This issue needs to be addressed, as individuals process sounds and words in everyday speech differently than when they are separated into individual elements with no competing sound sources or noise. Moreover, further research is needed to explore patterns of eye movements during speech comprehension – especially in the presence of noise – as such an investigation would allow us to better understand how people strategically use visual information while processing speech. To this end, we conducted an experiment to track eye-gaze behavior during a series of listening tasks as a function of the number of speakers, background noise intensity, and the presence or absence of simulated hearing impairment. Our specific aims were to discover how individuals might adapt their oculomotor behavior to compensate for the difficulty of the listening scenario, such as when listening in noisy environments or experiencing simulated hearing loss. Speech comprehension difficulty was manipulated by simulating hearing loss and varying background noise intensity. Results showed that eye movements were affected by the number of speakers, simulated hearing impairment, and the presence of noise. Further, findings showed that differing levels of signal-to-noise ratio (SNR) led to changes in eye-gaze behavior. Most notably, we found that the addition of visual information (i.e. videos vs. auditory information only) led to enhanced speech comprehension – highlighting the strategic usage of visual information during this process.Speech comprehension is often thought of as an entirely auditory process, but both normal hearing and hearing-impaired individuals sometimes use visual attention to disambiguate speech, particularly when it is difficult to hear. Many studies have investigated how visual attention (or the lack thereof) impacts the perception of simple speech sounds such as isolated consonants, but there is a gap in the literature concerning visual attention during  Many challenges can complicate conversational speech comprehension, such as the presence of background noise or an individual listener’s own baseline hearing capabilities. Unless we are in a particularly quiet environment, an ensemble of noises bombards us at all times, making accurate recognition of speech sounds a significant perceptual challenge. Listeners may compensate for difficulties in speech perception, however, by strategically changing their eye gaze behavior. Such is the case for people that have the ability to “read” lips . Even inEye-gaze has long been identified as an accurate indicator of directional visual attention . It shouWhile the discussion hitherto has been concerned primarily with overt visual orienting (e.g. deliberately orienting the eyes toward the location of attention), it is important to note that individuals need not shift their gaze overtly to alter the location of their attention. Rather, it is possible to mentally shift our attention without foveating (i.e. directly looking at) the region of interest in a process known as covert orienting . ResearcA primary function of the human auditory attention system is to disentangle sounds of interest from less interesting or important sounds in the environment. During natural listening , such as within a café, attending to what someone is saying to you might occur while others are simultaneously speaking all around you. In other situations, multiple speakers might be talking to you at once , making it difficult to pay attention to any individual speech stream. A good example of the ability of humans to perceptually separate some sounds from others is the “cocktail party effect” , in whicIntrinsically difficult speech comprehension tasks – such as trying to listen to a quiet speaker in a room of robust noise – are further complicated by the presence of hearing impairment. The ability to correctly comprehend speech diminishes significantly with age . This caHearing loss can occur as a result of many different factors, such as exposure to noise, or a genetic predisposition. However, a particularly large proportion of the hearing-impaired population suffer hearing loss from age-related factors alone. As people age it becomes increasingly difficult to focus on speech that is of interest when it is surrounded by other noises – especially other speech sounds . While iIn everyday speech, people attend to and process full sentences and interact with the semantics of the speech, but must also be sensitive to all the subtleties present in real-world communication. While much research has been conducted that illuminates how noise impacts speech perception , the degQuick Speech In Noise . Twenty-six reported a female gender identity, 15 reported a male gender identity, and 1 reported another gender identity. Participants exhibited a mean better-ear pure tone threshold average (PTA) of 2.82 dB HL averaged over octave frequencies from 500 to 2000 Hz. Participant PTAs ranged from −3.3 to 10 dB HL (Median = 3.3 dB HL).Seventy-one participants were recruited from the New Mexico State University Psychology Subject Pool and were compensated with partial course credit. This study was approved by the Institutional Review Board at New Mexico State University, and all participants gave written informed consent in accordance with the Declaration of Helsinki. Sixteen participants exhibited impaired hearing  and were eliminated from all subsequent analyses. Hearing impaired participants were removed so that our participants were on equal footing regarding their baseline level of hearing abilities and therefore would only vary as a function of the condition they were randomly assigned to. Of the remaining 55 participants, 13 were eliminated from analyss due to eye tracking calibration issues (e.g. wearing highly reflective glasses). The 42 remaining participants ranged in age from 18 to 25 years .Six videos consisting of single speakers and six videos including multiple speakers were downloaded from Eighteen sentences from the Quick Speech-In-Noise test . Target 1. The QuickSIN stimuli, however, are proprietary and thus cannot be made available for download.We also created a new multimodal (audio plus video) versions of the 18 QuickSIN sentences to test the contribution of visual information to speech perception . Shaped noise was added to the normal hearing stimuli to produce the hearing-impaired stimuli. We implemented the hearing impairment simulation method detailed in Participants interacted with a desktop computer running the Windows 10 operating system throughout the entirety of the experiment. The experiment itself was programmed in E-prime 3.0 . A desktop-mounted Eyelink 1000 eye-tracker  was used to record eye movement behavior at a temporal resolution of 500 Hz. A chinrest was used throughout the experiment to maximize eye tracking accuracy. AKG K240DF circumaural headphones  were used to present all auditory stimuli. A HP L2045w monitor with a refresh rate of 60 Hz and a resolution of 1680 × 1050 was used to display all video stimuli. The distance from the monitor to the chinrest was 30 inches. The entirety of the experiment was conducted within a sound attenuating booth  to control and minimize background noise. The ambient background noise level in the sound booth was approximately 36 dB(A) measured with a sound level meter.Each experiment session started by obtaining informed consent from the participant. When consent was provided, we then measured pure tone detection thresholds in both ears at octave intervals between 250 and 8000 Hz. The participant was then seated in front of the eye tracking apparatus and instructed to place their chin on the chinrest for the remainder of the experimental session. The chinrest was adjusted so each participant’s gaze landed centrally on the computer screen when the participant looked straight ahead. The participant then went through the calibration routine for the eye tracking system. The eye-tracker was then calibrated to be able to adequately track the participant’s pupil. The calibration procedure established a map of the participant’s known gaze position relative to the tracker’s coordinate estimate of that position. The routine required participants to fixate on a black circle as it moved to nine different positions (randomly) on the screen. Calibration was accepted if the mean error was less than 0.5° of visual angle, with no error exceeding 1.0° of visual angle. Periodic recalibrations ensured the accurate recording of gaze position throughout the experiment. Viewing was binocular, but only the right eye was recorded.2. The participant then proceeded to the next trial. The participant viewed a total of 12 videos: six single-speaker and six two-speaker. The presentation order for the 12 videos was randomized.The participant started the main phase of the experiment once calibration was complete. Throughout the experiment, the participant interacted with the tasks via the computer keyboard, and all aspects of the experiment were self-paced. The main experiment phase started with the participant providing demographic information. The participant then proceeded to the video-viewing portion of the experiment. During each video trial, the participant was instructed to attend carefully as there would be test questions following the clip. The eye tracker was recalibrated if necessary  and then the participant viewed the video. Four comprehension questions  were presented after each video terminatedThe audio-only QuickSIN was administered next. We utilized the standard QuickSIN procedure with the exception that responses were entered using a computer keyboard rather than verbally. At the beginning of the QuickSIN test, participants were instructed to listen for the target sentence and then type in some of the words from the sentence. A QuickSIN trial started with the presentation of the QuickSIN sentence, followed by a prompt that had the five keywords removed, e.g. “The ______ ______ ______ jumped over the ______ ______.” The participant was asked to type in the missing keywords one at a time. Keyword responses were scored as correct if they exactly matched one of the keywords in the QuickSIN stimulus. Word order was not considered during scoring, and typos/spelling errors were evaluated individually for correctness. Participants were presented with a total of three QuickSIN sentence lists (18 sentences). The number of correctly identified keywords was averaged across the three lists to produce an estimate of SNR loss.The final phase of the experiment consisted of the multimodal version of the QuickSIN. All details of this phase were identical to the audio-only QuickSIN with the exception that multimodal stimuli were used in place of the audio-only QuickSIN stimuli, and different sentences were used to avoid practice effects. After the conclusion of the multimodal QuickSIN phase, the experiment terminated and participants were debriefed. Experiment sessions lasted approximately 90 min, including obtaining informed consent, audiometry, the main experiment, and participant debriefing.While other research studies have investigated how different listening conditions influence the degree to which certain facial regions, such as the lips and eyes, are visually attended to F = 2.615, p = 0.86, ηp2 = 0.118, but we did find an effect of Number of Speakers, F = 35.885, p < 0.001, ηp2 = 0.648. The interaction was not significant, F = 0.212, p = 0.81, ηp2 = 0.011. We then used a pair of 2  × 2  mixed ANOVAs for follow-up analyses (one for each of the dependent variables). Here, we found no effect of Simulated Hearing Impairment on mean fixation duration, F = 0.036, p = 0.851, but we did find an effect of Number of Speakers, F = 18.238, p < 0.001, ηp2 = 0.313, with longer fixation durations for one-speaker videos (597 ms) relative to two-speaker videos (521 ms). The interaction was not significant, F = 0.159, p = 0.692. Eye movement results for video stimuli are plotted in F = 1.899, p = 