculate that the commonality of ear-level devices and improvements in hearing aid size, design, performance and connectivity, have improved others perception of hearing aid use, resulting in the documented decrease of the hearing aid effect. It’s possible that the same social and technological factors are taking a similar toll on the negative self-perception of hearing aid use. Time will reveal the reality of these trends but smart research design helps us take a peak into the not-too-distant future.



Blood, G., Blood, I. & Danhauer, J. (1977). The hearing aid effect. Hearing Instruments 28, 12.

Blood, G., Blood, I. & Danhauer, J. (1978). Listeners’ impressions of normal-hearing and hearing-impaired children. Journal of Communication Disorders 11(6), 513-518.

Clucas, C., Karira, J. & Claire, L. (2012). Respect for a young male with and without a hearing aid: a reversal of the “hearing aid effect” in medical and non-medical students? International Journal of Audiology 51(10), 739-745.

Danhauer, J., Blood, G., Blood, I. & Gomez, N. (1980). Professional and lay observers’ impressions of preschoolers wearing hearing aids. Journal of Speech and Hearing Disorders 45(3), 415-422.

Dengerink, J. & Porter, J. (1984). Children’s attitudes towards peers wearing hearing aids. Language, Speech and Hearing Services in Schools 15, 205-209.

Iler, K., Danhauer, J. & Mulac, A. (1982).  Peer perceptions of geriatrics wearing hearing aids. Journal of Speech and Hearing Disorders 47(4), 433-438.

Johnson, C. & Danhauer, J. (1982). Attitudes towards severely hearing impaired geriatrics with and without hearing aids. Australian Journal of Audiology 4, 41-45.

Mulac, A., Danhauer, J. & Johnson, C. (1983). Young adults’ and peers’ attitudes towards elderly hearing aid wearers. Australian Journal of Audiology 5(2), 57-62.

Rauterkus, E. & Palmer, C. (2014). The hearing aid effect in 2013. Journal of the American Academy of Audiology 25, 893-903.

Silverman, F. & Klees, J. (1989).  Adolescents’ attitudes toward peers who wear visible hearing aids. Journal of Communication Disorders 22(2), 147-150.


Tinnitus Treatment through Sound Therapy

Henry, J., Frederick, M., Sell, S., Griest, S. & Abrams, H. (2014). Validation of a novel combination hearing aid and tinnitus therapy device. Ear and Hearing, e-published ahead of print, September 2014.

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


Most tinnitus management programs include a combination of counseling and sound therapy (Jastreboff, 1990; Jastreboff & Hazell, 2004). The goals of sound therapy for tinnitus treatment include achieving immediate relief as well as facilitating long-term habituation to the tinnitus (Vernon, 1988; Jastreboff & Hazell, 1998). Many sound generators or tinnitus masking devices offer only basic amplification features because they were intended primarily for tinnitus treatment through sound therapy. Current combination devices with advanced digital signal processing can provide improved audibility and comfort in addition to offering noise stimuli (i.e., sound therapy) for tinnitus management. Some estimates report that up to 90% of patients with tinnitus may benefit from amplification (Johnson, 1998; Schechter et al., 2002) so combination hearing aid / sound therapy devices are a valuable tool for tinnitus treatment and hearing loss remediation.

Most scientific studies support the potential benefit of hearing aids for tinnitus management. In a recent literature review, Shekhawat et al. (2013) reported that 17 of 18 research studies included the use of hearing aids in tinnitus treatment, but they highlighted the absence of randomized control trials with hearing aids that include sound therapy options. Parazzini et al. (2010) found that open-fit hearing aids were as effective as sound generator-only devices for use in tinnitus therapy, but they did not investigate combination devices. A primary goal of therapy is to reduce tinnitus awareness, so combination devices could be particularly beneficial because they employ masking stimuli as well as amplified environmental sound that may effectively draw attention away from the tinnitus. Though this proposition has merit, it has not yet been supported by scientific evidence. To this end, Henry and his colleagues prepared a randomized, controlled trial to investigate the benefit of hearing aids versus combination devices for tinnitus management.

Methods and Findings

Thirty participants with mild-to-moderately severe, symmetrical, sensorineural hearing loss were recruited for this study. All had clinically significant tinnitus according to Section A of the Tinnitus and Hearing Survey (Henry et al., 2010a, 2012). At the first session, subjects completed audiometry, medical and tinnitus screening and responded to 3 questionnaires: the Tinnitus Functional Index (TFI; Meikle et al., 2012), the Hearing Handicap Inventory for the Elderly (HHIE; Ventry & Weinstein, 1982) and a general tinnitus survey.  The TFI evaluates the negative impact of tinnitus and measures changes in tinnitus impact after treatment. TFI scores range from 0 to 100, with higher scores indicating more severe problems. Scores of at least 25 are considered significant and a 13-point difference from one test administration to another is considered a significant change. The HHIE evaluates the social and emotional effects of hearing loss and higher scores indicate more social and emotional impact. In this study, the HHIE was administered face-to-face, so a change of 19 points from one session to another was considered significant.

