Auditory Tests for Characterizing Hearing Deficits in Listeners With Various Hearing Abilities: The BEAR Test Battery

Sentence recognition with modulation-filtered speech segments for younger and older adults: Effects of hearing impairment and cognition

This study investigated word recognition for sentences temporally filtered within and across acoustic-phonetic segments providing primarily vocalic or consonantal cues. Amplitude modulation was filtered at syllabic (0-8 Hz) or slow phonemic (8-16 Hz) rates. Sentence-level modulation properties were also varied by amplifying or attenuating segments. Participants were older adults with normal or impaired hearing. Older adult speech recognition was compared to groups of younger normal-hearing adults who heard speech unmodified or spectrally shaped with and without threshold matching noise that matched audibility to hearing-impaired thresholds. Participants also completed cognitive and speech recognition measures. Overall, results confirm the primary contribution of syllabic speech modulations to recognition and demonstrate the importance of these modulations across vowel and consonant segments. Group differences demonstrated a hearing loss-related impairment in processing modulation-filtered speech, particularly at 8-16 Hz. This impairment could not be fully explained by age or poorer audibility. Principal components analysis identified a single factor score that summarized speech recognition across modulation-filtered conditions; analysis of individual differences explained 81% of the variance in this summary factor among the older adults with hearing loss. These results suggest that a combination of cognitive abilities and speech glimpsing abilities contribute to speech recognition in this group.

Impact of hearing aid technology level at first-fit on self-reported outcomes in patients with presbycusis: a randomized controlled trial

To provide clinical guidance in hearing aid prescription for older adults with presbycusis, we investigated differences in self-reported hearing abilities and hearing aid effectiveness for premium or basic hearing aid users. Secondly, as an explorative analysis, we investigated if differences in gain prescription verified with real-ear measurements explain differences in self-reported outcomes. The study was designed as a randomized controlled trial in which the patients were blinded towards the purpose of the study. In total, 190 first-time hearing aid users (>60 years of age) with symmetric bilateral presbycusis were fitted with either a premium or basic hearing aid. The randomization was stratified on age, sex, and word recognition score. Two outcome questionnaires were distributed: the International Outcome Inventory for Hearing Aids (IOI-HA) and the short form of the Speech, Spatial, and Qualities of Hearing Scale (SSQ-12). In addition, insertion gains were calculated from real-ear measurements at first-fit for all fitted hearing aids. Premium hearing aid users reported 0.7 (95%CI: 0.2; 1.1) scale points higher total SSQ-12 score per item and 0.8 (95%CI: 0.2; 1.4) scale points higher speech score per item, as well as 0.6 (95%CI: 0.2; 1.1) scale points higher qualities score compared to basic-feature hearing aid users. No significant differences in reported hearing aid effectiveness were found using the IOI-HA. Differences in the prescribed gain at 1 and 2 kHz were observed between premium and basic hearing aids within each company. Premium-feature devices yielded slightly better self-reported hearing abilities than basic-feature devices, but a statistically significant difference was only found in three out of seven outcome variables, and the effect was small. The generalizability of the study is limited to community-dwelling older adults with presbycusis. Thus, further research is needed for understanding the potential effects of hearing aid technology for other populations. Hearing care providers should continue to insist on research to support the choice of more costly premium technologies when prescribing hearing aids for older adults with presbycusis. Clinical Trial Registration: https://register.clinicaltrials.gov/, identifier NCT04539847.

Predicting Aided Outcome With Aided Word Recognition Scores Measured With Linear Amplification at Above-conversational Levels

OBJECTIVES

Many hearing aid (HA) users receive limited benefit from amplification, especially when trying to understand speech in noise, and they often report hearing-related residual activity limitations. Current HA fitting strategies are typically based on pure-tone hearing thresholds only, even though suprathreshold factors have been linked to aided outcomes. Furthermore, clinical measures of speech perception such as word recognition scores (WRSs) are performed without frequency-specific amplification, likely resulting in suboptimal speech audibility and thus inaccurate estimates of suprathreshold hearing abilities. Corresponding measures with frequency-specific amplification ("aided") would likely improve such estimates and enable more accurate aided outcome prediction. Here, we investigated potential links between either unaided WRSs or aided WRSs measured at several above-conversational levels and two established HA outcome measures: The Hearing-In-Noise Test (HINT) and the International Outcome Inventory for Hearing Aids (IOI-HA).