0.176. There was a main effect of the Number of Speakers, F = 67.614, p < 0.001, ηp2 = 0.628, with fewer fixations being committed during one-speaker videos (253.27) relative to two-speaker videos (298.40). The interaction was not significant, F = 0.424, p = 0.519.We began by examining fixation duration and fixation frequency as a function of simulated hearing impairment condition and the number of speakers in the video. We first conducted a MANOVA that included both mean fixation duration and total fixation frequency data as dependent variables, and simulated hearing impairment and number of speakers as independent variables. We found no effect of Simulated Hearing Impairment, x, y) coordinates. Because the fixations varied in number, either a single bivariate normal distribution (for the single speaker videos) or a mixture of two bivariate normal distributions (for the two speaker videos) were fit to each subject’s data, separately for each video. This resulted in a vector of means for each combination of subject and video, corresponding to the mean(s) of the fitted distribution(s). One-speaker videos had a two-element vector corresponding to the x and y coordinates of the mean of the single fitted distribution, and two-speaker videos had a four-element vector corresponding to the x and y coordinates of the means of the two fitted distributions. In the two-speaker case, the mean of the leftmost fitted distribution was represented as the first two elements of the vector, and the rightmost fitted distribution was represented as the last two elements of the vector. These vectors served as the dependent variables for the subsequent Multivariate Analysis of Variance (MANOVA). Because the number of dependent variables (as well as the movies themselves) differed across the one- and two-speaker conditions, we ran two separate MANOVAs.We then conducted a quantitative analysis to compare the spatial distribution of gaze across conditions. Each subject viewed a total of 12 videos, six with a single speaker and six with two speakers. For each video, the eye tracker recorded the subject’s eye fixations as  = 1.279, p = 0.287. The main effect of video was significant, F = 128.529, p < 0.001, ηp2 = 0.978. The main effect of Simulated Hearing Impairment was not significant, F = 1.701, p = 0.196.Starting with the one-speaker videos, we ran a 2-way mixed MANOVA with Simulated Hearing Impairment  as a between-subjects factor and Video (six levels) as a within-subjects factor. The x and y coordinates for the mean of the fitted distribution served as dependent variables in the analysis. The Video by Simulated Hearing Impairment interaction was not significant, x and y coordinates for the means of each of the fitted distributions served as dependent variables in the analysis. The Video by Simulated Hearing Impairment interaction was not significant, F = 1.358, p = 0.254. The main effect of video was significant, F = 64.082, p < 0.001, ηp2 = 0.985. The main effect of Simulated Hearing Impairment was not significant, F = 1.514, p = 0.219. Therefore, we did not find evidence to support the idea that the spatial distribution of gaze changed with the level of hearing impairment for either one- or two-speaker videos.We found very similar results with the two-speaker videos. For this analysis we ran a 2-way mixed MANOVA with Simulated Hearing Impairment  as a between-subjects factor and Video (six levels) as a within-subjects factor. The To analyze the data from the QuickSIN phase of the experiment, we started by examining the eye movement data during the multimodal version of the QuickSIN test. We looked at the effects of simulated hearing impairment and Signal-to-Noise Ratio  on fixation duration and fixation frequency.F = 2.760, p = 0.76, ηp2 = 0.124, but we did find an effect of SNR, F = 2.556, p < 0.0001, ηp2 = 0.452. The interaction was not significant, F = 0.897, p = 0.547, ηp2 = 0.224.We first conducted a MANOVA that included both mean fixation duration and total fixation frequency data as dependent variables and simulated hearing impairment and SNR as independent variables. We found no effect of Simulated Hearing Impairment, F = 0.328, p = 0.570. There was a main effect of SNR, F = 3.918, p = 0.038, ηp2 = 0.089. As SNR increased, fixation durations decreased . The interaction was not significant, F = 0.561, p = 0.518.We then conducted a follow-up pair of 2 (Simulated Hearing Impairment) × 6  mixed ANOVAs, one for each dependent variable. We found no effect of Simulated Hearing Impairment on fixation duration, F = 4.823, p = 0.034, ηp2 = 0.108,with fewer fixations in the simulated hearing impairment condition (7.10), relative to the normal condition (9.48). There was also a marginally significant effect of SNR, F = 3.010, p = 0.062, ηp2 = 0.070. Fixation frequency tended to increase as SNR increased . The interaction was not significant, F = 0.998, p = 0.365. Eye movement results can be seen in We found a main effect of Simulated Hearing Impairment on total fixation frequency, As with the movie data discussed above, we conducted an analysis of the spatial distribution of gaze during the multimodal QuickSIN test. In this case, Simulated Hearing Impairment was still a between-subjects factor. Signal-to-Noise Ratio (SNR) was a within-subjects factor and ranged from 25 to 0 dB in 5 dB steps. Because all speakers in the multimodal QuickSIN were located in the same position on the computer screen (unlike the movie stimuli), we combined fixation data across the videos. This resulted in a collection of gaze fixations for each combination of subject and SNR. As before, a bivariate normal distribution was fit to these data, resulting in a two-element mean vector for each combination of subject and SNR. These vectors served as the dependent variables for the MANOVA-based analysis.F = 1.036, p = 0.439. The main effect of SNR was not significant, F = 0.664, p = 0.748. The main effect of simulated hearing impairment was not significant, F = 0.655, p = 0.525. As with the video data discussed above, we found no evidence from the multimodal QuickSIN data that the spatial distribution of gaze changes with the difficulty of the listening task (either through the simulated hearing impairment or SNR manipulations).We ran a 2-way mixed MANOVA with Simulated Hearing Impairment  as a between-subjects factor and SNR (six levels) as a within-subjects factor. The x and y coordinates for the mean of the fitted distributions served as dependent variables in the analysis. The SNR by Simulated Hearing Impairment interaction was not significant, r(40) = 0.95, p < 0.001. Mean SNR loss as a function of QuickSIN modality  and simulated hearing impairment  is illustrated in F = 74.522, p < 0.001, ηp2 = 0.651. The additional visual information in the multimodal stimuli led to a 9 dB improvement in SNR loss, but only for participants in the simulated hearing impaired condition. There were also significant main effects of modality, F = 43.806, p < 0.001, ηp2 = 0.523, and simulated hearing impairment F = 70.143, p < 0.001, ηp2 = 0.637. The main effect of modality appears to be entirely driven by the significant modality by simulated hearing impairment interaction.Finally, we compared the audio-only and multimodal versions of the QuickSIN to determine the use of visual information during different levels of simulated hearing impairment. SNR loss measures using the audio-only and multimodal QuickSIN measures were strongly correlated, Our ability to process auditory environments and disentangle sounds of interest from irrelevant sounds is often taken for granted. This ability, unfortunately, degrades as we age and as a result of hearing damage. However, both normal hearing and hearing-impaired individuals may be able to make use of a number of strategies to better understand speech and other sounds in perceptually challenging conditions. The present research investigated how individuals vary their oculomotor behavior as a function of simulated hearing impairment, number of speakers in the conversation, and the degree of background noise. This research fills an apparent gap in the literature for studies that go beyond the perception of simple speech sounds, such as individual consonants, and instead makes use of either sentences or fully conversational stimuli, which include the nuances of language such as semantics.There were three major findings in the present research: (1) visual information was especially useful for those in the simulated hearing impairment condition, (2) fixation durations were longer when participants were listening in higher levels of background noise, and (3) the spatial distribution of eye gaze was consistent across levels of simulated impairment and background noise. These results suggest that eye gaze stabilizes to some extent during difficult listening conditions, and that hearing impaired listeners may benefit especially from the presence of visual information compared to individuals with normal hearing.The audio-only vs. multimodal QuickSIN results supported our prediction that visual speech information could be used to improve speech perception for those with simulated hearing impairment. Participants in the simulated hearing impairment condition were able to use the visual information that accompanied multimodal QuickSIN stimuli to perform significantly better than in the audio-only QuickSIN, reducing SNR loss by approximately 9 dB. It appears that participants were using the visual information provided to help capture additional information about the speech stimulus. The participants may have used cues based on lip movements to disambiguate the sentence in the presence of noise; in this case the moderate simulated hearing impairment. Interestingly, normal-hearing listeners did not show any benefit from the inclusion of this information. This points to the fact that, during challenging listening tasks such as speech comprehension in noise and in difficult SNR environments, individuals can effectively take advantage of visual information to partially counteract the effects of moderate hearing loss. This has important implications for better understanding how hearing-impaired individuals strategically change their eye gaze behavior  to handle perceptually challenging speech comprehension. It is important to note that the audio-only QuickSIN always preceded the multimodal QuickSIN. We firmly believe that the result observed is due to our experimental manipulation and not a potential order effect for two primary reasons: (1) no QuickSIN sentences were repeated during the experiment, so participants did not have any additional information during the multimodal QuickSIN than they had during the audio-only QuickSIN , and (2) the QuickSIN is a validated diagnostic instrument that does not show practice effects as the individual’s ability to perceptually segregate noise from a target will not improve or worsen over the course of the experiment. Indeed, research has supported that repeated speech perception in noise tests are not susceptible to learning effects so long as the stimuli are not repeated .A significant effect of SNR on fixation duration also supported our prediction that oculomotor behavior would vary across noise levels, such that longer fixation durations would be observed under more difficult listening conditions. While eye-gaze data did not, by and large, differ in relation to simulated hearing impairment, gaze fixation duration was significantly impacted by the level of SNR. Analyses also showed a main effect of SNR on mean fixation duration, such that fixation durations generally decreased as SNR increased. In other words, more difficult listening situations appear to lead to longer fixation durations, and in general, heightened or stabilized visual attention. The implication here is that individuals rely on visual information more frequently when the level of auditory background noise is louder and more robust than the target