At the second session, participants were fitted with receiver-in-canal (RIC) hearing instruments that included the Multiflex adjustable sound-generator. Most subjects used manufacturer’s silicone domes, but two required custom fitted acrylic earmolds. Hearing aids were programmed to NAL-NL2 targets, verified with real-ear measures and adjusted according for sound quality and comfort. Following hearing aid fitting, all participants received general tinnitus counseling derived from Progressive Tinnitus Management: Counseling Guide (Henry et al., 2010b). Following counseling, the experimental group had the tinnitus sound therapy in their hearing aids adjusted according to their individual preferences to obtain immediate relief from their tinnitus, while the control group was prescribed hearing aids without the tinnitus sound therapy.  The default settings for the modulated noise stimuli were based on the individual’s audiogram, but could be adjusted in 16 channels and subjects could select a slow, medium or fast modulation rate.

Approximately 3 to 4 months after the initial fitting appointment, participants returned to complete an exit interview. They were asked about their general impressions of hearing aids and experience of tinnitus relief and completed the TFI and HHIE inventories two more times; once to indicate their responses when they were using their hearing aids and again to indicate their responses when they were not using their hearing aids.

TFI and HHIE scores were obtained 3 times each: at the initial visit prior to hearing aid fitting and at the 3-month session, for responses referring to experiences with the hearing aids and without. The initial average TFI score for the overall subject group was 58.3. At the 3-month session, the average TFI scores were 22.2 (with hearing aids) and 44.8 (without hearing aids). Though the change in score for the with-hearing-aid condition was much larger, the reductions in score were significant for both conditions. For the control group, the initial score was 60.5 and at 3 months the average scores were 27.6 (with hearing aids) and 44.3 (without hearing aids). Again, both reductions were significant, though the effect size for the with-hearing-aids condition was much larger. For the experimental group, the initial average score was 56.1. At the 3-month session, the average scores were 16.8 (with hearing aids) and 45.3 (without hearing aids). The score reduction was significant for the with-hearing-aids condition but not for the without-hearing-aids condition. These outcomes indicate that both groups, regardless of whether the sound therapy was used or not, responded better to TFI questions with respect to when they were wearing the hearing aids versus when they were not.  There was no significant difference between the TFI score reductions for the control versus experimental groups, though the experimental group had a larger score reduction by about 6 points.

At the 3-month session, the average HHIE scores were 23.6 (with hearing aids) and 47.5 (without hearing aids). The score reduction was significant for the with-hearing-aid condition but was not for the without-hearing-aid condition. For the control group, the initial score was 55.3 and at 3 months the average scores were 26.9 (with hearing aids) and 47.5 (without hearing aids). For the experimental group, the initial average HHIE score was 49.3 and at the 3-month session the average scores were 20 (with hearing aids) and 47.5 (without hearing aids). Again, for both the control and experimental groups, the score reduction was significant for the with-hearing-aid condition but was not for the without-hearing-aid condition.  There was a significant main effect between initial scores and 3-month scores for the with-hearing-aid condition but not for the without-hearing-aid condition. There was also a significant difference between the two conditions at the 3-month session; the with-hearing-aid scores were significantly lower than without-hearing-aid scores.


The findings of Henry and colleagues indicate that hearing aid use significantly reduces the negative effects of tinnitus, regardless of the presence or absence of sound therapy. Though there was not a significant difference between the control and experimental groups, the group using sound therapy had a larger reduction in TFI score than the group that used amplification alone. This difference approached but did not reach significance and the authors posit that perhaps with a larger subject group this difference would have been significant. HHIE results suggest that hearing aid benefit was not hampered by the use of sound therapy.

From a clinical perspective, several factors should be considered when fitting combination devices. The TFI is a good way to determine candidacy for combination devices, but a few key questions in the patient history can be helpful. We ask patients how they would rate their tinnitus and if it disrupts concentration, distracts or upsets them. It is also informative to ask if their tinnitus keeps them awake at night, though this concern is not directly addressed by the use of a combination device. Even a question about how motivated they are to seek treatment, such as the one employed in this study, can be indicative of candidacy.