signal, regardless of hearing impairment.While individual distribution of gaze location did differ across one and two-speaker videos, such that there were a pair of hotspots in the two-speaker videos compared to one major hotspot region in the one-speaker heatmaps, quantitative analyses did not show any difference the gaze spatial distribution across simulated hearing impairment or noise. The video clips presented had the speakers situated in the center of the screen, where eye-gaze was most focused. This indicates that during the one-speaker videos participants were staring at the single speaker’s face for a majority of the clips, whereas during the two speaker videos, participants split their fixations between the two faces. In both situations, participants focused their gaze more on the faces rather than the surrounding environment. This behavior was consistent across levels of simulated hearing impairment and background noise. Additionally, we found that eye movement behavior varied across levels of SNR during the multimodal QuickSIN tasks. Indeed, fixations increased in duration as SNR decreased, which suggests that listeners focused longer on particular visual regions in difficult listening conditions. However, we found no evidence that listeners distribute their gaze differently according to the difficulty of the listening environment. Across all conditions in both experiments, approximately 75% of total fixation time was spent focused on the face(s) of the speaker(s).We did, however, find an effect of simulated hearing impairment on total fixation frequency data showing that fewer fixations were observed in the simulated hearing impairment condition. Specifically, longer fixation durations were observed at lower SNRs, and a main effect of simulated hearing impairment on total fixation frequency data showed that fewer fixations were observed in the simulated hearing impairment condition. This was the only such finding, however, and the pattern of results seems to support the notion that noise is more of a consistent factor on eye movements during conversational listening than simulated hearing impairment. Taken together, the results not only suggest that individuals focus longer on critical areas of interest at lower SNRs, but also that hearing-impaired individuals tend to focus longer on particular areas of interest relative to normal-hearing individuals. While lower SNRs led to longer fixation durations across both normal and simulated hearing-impaired individuals, simulated hearing-impaired individuals needed to fixate longer on particular regions of interest to help manage the increased perceptual challenge.These findings support the conclusion that individuals strategically adjust aspects of their oculomotor behavior in response to the level of background noise in the listening environment. In high noise environments, listeners lengthen their eye fixations and begin to make use of visual speech information to improve their speech perception. Research investigating how listeners use and direct their gaze to focus attention on a speaker is integral to better understanding the strategies people – particularly those with hearing impairment – use to understand speech.Difficulty in the perception of speech can be the result of a variety of factors, any of which can lead a person to strategically alter their listening and oculomotor behaviors. The present research gives us a better understanding of how individuals direct their gaze under different levels of hearing impairment and background noise. Importantly, this investigation incorporated conversational listening tasks and real-world noise environments to improve the generalizability of the findings. Our results showed that different levels of SNR led to unique eye movement behavior such as longer fixation durations during more difficult hearing conditions. This finding generalized to both normal hearing and simulated hearing impairment individuals. These results indicate that eye-gaze behavior may be less well predicted by hearing impairment than originally thought, and that instead, eye-gaze behavior may be more heavily impacted by the relative noise conditions in the auditory environment.https://osf.io/3q8y6/?view_only=89e01a3eba4c447b987f2d 3642e773c2.All raw data and multimodal video stimuli can be found here: The studies involving human participants were reviewed and approved by the New Mexico State University Institutional Review Board. The patients/participants provided their written informed consent to participate in this study.All authors contributed to the conception and design of the study and contributed to revising the manuscript either through direct edits or feedback, and read and approved the submitted version. MH and JM processed all experimental data, conducted appropriate analyses, and created the figures. EŠ, DH, MH, and JM wrote components of the manuscript. EŠ and DH led the organization of databases. EŠ was lead on drafting the work and revising it critically. All authors assisted with interpretation of the data. MH programmed the experiment. JM, EŠ, and DH wrote scripts to programmatically generate and standardize the stimuli. AM and HM substantially contributed to the acquisition of data.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Cochlear implants (CIs) can provide a sound sensation for those with severe sensorineural hearing loss (SNHL), benefitting speech understanding and quality of life. Nevertheless, rates of implantation remain low, and limited research investigates journeys from traditional hearing aids to implantable devices.Fifty-five adults (≥ 50 years), hearing aid users and/or CI users, General Practitioners, and Australian and United Kingdom audiologists took part in a multi-methods study. Focus groups, interviews, and surveys were thematically analysed.The burden of hearing loss and the impact of Cochlear Implants”, and 2) “Professional Support and Practice, and HCPs Roles and Responsibilities”.One hundred forty-three data-capture events disclosed 2 themes: 1) “Care experience can include convoluted, complex journeys towards cochlear implantation. The significant impact of this, as hearing loss progresses, motivates people to consider implants, but they and healthcare professionals need clear supported with defined referral pathways, and less system complexity. The incidence of significant, acquired hearing loss in adults is rising year on year. In the United Kingdom (UK), it is estimated that 5.3 million adults over the age of 65 have a hearing loss  and thatAdditionally, hearing loss has significant negative implications for individuals in relation to communication, work and education, and social participation , 5, and Despite the well-documented, positive benefits of cochlear implantation and the known costs of untreated hearing loss , utilisaThe patient journey may be defined as the experiences and processes the patient goes through during the course of a disease and its treatment . To dateGiven the limited research investigating the patient journey for adults who go on to receive CIs, this study aimed to develop a rich, in-depth understanding of the factors that impact and influence patients’ and professionals’ experiences within the context of this journey. The current study is novel in its international approach to exploring older adults’ lived experiences of hearing loss and hearing healthcare, together with its focus on professional roles and responsibilities and the complex decision-making associated with CI referral. This study also uniquely includes first-hand accounts from non-CI specialists.The study explored the hearing healthcare experiences of older adults with severe (or ‘greater’) SNHL in the context of their journey to cochlear implantation. Specifically, this study sought to: 1) describe the experiences of hearing healthcare provision from the perspective of patients, GPs and audiologists and 2) gain insights into this client group’s perceived hearing healthcare needs as they investigate different treatment options including cochlear implantation.Ethical approval was obtained for this study from Macquarie University Human Research Ethics Committee before any data collection took place .This was a multi-phase, multi-method study conducted in Australia and the United Kingdom, between June 2017 and April 2018. The UK’s publicly-funded National Health Service (NHS) offers universal healthcare that is free to all legal residents from point of use . ConductPromotional flyers were distributed across Australian audiology clinics, GP clinics and hearing associations, in hard copy and online, and via professional organisation websites in the UK . In Aust(1) 50 years of age and older, (2) with severe, post-lingual SNHL, (3) self-identified as proficient English speakers, (4) willing to participate in focus groups or interviews, and (5) willing to complete a demographic questionnaire and an open-ended qualitative survey.(1) GPs or audiologists HCPs, (2) working with the target patient populations, (3) willing to participate in focus groups or interviews, and (4) willing to complete a demographic questionnaire and an open-ended qualitative survey.Purposive timeframe sampling, a tried and tested method by this team , 23, wasFocus groups and individual interviews were facilitated by a researcher, one in Australia  and another in the UK , both with extensive experience conducting research, and no prior relationships with participants. For further detail on the data collection methods see the parallel publication . A set oAll focus groups and interviews lasted approximately forty-five minutes and were audio-recorded. Focus group facilitators were trained in facilitation techniques to support communication with people with hearing loss . Real-time sub-titles and printed questions were provided to participants before the interviews or focus groups began, for additional support . The rooAll audio recordings were transcribed verbatim and thematically analysed  along win = 55): 17 CI users, nine HA users (including two CI candidates who had begun CI candidacy assessment), seven GPs, and 11 Australian audiologists (9 HA audiologists and 2 CI audiologists). To compare two well-established systems using different funding models, 11 audiologists were also recruited from the UK  , fitted with a CI in one ear and a HA in the other (n = 8), who had used a CI for more than 3 years (n = 17), and were HA users for more than five years prior to implantation (n = 16). Many CI users (n = 8) travelled to access hearing services (up to 1700 km per round trip). The HA users (including two CI candidates), were all bilateral HA users (N = 9), and had been for more than 5 years (n = 9). Most HA users accessed local hearing services (n = 7)  can’t hear properly” (CI user 7). They felt less sure of themselves, their self-confidence progressively declined, and they saw themselves as ineffectual communicators, who needed to find extensive adaptive behaviours:It’s almost like hearing impairment actually makes you inferior … People seem to be more comfortable helping someone with vision problems. They’re less patient with people who have communication difficulties.—HA user 1.The effect of increased listening effort resulted in changes to HA and CI users’ sense of self-identity, and the sense that others perceived them as “Some HA and CI users reported using strategies to cope, including lip reading, choosing a quiet environment to talk in, and using emails to communicate. However, this still led to frustration and stress, affecting their social life, and limiting their opportunities at work.I would suffer from dreadful tiredness from trying to communicate all day. It used to take so much out of me to listen. Now I forget how much trouble I had and how tired and depressed it used to make me feel” (CI user 2). Many also reported that CIs improved their ability to use the phone and hear music, as well as increasing their engagement and confidence, and improving relationships with friends and family.Most CI recipients discussed the effect of CIs on their wellbeing and were generally positive, reporting a marked improvement in their emotional wellbeing, hearing, and communication as well as reduced listening effort and listening-related fatigue: “People in the everyday world, which includes health professionals, [need] to develop more understanding of hearing impairment, and not consider a [HA] or a [CI] as something that restores hearing to normal function.—CI user 11.HA and CI users suggested improvements need to be made to professional education, to better support adults to understand their options, enabling patients to receive better information early on, and providing greater access to CI services. Similarly, they talked about the need for health promotion campaigns to support greater awareness, understanding and empathy in the general public about what it means to have a hearing loss, the impacts and limitations of CIs and HAs and the need for improved support infrastructure, and services.I would say the only thing missing at the beginning of my discovery of my hearing impairment was emotional support to cope with hearing impairment” (CI user 2).The provision of psychosocial support from hearing services, increased access to CIs for individuals, and continued financial and technological support from CI manufacturers, insurance companies and hearing organisations were seen as ways to ease the burden of hearing loss by both CI and HA users: “I would say the main challenge is the distance that I have to go to get mappings done, to get replacements, things like that.—CI user 3.Unilateral CI recipients were protective of their remaining hearing in the other ear, fearing further damage, and guarded against this by avoiding noisy situations. They were satisfied and grateful for the improvements in hearing, however a number of challenges remained, including trying to hear conversations in large groups, and using the telephone. Other issues included the need for regular battery changes, the dissatisfaction with the quality of the CI sound, and the need for safety devices, to provide alerts when they took off the external part of their device. Live entertainment also proved difficult for both HA users and CI recipients who, limited by their hearing loss, had to rely on captioning or subtitles. Some CI and HA users talked about the burden of costly devices and upgrades, problems of travelling to hearing health services, and ongoing associated maintenance costs leading to a reliance on financial support from private health insurers, and government schemes:Just being deaf does make it difficult to communicate with health specialists … heaven knows how I ever communicated with my doctor in the past about important health issues.—CI user 2.HA and CI users discussed the practical assistance they received from HCPs. Both groups found accessing health information themselves challenging, due to the severity of their hearing loss:It’s not something that’s achieved in one visit. It’s an idea that you set the seed and develop, feeding in information as appropriate, and get them to a position where they feel they can make a decision whether to be referred or not.—UK audiologist 9.To complement the patient perspective, HCPs discussed their practice, roles and responsibilities. CIs are first introduced by HA audiologists when patients report inadequate HA benefit, and when audiometric results suggest patients may benefit from a CI. Feeling supported and provided with consistent information was seen to be important to help patients to come to terms with changes in their hearing loss and needs. However, Australian and UK audiologists described patients as often negative about CIs to begin with and as a result, discussions and decisions about CIs often required multiple sessions:Audiologists’ perceptions of their own roles varied. Some thought they were there to provide a basic service only, while others felt patients required more active support. This included: making appointments for CI clinic assessments, providing resource materials, directing patients to hearing associations, and ensuring patients were fully informed. GPs on the other hand, saw themselves as playing a coordinating and referral role only. Key decision-points in the patient journey, as perceived by HCPs, included patients’ acknowledgment of their hearing loss, accessing hearing healthcare services, deciding to have an HA fitted, agreeing to a CI assessment, and agreeing to CI surgery.Very hard … I see a different person almost every appointment which is quite confusing having to go over everything each time…. I feel too old sometimes to bother, sometimes too frustrated with my hearing disappearing so fast and not getting answers.—CI candidate 1.Most patients reported being satisfied with their audiologists’ advice and support, but felt that knowledge of CIs was variable amongst HA audiologists. A lack of individual clinician-patient continuity was seen to be problematic, especially if patients had to provide their hearing history repeatedly to new clinicians along the way:I’ve seen a patient and then I’ve discussed [CIs]. Then they’ve seen somebody … Then the patient won’t come back again. I wouldn’t know what happened to them … and there’s no closure.—UK audiologist 3.Audiologists felt that poor patient-clinician continuity made the building of trust challenging, and often resulted in a lack of awareness of a patient’s hearing history. HA audiologists did not always feel confident discussing CIs with patients and fragmented care could make it more difficult for professionals to confidently raise the issue of CIs with patients, and to understand the impact that conversations with preceding clinicians had on a patient’s perception of CIs.We find ourselves sometimes chasing up communication from medical professionals, particularly specialists. Sometimes ensuring the lines of communication are open falls to the client.—Australian audiologist 2.Communication between HCPs in Australia was reported to be inconsistent and unidirectional at times, with audiological assessment reports sent to GPs, specialists, and CI clinics, but feedback rarely received by HA audiologists, whereas communication between HCPs in the UK was reported as much more consistent. In Australia, shared care was reportedly lacking, between GPs, audiologists, and specialists:.HCPs in Australia felt the referral pathways were convoluted and lacking in clarity. Whereas in the UK, audiologists reported typically sending CI candidates to either a senior audiologist or a CI clinic, as well as to hearing associations for information. Co-location of some hearing clinics with CI clinics in the UK, made bi-directional communication and shared patient information more feasible. Multidisciplinary team meetings were suggested by several UK audiologists as an effective strategy to improve shared-care, where patient cases were discussed across health specialistsThe GP is really not interested in my hearing. He’s more into keeping me alive I suppose” (CI user 6). GPs self-identified as lacking knowledge about CIs and hearing loss devices in general and felt unable to directly advise patients. They were often seen by patients as lacking in knowledge regarding hearing pathways, adding unnecessary time, especially during early-stage investigations, to the patient journey through the system.HA and CI users felt most GPs prioritised other health conditions over hearing health: “Many HA and CI users found support groups helpful and valued attending functions where they could access CI information, and increase opportunities for social support, enabling HA participants to meet CI recipients, and gain first-hand information about CIs.This multi-method study used thematic analysis, from an essentialist perspective, to provide insights into factors that impact the patient journey for adults with hearing loss, who go on to access CIs. The findings present accounts from both patients and HCPs in Australia, and audiologists in the UK. While the content of the two themes confirms previously published literature on the impact of severe SNHL and the benefits of CIs, it also contributes novel findings relating to the patient journey, especially regarding events occurring before referral to specialist CI services, and adds rich content to clarify the team’s research in this field , 22. TheThe factors that characterise the patient journey to cochlear implantation may be anchored in Manchaiah et al.’s  account This study provides valuable insights into the role of the non-specialist professional  in patient care. Few studies have explored qualitatively the care pathway up to the point of CI referral. The findings emphasise the important role that non-specialist professionals assume in this process. The patient and professional accounts support and enhance findings of a UK survey-based pilot study  undertakReduced wellbeing was reported by participants as a “burden of hearing loss” and is consistent with the established literature on psychosocial wellbeing in hearing loss , 19 and The results from this study have the potential to inform clinical practice with respect to public health. Our interpretation of participant accounts suggests that strategies to increase public awareness of hearing loss could empower patients to raise cochlear implantation with their HCPs, leading to timely referral to CI specialist programmes. Moreover, increased public awareness could empower patients’ help-seeking behaviours, particularly with regards to information access. Adult hearing loss Associations of are powerful providers of support and buddying schemes . These mDespite the purposive timeframe sampling approach, recruitment took a lengthy period of time as HCP participants were slow to recruit. Furthermore, participant self-selection may have influenced the representativeness of the sample, which in turn has implications for the translation of these data to wider population groups. However, self-selection within a given time-period and across a wide professional group, in addition to the patient demographic-mix, meant rich data were collected from participants willing and able to offer detailed accounts of their needs and of professional support. We also note that a considerable proportion of patients were recruited via patient associations, which may have influenced the positive report these participants had towards such organisations.The present study utilised the accounts of audiologists in the UK to examine the patient journey to cochlear implantation within a different healthcare system. The UK audiologist accounts supported findings from Australian audiologists, irrespective of the differences in service delivery and are a strength of this study. However, for pragmatic reasons, a UK sample of adults with HL who used either HAs or CIs was not included; therefore, a comparative patient perspective of the CI journey was not provided. Future research to verify and extend the findings from patient groups across different healthcare systems would further enrich study findings. In addition, future research will include the perspectives of other HCPs involved in the pathway to CIs, such as Ear Nose and Throat specialists, to develop a more comprehensive understanding of all of the services involved in the patient journey.A better understanding of the patient journey to cochlear implantation is identified as an important component of continued quality improvement in hearing healthcare. This multi-method study presented key factors that influence the CI journey for adults with severe SNHL. In identifying these factors, the study offers a picture of the hearing health experiences of Australian CI and HA users, and their reflections on professional practice, supported by the views and experiences of Australian GPs and audiologists, and corroborated by accounts from audiologists in England and Wales.These findings suggest that patients require early, easy access to reliable information on CIs and timely referral to specialist CI services, and targeted support for patients and professionals is required at earlier stages of the CI journey. Non-specialist hearing HCPs must be confident and well-informed, and should have access to targeted, evidence-based continuing professional education and resources. Peer-support is an important element of patient care, with the aim of increasing access to reliable information and uptake of appropriate CI referrals and to ease the patient’s transition from HAs to CIs.These strategies along with improved shared care, and better infrastructure and support strategies, have the potential to improve the QoL of adults with severe SNHL, who currently experience difficulties with their HAs, by providing more comprehensive information and timely referral to CI specialist teams. Importantly, future research should extend the study’s findings by seeking to determine the most effective strategies for CI uptake. Importantly, the patient journey continues beyond the act of receiving a CI, therefore further research is needed to extend the study’s findings, mapping the patient journey in-depth, as they move towards cochlear implantation.