After candidacy is established, there are still several factors to consider. Discussion of the individual’s tinnitus characteristics might help indicate which type of noise is most likely to be effective. Shaping the noise by frequency and intensity can help to achieve relief, while avoiding annoyance that may come with continued use. Clinicians should also discuss whether patients would like to use the noise constantly, in their main hearing aid program, or have it allocated to an alternate program for use as needed. We have found that most people prefer to have a “masking program” that they can use on occasion when their tinnitus is disruptive or annoying. For many people, this is in quiet conditions when they must concentrate on reading or quiet work. Follow-up consultations are critical to determine if the approach is working. Some individuals prefer to modify the characteristics of their sound therapy at later visits, either increasing or decreasing the intensity or shaping the frequency bands. The TFI is useful as a follow-up measure, but it should probably be administered after a few months of use, to make sure that programming adjustments are worked out before treatment efficacy is assessed.


Bock, K. & Abrams, H. (2013). An evaluation of the efficacy of a remotely driven auditory training program. Biennial NCRAR International Conference: Beyond the Audiology Clinic: Innovations and Possibilities of Connected Health. Portland, OR.

Coles, R. (2000). Medicolegal issues. In R.S. Tyler (Ed.). Tinnitus Handbook (pp. 399-417). San Diego: Singular Publishing Group.

Henry, J., Frederick, M., Sell, S., Griest, S. & Abrams, H. (2014). Validation of a novel combination hearing aid and tinnitus therapy device. Ear and Hearing, e-published ahead of print, September 2014.

Henry, J., Zaugg, T. & Myers, P. (2010a). Progressive Tinnitus Management: Clinical Handbook for Audiologists. San Diego, CA: Plural Publishing.

Henry, J., Zaugg, T. & Myers, P. (2010b).  Progressive Tinnitus Management: Counseling Guide. San Diego, CA: Plural Publishing.

Henry, J., Zaugg, T. & Myers, P. (2012). Pilot study to develop telehealth tinnitus management for persons with and without traumatic brain injury. Journal of Rehabilitation Research Developments 49, 1025-1042.

Hoffman, H. & Reed, G. (2004). Epidemiology of tinnitus. In J.B. Snow (Ed.). Tinnitus: Theory and Management (pp. 16-41). Lewiston, NY: BC Decker, Inc.

Humes, L., Wilson, D. & Barlow, N. (2002). Longitudinal changes in hearing aid satisfaction and usage in the elderly over a period of one or two years after hearing aid delivery. Ear and Hearing 23, 428-438.

Jastreboff, P. (1990). Phantom auditory perception (tinnitus): Mechanisms of generation and perception. Neuroscience Research 8, 221-254.

Jastreboff, P.  & Hazell, J. (1998). Treatment of tinnitus based on a neurophysiological model. In J.A. Vernon (Ed.). Tinnitus Treatment and Relief (pp. 201-217). Needham Heights: Allyn & Bacon.

Jastreboff, P. & Hazell, J. (2004). Tinnitus Retraining Therapy: Implementing the Neurophysiological Model. Cambridge University Press.

Johnson, R. (1998). The masking of tinnitus. In J.A. Vernon (Ed.). Tinnitus Treatment and Relief (pp. 164-186). Needham Heights: Allyn & Bacon.

Meikle, M. & Taylor-Walsh, E. (2012). Characteristics of tinnitus and related observations in over 1800 tinnitus patients. Proceedings of the Second International Tinnitus Seminar. New York 1983. Ashford, Kent, Invicta Press. Journal of Laryngology and Otology Suppl. 9, 17-21.

Mulrow, C., Tuley, M. & Aguilar, C. (1992). Sustained benefits of hearing aids. Journal of Speech and Hearing Research 35, 1402-1405.

Parazzini, M., Del Bo, L., Jastreboff, M., Tognola, G. & Ravazzani, P. (2010). Open ear hearing aids in tinnitus therapy: An efficacy comparison with sound generators. International Journal of Audiology 2011 Early Online, 1-6.

Schechter, M., Henry, J. & Zaugg, T. (2002). Selection of ear level devices for two different methods of tinnitus treatment. VIIth International Tinnitus Seminar Proceedings. R. Patuzzi. Perth, Physiology Department, University of Western Australia, p. 13.

Shekhawat, G., Searchfield, G. & Stinear, C. (2013). Role of hearing aids in tinnitus intervention: A scoping review. Journal of the American Academy of Audiology 24, 747-762.

Surr, R., Montgomery, A. & Mueller, H. (1985). Effect of amplification on tinnitus among new hearing aid users. Ear and Hearing 6, 71-75.

Ventry, I. & Weinstein, B. (1982). The hearing handicap inventory for the elderly: A new tool. Ear and Hearing 3, 128-134.

Vernon, J. (1988). Current use of masking for the relief of tinnitus. In M. Kitahara (Ed.). Tinnitus. Pathophysiology and Management (pp. 96-106). Tokyo: Igaku-Shoin.

Vernon, J. (1992).  Tinnitus: causes, evaluation and treatment. In G.M. English (Ed.). Otolaryngology (Revised Edition), pp. 1-25. Philadelphia: J.B. Lippincott.