Tropical cyclones (TC) are one of the deadliest and costliest natural disasters. To mitigate the impact of such disasters, it is essential to know extreme exceedance probabilities, also known as return periods, of TC hazards. In this paper, we demonstrate the use of the STORM dataset, containing synthetic TCs equivalent of 10,000 years under present-day climate conditions, for the calculation of TC wind speed return periods. The temporal length of the STORM dataset allows us to empirically calculate return periods up to 10,000 years without fitting an extreme value distribution. We show that fitting a distribution typically results in higher wind speeds compared to their empirically derived counterparts, especially for return periods exceeding 100-yr. By applying a parametric wind model to the TC tracks, we derive return periods at 10 km resolution in TC-prone regions. The return periods are validated against observations and previous studies, and show a good agreement. The accompanying global-scale wind speed return period dataset is publicly available and can be used for high-resolution TC risk assessments. In 2017, Hurricanes Harvey, Irma and Maria entered the top-5 costliest Atlantic hurricanes ever, with combined losses estimated at $220 billion2. To minimize future loss of life and property, it is crucial to perform accurate TC risk assessments and identify high-risk locations so that appropriate protection measures can be designed.Tropical cyclones (TCs) are amongst the deadliest and costliest natural disasters, affecting people, economies and the environment in coastal areas around the globe. In 2019, Cyclone Idai caused over 1,000 fatalities and displaced 3 million people upon landfall in Mozambique3. Moreover, wind correlates with the intensity of other TC-induced hazards, such as storm surges, waves and precipitation6. To enhance our understanding of TC risk at the global scale, it is therefore essential to analyze wind speed probabilities in coastal zones. Risk is commonly calculated as the integrated value of expected damages over all exceedance probabilities –the inverse of these probabilities being return periods (RPs)7. As such, accurately calculating risk requires information on a wide range of RPs. Simpson and Lawrence8 empirically estimated TC RPs along 80 km-long coastal segments of the US coastline based on historical TCs. However, RPs could not be calculated for those coastal segments that were not hit by a TC in the 85 years of observations. This shows that, due to the short length of the observational record, data often needs to be aggregated over larger spatial regions to perform a RP analysis, hereby omitting the spatial heterogeneity. Moreover, estimating RPs comes with large uncertainties, especially for RPs exceeding the length of the observational record. To overcome these limitations, the methodology of synthetic TC track generation has been developed over the past few decades12. In this approach, TCs, extracted from either historical data13 or climate model simulations14, are statistically resampled and modeled to generate synthetic, but realistic, TCs. Using a Monte Carlo approach, this procedure is repeated recurrently to construct a TC dataset having the same statistical characteristics as the input dataset, but spanning hundreds to thousands of years.Wind is one of the major hazards associated with TCs and can do substantial damage to housing, infrastructure and ecosystems both in coastal regions and far inland12. The STORM dataset spans 10,000 years of global TC activity under present-day climate conditions, based on observed TC tracks. Here, we demonstrate usage of the STORM dataset by creating wind speed RPs at three different spatial scales: (i) basin level; (ii) within 100 km for 18 selected coastal cities and 63 islands; (iii) at 10 km resolution in TC-prone regions. This dataset is unique in presenting (high) RPs at a global scale for all TC-prone regions. More importantly, it represents an important step forward to calculating global TC damages and risk.Using synthetic data enables the analysis of higher RPs and at higher spatial resolution than previously possible. In an accompanying paper we have presented the global synthetic model STORM 16. A benefit of this approach is that no specific shape of the RP-curve is assumed; RPs are calculated per given wind speed without interpolation or smoothening of the data. However, the highest RP is limited by the temporal length of the data as this method does not allow for extrapolation beyond this timespan. TC risk assessments typically require information on extreme events that have not been observed yet. Therefore RPs are often determined by fitting extreme value (EV) distributions17 to historical data. This way any RP can be estimated, even those beyond the range of observations. To ensure there is enough data for a good fit, this approach is generally carried out for ocean basins or relatively large coastal sections. Such fitted RPs are strongly influenced by the selected EV distribution, especially for higher RPs18. Furthermore, short records have large uncertainties, and typically multi-decadal records are needed for reliable estimates of the tail (high RPs)19.Calculating RPs of (extreme) wind speeds in the STORM dataset can be done either empirically or statistically. When using an empirical approach, RPs are directly calculated from wind speeds ranked in order of magnitude using formulas like Hazen’s or Weibull’s plotting formula20, but other averaging periods can easily be obtained using conversion factors21. Next, we fit five EV distributions  to 1,000 random realizations of 38 years of data sampled from the STORM dataset. This 38-year length was chosen as the STORM dataset was created using 38 years of historical data (1980–2017) from the International Best Track dataset for Climate Stewardship (IBTrACS20).Here we compare these two approaches to estimate basin-scale RPs using the synthetic TCs from STORM. We apply Weibull’s plotting formula to the maximum 10-meter 10-minute average sustained wind speeds (max U10) in the full STORM dataset . We use max U10 because this is globally the most commonly reported value of wind speeds23. Consequently, at high RPs, max U10 from EV distributions are higher than their empirically derived counterparts, with a maximum difference of 117 m/s for the GEV in the North Atlantic at the 1,000-yr RP. For the North Indian, we observe a kink in the empirical curve around the 20-yr RP: this is likely caused by an absence of certain max U10 in the dataset, which are then excluded from the RP calculation. This absence is driven by a limited spatial distribution of sea-surface temperatures (SSTs), causing a more frequent occurrence of higher max U10. Figure At basin-level, the empirically derived STORM-RPs agree with the observed RPs Fig. . In the 24 and instead move out over the open ocean. This is caused by TCs being embedded within the prevailing easterly (westward) flow at these latitudes. Secondly, TCs dissipate when they make landfall. As Muscat is located in the relatively narrow Gulf of Oman, most TCs in this region will likely have passed land upon approaching Muscat. Lastly, both Mumbai and Muscat lie in the North Indian, where approximately 2 TCs form per year12, hereby further decreasing the chances of being hit by a TC in any given year. Of the cities considered here, Taipei (Taiwan) and Tokyo (Japan) experience TCs most often, with RPs for a Category-1 lower than 4-yr. Both cities are located in the Western Pacific, the most active basin with 22.5 TC formations per year12. Of the cities considered, San Juan (Puerto Rico) and Chittagong (Bangladesh) are most often affected by strong TCs, with Category-5 TCs having a 131-yr RP for both cities. San Juan’s central position in the tropical Atlantic Ocean combined with frequent Category-5 TC formations . The RP-curves  spatial resolution. While a single extreme event might be captured well in historical datasets (e.g. Hurricane Irma in IBTrACS), there are not enough events in such datasets to robustly calculate high RPs. To calculate max U10 at 10 km resolution, we fit a 2D-parametric wind model to each synthetic TC (see Methods). Note that RPs inherently depend on the spatial scale they are computed at. At basin-scale, multiple TCs form every year, each one potentially reaching a given max U10. At a high-resolution grid cell, a TC passage can be rare. Hence, for equal max U10, RPs are lower when computed at higher resolution.25 of approximately 29 °C drive TC intensification, resulting locally in max U10 exceeding 65 m/s for a 1,000-yr RP. Aside from basin-scale variability in max U10, the two insets in Fig. Figure 26, see Methods. There are large spatial variations, but for all basins RPs are lowest for a Category-1 or Category-3 event in the tropical regions. For large parts of the Western Pacific and the eastern part of the Eastern Pacific, Category-1 TCs have an approximate 2-yr RP. In the other basins, these RPs lie between 5 and 20-yr. Category-3 TCs, however, occur less frequent, ranging between 10-yr RP for the Western Pacific to 90-yr RP for the North Indian.Besides calculating max U10 for specific RPs, we can also reverse the procedure and compute the RP for given TC-categories. Figure At basin-level, we have shown that the STORM-RPs compare well with observations Fig. . At locaet al.24 reported a 49 to 97-yr RP for a Category-1 TC within 150 km from Mumbai, agreeing well with the STORM-RP of 66-yr. Similarly, they estimate Category-3 RPs around 500-yr, while STORM-RPs are around 138-yr. For a Category-1 TC occurring in Mumbai, Sobel, et al.24 list a 224 to 236-yr RP; compared to a STORM-RP of 95-yr. For the city itself, RPs vary between 3,000 to 10,000-yr, compared to 550-yr in STORM. STORM-RPs are predominantly lower than those in Sobel, et al.24. Sobel, et al.24, however, speculate that they underestimate the TC hazard. Further differences are likely driven by the use of different track modeling methods, wind field parameterization schemes (including different resolutions) and RP estimation techniques.For 18 cases we compare max U10 for given RPs with STORM, and for Mumbai we compare the RPs for given categories (see Online-only Table 1). Sobel, 27. This relatively large difference (−38.3%) is likely caused by the fact that Darwin is located near the South Indian-South Pacific basin border, and is hit by TCs originating in both basins. STORM, however, models TCs per basin, cutting off South Pacific TCs at the basin boundary. Townsville and Port Hedland are located further away from the basin boundary and max U10 are in better agreement. Additionally, we observe relative differences of −35.9% and −25.1% for the Federated States of Micronesia (FSM) and Palau, respectively. In STORM, the lower basin boundary in the Western Pacific is set at 5°N. As these island countries lie at around 7°N, and modelled TCs generally deflect away from the Equator, this means most TCs in STORM pass north of the island countries. Conversely, the AIR Tropical Cyclone Model28 models the Pacific region as a whole, and thus TCs have a higher probability of affecting FSM and Palau.STORM performs well for given RPs: for 13 out of 18 cases, absolute differences between max U10 in STORM and other models lie within 5 m/s. The largest difference is 18 m/s for Darwin, Australiaet al.29 calculated RPs for Category-1 and 3 TCs using the CHAZ model. The general spatial patterns in the CHAZ model  and STORM . Future research could study these aspects by e.g. using ensemble runs, or by generating synthetic TCs per oscillation phase.First, the STORM dataset is based on average present-day climate conditions (1980–2017), and as such does not capture climate variability. The climatology represented by STORM may be biased by the phases of multi-decadal variability contained in the 38-year period of record that was used to generate the dataset, which may not be representative for longer timescales. Moreover, the STORM dataset cannot be used to assess climate trends on decadal timescales or the effects of climate oscillations on TCs  RPs at 10 km resolution on a global scale. It represents an important step forward in global TC wind risk assessments, particularly for island countries and TC-scarce regions. Furthermore, this research can contribute to an improved quantification of other TC-induced hazards such as storm surge and precipitation12. This dataset is created using historical data from the International Best Track Archive for Climate Stewardship (IBTrACS20) as input dataset for the Synthetic Tropical cyclOne geneRation Model (STORM). The development of this dataset has been described in detail in Bloemendaal, et al.12. Here, we provide a brief description of the STORM dataset, but for more details on the methodology and validation we direct readers to Bloemendaal, et al.12.Our approach is based on estimating the empirical RPs on basis of the synthetic TCs derived from the STORM dataset38 From this, autoregressive formulas model consecutive changes in the longitudinal/latitudinal position of the TC (in °), the minimum pressure (in hPa) and the maximum wind speed (in m/s) at every time step during a TC’s lifetime. In addition, STORM also simulates the size of the TC eye, represented via the radius to maximum winds (in km).The STORM dataset, a global synthetic dataset comprised of 10,000 years of synthetic TCs under present-climate conditions, is used for the calculation of the return periods (RPs). The STORM dataset was generated using STORM. This model takes the following IBTrACS data as input: the latitudinal and longitudinal position of the TC, maximum 10-meter 10-minute average sustained wind speeds (max U10), mean sea-level pressure (MSLP), and the size of the TC eye . Averaged environmental conditions are modeled using monthly-mean sea-surface temperatures (SST) and MSLP fields from ERA5.et al.12. Results show that STORM preserves the TC statistics as found in the IBTrACS input dataset, which indicates a good model performance. The average number of both genesis and landfalling events in the STORM dataset, as well as landfall intensity was found to closely correspond (within one standard deviation) to those in the IBTrACS dataset. The largest deviations in max U10 along a TC track were found to be approximately 2 m/s in the STORM dataset compared to the IBTrACS dataset.STORM is validated in Bloemendaal, 16, see Equation 1. The Weibull plotting formula has been demonstrated to be the best performing empirical formula for the estimation of return periods39.Using the 10,000 years of TC activity in the STORM dataset, we empirically calculate the max U10 for different RPs using Weibull’s plotting formulai. n is the total number of events in the set, and m the total length of the dataset , we fit five continuous extreme value distributions to the STORM dataset. These distributions include the Generalized Extreme Value, Exponential, Gumbel, Weibull, and Pareto distribution. Estimation of the optimal parameters for each of the distributions was done using Python’s et al.12, see Table The basin definitions used in this paper are adapted from Bloemendaal, 26 as an additional metric to communicate about wind speeds. The categorization on this scale, however, is done using 1-minute average sustained wind speeds, whereas the STORM wind data is given as a 10-minute average value. For this reason, we convert the 1-minute threshold values on the Saffir-Simpson scale to a 10-minute equivalent using a conversion factor of 0.8821, see Table We use the Saffir-Simpson Scale


Scyliorhinus canicula, a cartilaginous fish, shows active proliferation and neurogenesis. Here, we compared the morphology and proliferative status of the retina in catshark juveniles and adults. Histological and immunohistochemical analyses revealed an important reduction in the size of the peripheral retina (where progenitor cells are mainly located), a decrease in the thickness of the inner nuclear layer (INL), an increase in the thickness of the inner plexiform layer and a decrease in the cell density in the INL and in the ganglion cell layer in adults. Contrary to what has been reported in teleost fish, mitotic activity in the catshark retina was virtually absent after sexual maturation. Based on these results, we carried out RNA-Sequencing (RNA-Seq) analyses comparing the retinal transcriptome of juveniles and adults, which revealed a statistically significant decrease in the expression of many genes involved in cell proliferation and neurogenesis in adult catsharks. Our RNA-Seq data provides an excellent resource to identify new signaling pathways controlling neurogenesis in the vertebrate retina.Neurogenesis is the process by which progenitor cells generate new neurons. As development progresses neurogenesis becomes restricted to discrete neurogenic niches, where it persists during postnatal life. The retina of teleost fishes is thought to proliferate and produce new cells throughout life. Whether this capacity may be an ancestral characteristic of gnathostome vertebrates is completely unknown. Cartilaginous fishes occupy a key phylogenetic position to infer ancestral states fixed prior to the gnathostome radiation. Previous work from our group revealed that the juvenile retina of the catshark  Neurogenesis is the process by which multipotent neural stem cells (NSCs) generate new neurons. In the mammalian central nervous system (CNS), multipotent NSCs are known as apical progenitors and include neuroepithelial cells (NECs) that have limited capacity for self-renewal and divide symmetrically to generate more NECs, and apical radial glial cells (RGCs) that divide symmetrically or asymmetrically to generate neurons and glial cells, sometimes through secondary progenitors known as apical intermediate progenitor cells , which also contains progenitor cells , phosphohistone H3 (pH3), doublecortin (DCX), or glial fibrillary acidic protein (GFAP), though both DCX and GFAP also label postmitotic cells  study comparing the retinal transcriptomes of juveniles and adults to detect changes in the expression of genes involved in cell proliferation and neurogenesis, and to identify new genes and signaling pathways responsible for the neurogenic process in the retina of vertebrates.Here, we aimed to gain knowledge about the evolution of adult neurogenesis in the vertebrate retina by exploring this process in cartilaginous fishes with the catshark n = 17; 10–13 cm long) and adult specimens , or rabbit polyclonal anti-DCX . Sections were rinsed three times in TBS for 10 min each, and incubated with the fluorescent dye-labeled secondary antibodies Cy3-conjugated goat anti-rabbit  and FITC-conjugated goat anti-mouse  for 1 h at RT. All antibody dilutions were made in TBS containing 15% normal goat serum (Millipore), 0.2% Triton X-100 (Sigma), and 2% BSA (Sigma). Sections were then rinsed three times in TBS for 10 min each and in distilled water for 30 min, allowed to dry for 30 min at 37°C, and mounted in MOWIOL 4-88 Reagent .S. canicula  experiments were carried out to study the expression of S. canicula Sox2 (ScSox2) transcripts using the probe described in Lagadec et al. . ISH was performed on cryostat sections (18 μm) of juvenile and adult retinas as previously described . Brightfield images were obtained with an Olympus BX51 microscope equipped with an Olympus DP71 camera. Contrast and brightness were minimally adjusted using Adobe Photoshop CS4 .n = 3 retinas from three different juveniles; n = 3 retinas from three different adults) using Image J  and inner plexiform layer (IPL), and cell density of the INL and ganglion cell layer (GCL) were quantified in haematoxylin-eosin-stained retinal sections  and adults . The number of pH3+ cells and PCNA+ cells were manually counted under the microscope in one out of each four consecutive retinal sections (18 μm). The limit between the peripheral and the central retina was established based on morphological differences like the characteristic layered structure of the central retina. Then, we calculated the mean number of cells per section for each retina.We quantified the number of mitotic [pH3 positive (pH3+) cells] in the peripheral retina (CMZ and TZ) and proliferative cells (PCNA+ cells) in the whole central retina of juveniles (p < 0.05) between juveniles and adults, a Mann-Whitney test was used for non-normally distributed data (only the pH3+ data) and a Student's (unpaired) t-test was used for normally distributed data.Statistical analyses were performed with Prism 8 . Normality of the data was determined with the Shapiro-Wilk test. To determine significant differences  and adults  were dissected out and put in RNAlater . RNA extraction was performed using the RNeasy mini kit  with DNase treatment following the manufacturer's instructions. Isolated RNAs were eluted in nuclease free water. RNA quality and quantity were evaluated in a Bioanalyzer  and in a NanoDrop® ND-1000 spectrophotometer . Thereafter, the Illumina Truseq mRNA stranded RNA-Seq Library Prep Kit protocol was followed. Libraries were checked for quality and quantified using the Bioanalyzer 2100  , before being sequenced on one S1 lane of the Illumina NovaSeq instrument using 150 base paired-end sequencing at Edinburgh Genomics (UK). Raw reads have been deposited in NCBI's Sequence Read Archive (SRA) under BioProject accession number PRJNA668789.The retinas of juveniles (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Quality filtering and removal of residual adaptor sequences was conducted on read pairs using Fastp v.0.20.0 . Gene count data were used to estimate differential gene expression using the Bioconductor package DESeq2 v.3.4  analyses were performed using R v.3.6.2 (p = 0.0142). As previously reported , an increase in the thickness of the IPL (p = 0.0231) and a significant decrease in cell density in the INL and GCL .The adult retina increased in size respect to the juvenile retina as revealed by area quantification in retinal sections  and the neural stem and progenitor cell marker Sox2.To better define the border of the peripheral retina, where the main retinal neurogenic niche in In the juvenile retina, GFAP expression was observed in processes of progenitor cells in the peripheral retina  and in mIn adults , the expScSox2 in situ labeling allowed us to clearly establish the boundary between the CMZ and TZ within the peripheral retina in juvenile specimens . Here, we compared the proliferative status and mitotic activity of juvenile and adult catshark retinas using PCNA and pH3 double immunolabeling. As previously reported  in the peripheral retina of adults  and proliferating (PCNA+) cells revealed significant differences in the proliferative capacity of juvenile and adult retinas. There was a statistically significant decrease in the number of pH3+ cells , Ki67, N-myc, Otx2, Foxo1, Olig2, Ins1b, Mcm2, Meis2, Zic2, H2b2e, H3.2, Eomes (Tbr2) or Sox family factors like Sox8 or Sox11  also showed differential expression (Genes showing decreased expression in the adult retina (a positive fold change indicates decreased expression in adults) are good candidates to be pro-neurogenic and responsible for the higher proliferative activity of the juvenile retina. Actually, many of the genes that showed decreased expression in the adult retina [e.g., several cyclins , we also observed significant changes in the expression of progenitor markers. The number of GFAP+ and Shh, Wnt, Notch or Slit/Robo signaling  can be found at: The animal study was reviewed and approved by Bioethics Committee of the University of Santiago de Compostela.IH-N, FA, AB-I, and EC: conceived and devised the study, approved the article, and study concept and design. IH-N, SM, LS, HM, and DR: acquisition of data. IH-N, DR, FA, AB-I, and EC: analysis and interpretation of data and drafting of the manuscript. IH-N, SM, LS, HM, DR, FA, AB-I, and EC: critical revision of the manuscript. IH-N and EC: obtained funding. All authors had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Are the measures used in standard hearing assessments reliable in individuals with mild dementia?This cross-sectional study that included 15 adults with mild dementia and 32 adults with normal cognitive function found high test-retest reliability for hearing thresholds, hearing handicap assessment, and several physiological measures typically included in a standard audiology test battery.This study suggests that hearing assessments completed under ideal conditions are reliable in adults with mild dementia. Accurate assessment of hearing is critically important regardless of a person’s cognitive ability. The degree to which hearing can be reliably measured in adults with mild dementia has not been determined.To obtain quantitative measures of reliability to evaluate the degree to which audiologic testing can be accurately conducted in older adults with mild dementia.This repeated-measures cross-sectional study consisted of a comprehensive audiologic assessment on 2 occasions separated by 1 to 2 weeks performed in the department of otolaryngology at the Washington University School of Medicine from December 3, 2018, to March 4, 2020. Participants were 15 older adults with a verified diagnosis of mild dementia and 32 older adults without a verified diagnosis of mild dementia who were recruited from the Knight Alzheimer Disease Research Center at Washington University in St Louis.Test-retest reliability was assessed for tympanometry, acoustic reflex thresholds, otoacoustic emissions, hearing sensitivity, speech reception threshold, speech perception in noise, and hearing handicap, using standard clinical audiology measures.r = 0.84 ) and for the group with mild dementia . For hearing thresholds, all rank-order correlations were above 0.80 with 95% CIs at or below 15% in width, with the exception of a moderate correlation of bone conduction thresholds at 500 Hz for the group with normal cognitive function  and slightly wider 95% CIs for low-frequency bone conduction thresholds for both groups. For speech reception thresholds, correlations were high for groups with normal cognitive function  and mild dementia .A total of 47 older adults , including 32 with normal cognitive function and 15 with very mild or mild dementia, completed the study protocol. For participants with mild dementia, high test-retest reliability (Spearman ρ > 0.80) was found for most measures typically included in a comprehensive audiometric evaluation. For acoustic reflex thresholds, agreement was moderate to high, averaging approximately 83% across frequencies for both groups. Scores for the screening Hearing Handicap Inventory for the Elderly at time 1 and time 2 were highly correlated for the group with normal cognitive function (Test-retest reliability for hearing measures obtained from participants with mild dementia was comparable to that obtained from cognitively normal participants. These findings suggest that mild cognitive impairment does not preclude accurate audiologic assessment. This cross-sectional study obtains quantitative measures of reliability to evaluate the degree to which audiologic testing can be accurately conducted for older adults with mild dementia. Listening to and understanding speech, particularly in noisy environments, can be frustrating, effortful, and often impossible for individuals with age-related hearing loss. For listeners who are also experiencing pathologic changes in cognition associated with dementia, these situations may be even more discouraging and difficult to manage. Because of the potential for increased communicative difficulty for adults with concurrent age-related hearing loss and dementia, and a possible association between hearing loss and cognitive decline,6 there is a critical need to establish the accuracy of hearing measurements in listeners with dementia.Age-related hearing loss is highly prevalent and has far-reaching health, emotional, and social consequences.Assessment of hearing loss typically includes a battery of physiological and behavioral measures with results of outer, middle, and inner ear health that audiologists use to inform individualized treatment plans. Several measures do not require active participation by the patient, such as middle ear testing via tympanometry and acoustic reflexes and inner ear assessment via otoacoustic emissions. However, because hearing is a perceptual process, the criterion standard for the assessment of hearing sensitivity—audiometry—requires active and interactive behavioral responses from patients.9 However, it has long been appreciated that individual differences in cognitive abilities may affect test results.10 For example, in pediatric audiology, clinicians significantly modify standard test procedures in anticipation of children’s short attention spans and developmental limitations. Visual reinforcement audiometry (for infants and toddlers) and conditioned play audiometry (for children between 2 and 5 years of age) use toys and conditioned responses in place of standard “hand raise” voluntary responses. In addition, making the test more dynamic by switching ears often and prioritizing testing from 500 to 4000 Hz increases children’s engagement and provides clinicians with information about hearing sensitivity most important for speech.11 Furthermore, the association between acoustic challenge and cognitive effort12 raises the concern that listeners with both hearing loss and cognitive difficulty may struggle to adequately perform auditory tasks involving decision-making.In listeners without dementia, the pure-tone audiogram is generally presumed to have good reliability.14 or standard pure-tone audiometry.15 However, to our knowledge, there is a lack of information regarding how dementia may affect the ability to accurately assess hearing.16 Self-reported measures, which are only moderately correlated with hearing thresholds,17 may not be ideal for listeners with dementia, as previous studies indicate that reliable self-reported health measures may be difficult to obtain in this population.18 It is also possible that standard pure-tone audiometry might be challenging for individuals with dementia because difficulty following instructions, increased irritability, and memory deficits are hallmarks of cognitive decline.Studies evaluating the association between hearing loss and dementia typically quantify hearing abilities using self-reported hearing measuresIn this context, then, it is important to assess whether individuals with dementia, who may be experiencing a decline in memory and introspection as well as increased agitation and confusion, might also struggle to reliably respond during hearing assessments that require attentive behavioral responses. To address these issues, we examined the test-retest reliability of several audiologic measures in listeners with normal cognitive function and with mild dementia. We hypothesized that mild dementia would negatively affect the reliability of pure-tone audiometry, speech in quiet thresholds, speech in noise thresholds, and self-reported hearing handicap, all of which require active participation. Our goal was to obtain quantitative measures of reliability to evaluate the degree to which audiologic testing can be accurately conducted in older adults with mild dementia.Participants were recruited from the Charles F. and Joanne Knight Alzheimer Disease Research Center at the Washington University School of Medicine, St Louis, Missouri. Participants completed written informed consent and were paid $90 for their time. The study was approved by the Washington University Institutional Review Board.20 The mean (SD) amount of time between CDR assessment and participation in the study was 9.1 (4.3) months . Participants with neurologic diagnoses other than Alzheimer disease dementia or who were unable to read a computer screen with corrected vision were excluded. Prior to this study, participants were evaluated at the Knight Alzheimer Disease Research Center and assigned Clinical Dementia Ratings (CDRs) through structured interviews with the participant and their coparticipant . The CDR Dementia Staging Instrument classifies dementia severity on a 5-point scale .The following measures were completed from December 3, 2018, to March 4, 2020, at 2 sessions (time 1 and time 2) separated by 7 to 14 days . Testing time was limited to 1 hour and 20 minutes. With the exception of the screening hearing handicap survey, which was completed at the beginning of each session, all physiological measures were completed prior to behavioral measures and in the order listed below. All measures were administered in a sound-attenuating booth.Otoscopy was used to assess the presence of obstructing cerumen or abnormal tympanic membrane appearance. A cerumen impaction was identified in 1 participant who was referred to their primary care physician for cerumen management. They were rescheduled, and on return, otoscopy revealed clear canals bilaterally.Left and right ear tympanogram peak pressure, peak compensated static acoustic admittance, and equivalent ear canal volume were measured with an Interacoustics Titan impedance module (Interacoustics A/S), using a standard 226-Hz probe tone.Left and right ear distortion product otoacoustic emissions were obtained using the Interacoustics Titan distortion product otoacoustic emission module. Emissions were measured at 0.75, 1, 2, 3, 4, 6, and 8 kHz with a tone level of 65 dB sound pressure level and an F2 to F1 ratio of 1.22. Responses were considered present if the response level was −10 dB or more and the signal to noise ratio was more than 7.Ipsilateral and contralateral left and right ear acoustic reflex thresholds were obtained at 0.5, 1, 2, and 4 kHz with the Interacoustics Titan impedance module. A reflex was considered present if the downward deflection reached 0.02 mL at a given frequency.22 consisting of 10 questions regarding the impact of perceived hearing loss on daily communicative function. Participants answered never , sometimes , or always  to questions such as “Does a hearing problem cause you to feel embarrassed when meeting new people?” The possible total score range was 0 (no hearing handicap) to 40 (significant hearing handicap).Participants completed the screening version of the Hearing Handicap Inventory for the Elderly,23 with a GSI 61 audiometer or Audiostar Pro audiometer (Grason-Stadler). We modified the standard audiometric test order based on pediatric audiology best practices.11 Specifically, testing began in the participant’s better ear (if one was specified) at 2 kHz. After a threshold was established for the better ear, the poorer ear was tested at the same frequency. This procedure was followed for subsequent frequencies, in the following order: 0.5, 1, and 4 kHz  W-1 spondee words using recorded materials  or with monitored live voice (39 participants).25 Speech reception thresholds were then obtained first for the better ear and then for the poorer ear.Speech reception thresholds were obtained for left and right ears using standard clinical procedures.Speech perception in noise was assessed using the Quick Speech in Noise Test . Materials were routed to the audiometer from an external compact disc player (GSI 61) or integrated with the audiometer (Audiostar Pro). All materials were calibrated based on manufacturers’ specifications. Two QuickSIN lists were presented at each session . Presentation levels were based on the instructions from the test manual. In brief, for participants with a better ear pure-tone average of 45 dB in hearing level (HL) or lower, 70 dB HL was used as the presentation level. This level was adjusted upward to a perceptual “loud but comfortable” level above 70 dB HL for participants with a pure-tone average of 50 dB HL or higher. Signal to noise ratio loss was estimated for each participant by averaging the scores for the 2 lists.26 Data were analyzed in R, version 3.6.3 .27 Data were checked for normality and outliers, defined as scores more than 1.5 times the interquartile range. Analyses were conducted with and without outliers, and outliers are described for each measure in the sections below. With the exception of the QuickSIN speech perception in noise measure, there were no significant changes in overall results with outliers removed, and they were subsequently retained in the final analyses. QuickSIN results are reported with outliers removed. Changes in variances and mean values from time 1 to time 2 for each group were assessed for each measure. Test results were not significant at P < .05 with the exception of tympanogram peak pressure, which showed significant differences in variance from time 1 to time 2 for both groups.26Data and analysis scripts are available online.28). As is commonly reported, we treated left ear and right ear measures as being independent. However, because left and right ear hearing sensitivity measures are in fact correlated, we conducted follow-up analyses on single-ear data; in all cases, the single-ear results were compatible with the combined data.26 For measures analyzing left and right ears independently, the sample included 64 ears in the group with normal cognitive function and 30 ears in the group with mild dementia, unless otherwise specified.Because of deviations from normality, Spearman rank-order correlations were used for all analyses. To further evaluate the precision of the reliability estimates, 95% CIs were calculated for each measure using bootstrap resampling , including 32 (18 women) with normal cognitive function (CDR 0), and 15 (8 women) with a diagnosis of very mild or mild dementia  completed the study protocol. All participants completed both sessions within the allotted time, with the exception of 1 individual in the group with mild dementia. This participant required frequent task reinstruction. As a result, the final 2 (8 and 0.25 kHz) air conduction thresholds were not assessed owing to time constraints at time 1. However, the participant completed all measures within the allotted time at time 2.Measures at time 2 were not obtained for 2 ears in the group with mild dementia, 1 owing to inability to maintain a seal and 1 with no identifiable peak in pressure or admittance (without cerumen obstruction). Subsequently, 28 ears were included in the correlations for peak pressure, 28 for static admittance, and 29 for ear canal volume.r = 0.35 ) and moderately correlated for the group with mild dementia . Although correlations were not high and there were significant differences in variance from time 1 to time 2 for each group (as previously discussed), all ears were within clinically defined normal limits (−150 to 25 daPa) with the exception of 6 ears in the control group that were only slightly outside that range.26Ear canal volume and static admittance at time 1 and time 2 were highly correlated for both groups, with Spearman ρ > 0.80 for each correlation and with 95% CI widths between 10% and 20% around the point estimates. However, peak pressure from time 1 to time 2 was weakly correlated for the group with normal cognitive function  and absent (0) to assess percentage agreement between time 1 and time 2. Percentage agreement was calculated for left and right ear, ipsilateral and contralateral thresholds at each frequency. Agreement was moderate to high, averaging approximately 83% across frequencies for both groups .Responses were coded as present (1) and absent (0) to assess percentage agreement between time 1 and time 2. Percentage agreement was high for both groups, ranging from approximately 78% to 100%. The lowest agreement was seen in the low frequencies and likely reflects interference of low-frequency background noise .r = 0.84 ) and for the group with mild dementia , indicating good test-retest reliability.Scores for the screening Hearing Handicap Inventory for the Elderly at time 1 and time 2 were highly correlated for the group with normal cognitive function , middle- , and high-frequency (6 and 8 kHz) ranges, as well as bone conduction thresholds , were used in the analysis. One participant with normal cognitive function had asymmetric hearing loss with no measurable hearing in 1 ear; that ear was excluded from all analyses. One ear in the group with normal cognitive function and 1 ear in the group with mild dementia were excluded from the air conduction high-frequency pure-tone average analysis owing to those 2 participants having no measurable hearing at 6 and 8 kHz. One ear in the group with normal cognitive function was excluded from bone conduction for 1 and 4 kHz owing to failure to mask and no response at system limits, respectively. One, 2, and 5 ears in the group with mild dementia were excluded from bone conduction for 0.5, 2, and 4 kHz, respectively, owing to no response at system limits (7 ears) and failure to mask (1 ear).r = 0.69 ) and slightly wider 95% CIs for low-frequency bone conduction thresholds for both groups. These results indicate good test-retest reliability of hearing thresholds for both groups. The mean dB HL difference between time 1 and time 2 was under 5 dB at all frequencies for air and bone conduction thresholds, for both groups.26Scatterplots showing low-, middle-, and high-frequency air conduction thresholds and bone conduction thresholds at time 2 as a function of time 1 are shown in r = 0.91 ) and mild dementia , indicating good test-retest reliability for both groups  but was high for the group with mild dementia . The results observed for the group with normal cognitive function are likely due to restricted variance  and having QuickSIN scores identified as outliers at time 1 or time 2 (3 participants).The goal of this study was to assess the reliability of standard audiologic measures for individuals with mild dementia. We anticipated that mild dementia might negatively affect the reliability of pure tone, speech in quiet and speech in noise thresholds, and self-reported hearing handicap, which all require active participation for testing and could be affected by the cognitive consequences of mild dementia. We found test-retest reliability to be comparably high between the groups with and without mild dementia. Although our sample size was limited and the results should be interpreted with caution, the 95% CIs surrounding the reliability point estimates were generally in the range of 10% to 20%, meaning that we expect larger samples to show similar reliability. Our results suggest that interactions between hearing loss and mild dementia do not appear to affect the accurate assessment of key measures of hearing sensitivity, auditory function, and self-reported hearing handicap.We maximized best-practice procedures for hearing assessment in this protocol in several ways. All measures were performed in a sound-attenuating booth with good lighting and little visual or auditory distractors. The accuracy and reliability of assessments in noisier or more visually intrusive environments, however, may be significantly diminished. In addition, we reorganized the standard audiologic test order, prioritizing ear-specific thresholds at an abbreviated number of frequencies. It is possible that reordering frequencies increased the salience of the pure tones by frequently switching from ear to ear and roving in frequency. Reliability may be reduced when standard protocols assess a single ear at a time for all frequencies and ascend or descend in frequency in predictable octave steps. The potential consequences of these changes require further examination.16 many included participants with moderate to severe dementia. We limited our focus to those with mild dementia (CDR 0.5 and 1) and have identified hearing assessments to be reliable for individuals in the early stages of dementia progression. Our findings emphasize the importance of hearing loss screening and diagnosis for older adults before dementia symptoms become more severe, at which time an individual’s ability to participate in hearing assessments may be affected. Future studies are needed to address how more severe dementia symptoms may affect the accuracy and reliability of audiologic assessments.Although some prior studies suggested difficulties assessing hearing sensitivity in individuals with dementia,The sample size was limited, so our results should be interpreted with caution; however, we are confident that results would be comparable in a larger sample. The current study only measured the reliability of hearing measures for adults with mild dementia. Therefore, this study does not provide a complete picture of how symptoms of more advanced dementia may interact with the ability to assess hearing. Future studies are warranted.In this study, mild dementia and associated symptoms did not appear to affect the reliability of measures commonly included in a standard audiometric test battery, when performed under ideal conditions. Observing no significant group differences may initially seem less compelling than finding large group differences. However, we argue that our findings are as powerful, if not more so, than if we would have found reduced reliability for the dementia group. There have been many studies that have used audiometry and self-reported hearing measures to examine the association between hearing loss and dementia. The accuracy of these findings is predicated on the assumption that the measures are reliable for those participants. Given that audiometry requires participants to engage their attention, executive function, and short-term memory, all of which are specifically affected by cognitive changes associated with mild or worse dementia, it is essential to establish the measures’ reliability. Our findings support the continued use of these measures for adults with mild dementia, for both clinical and research purposes.Future studies need to address the possibility that, as dementia symptoms worsen, it may become more difficult to administer auditory tests, particularly those that require active participation. We hope that our findings also encourage other researchers to consider reliability in a variety of populations and set an example for how testing and measurement might be approached. Having confidence in the measures used to assess auditory function in adults with dementia is critical for clinicians, in order to provide optimal hearing health care, and for researchers, when examining the potential link between dementia and hearing loss to ensure the association between the two is not confounded by poor test reliability.