DESIGN

Thirty-seven older individuals with bilateral hearing impairments participated. Two conditions were tested: unaided and aided, with all stimuli presented over headphones. In the unaided condition, the most comfortable level (MCL) for the presented speech stimuli, WRS at MCL+10 dB as well as uncomfortable levels (UCLs) for narrowband noise stimuli were measured. In the aided condition, all stimuli were individually amplified according to the "National Acoustic Laboratories-Revised, Profound" fitting rule. Aided WRSs were then measured using an Interacoustics Affinity system at three above-conversational levels, allowing for the maximum aided WRS as well as the presence of "rollover" in the performance-intensity function to be estimated. Multivariate data analyses were performed to examine the relations between the HINT (measured using a simulated HA with the NAL-RP amplification) or IOI-HA scores (for the participants' own HAs) and various potential predictors (age, pure-tone average hearing loss, unaided WRS, aided WRS, rollover presence [ROp], and UCL).

RESULTS

Aided WRSs predicted the HINT scores better than any other predictor and were also the only significant predictor of the IOI-HA scores. In addition, UCL and ROp in the aided WRSs were significant predictors of the HINT scores and competed for variance in the statistical models. Neither age nor pure-tone average hearing loss could predict the two aided outcomes.

CONCLUSIONS

Aided WRSs can predict HA outcome more effectively than unaided WRSs, age or pure-tone audiometry and could be relatively easily implemented in clinical settings. More research is necessary to better understand the relations between ROp, UCL and speech recognition at above-conversational levels.

Genetic Hearing Loss Affects Cochlear Processing

The relationship between speech recognition and hereditary hearing loss is not straightforward. Underlying genetic defects might determine an impaired cochlear processing of sound. We obtained data from nine groups of patients with a specific type of genetic hearing loss. For each group, the affected cochlear site-of-lesion was determined based on previously published animal studies. Retrospectively obtained speech recognition scores in noise were related to several aspects of supra-threshold cochlear processing as assessed by psychophysical measurements. The differences in speech perception in noise between these patient groups could be explained by these factors and partially by the hypothesized affected structure of the cochlea, suggesting that speech recognition in noise was associated with a genetics-related malfunctioning of the cochlea. In particular, regression models indicate that loudness growth and spectral resolution best describe the cochlear distortions and are thus a good biomarker for speech understanding in noise.

A flexible data-driven audiological patient stratification method for deriving auditory profiles

For characterizing the complexity of hearing deficits, it is important to consider different aspects of auditory functioning in addition to the audiogram. For this purpose, extensive test batteries have been developed aiming to cover all relevant aspects as defined by experts or model assumptions. However, as the assessment time of physicians is limited, such test batteries are often not used in clinical practice. Instead, fewer measures are used, which vary across clinics. This study aimed at proposing a flexible data-driven approach for characterizing distinct patient groups (patient stratification into auditory profiles) based on one prototypical database (N = 595) containing audiogram data, loudness scaling, speech tests, and anamnesis questions. To further maintain the applicability of the auditory profiles in clinical routine, we built random forest classification models based on a reduced set of audiological measures which are often available in clinics. Different parameterizations regarding binarization strategy, cross-validation procedure, and evaluation metric were compared to determine the optimum classification model. Our data-driven approach, involving model-based clustering, resulted in a set of 13 patient groups, which serve as auditory profiles. The 13 auditory profiles separate patients within certain ranges across audiological measures and are audiologically plausible. Both a normal hearing profile and profiles with varying extents of hearing impairments are defined. Further, a random forest classification model with a combination of a one-vs.-all and one-vs.-one binarization strategy, 10-fold cross-validation, and the kappa evaluation metric was determined as the optimal model. With the selected model, patients can be classified into 12 of the 13 auditory profiles with adequate precision (mean across profiles = 0.9) and sensitivity (mean across profiles = 0.84). The proposed approach, consequently, allows generating of audiologically plausible and interpretable, data-driven clinical auditory profiles, providing an efficient way of characterizing hearing deficits, while maintaining clinical applicability. The method should by design be applicable to all audiological data sets from clinics or research, and in addition be flexible to summarize information across databases by means of profiles, as well as to expand the approach toward aided measurements, fitting parameters, and further information from databases.

Revisiting Auditory Profiling: Can Cognitive Factors Improve the Prediction of Aided Speech-in-Noise Outcome?

Hearing aids (HA) are the most common type of rehabilitation treatment for age-related hearing loss. However, HA users often obtain limited benefit from their devices, particularly in noisy environments, and thus many HA candidates do not use them at all. A possible reason for this could be that current HA fittings are audiogram-based, that is, they neglect supra-threshold factors. In an earlier study, an auditory-profiling method was proposed as a basis for more personalized HA fittings. This method classifies HA users into four profiles that differ in terms of hearing sensitivity and supra-threshold hearing abilities. Previously, HA users belonging to these profiles showed significant differences in terms of speech recognition in noise but not subjective assessments of speech-in-noise (SIN) outcome. Moreover, large individual differences within some profiles were observed. The current study therefore explored if cognitive factors can help explain these differences and improve aided outcome prediction. Thirty-nine older HA users completed sets of auditory and SIN tests as well as two tablet-based cognitive measures (the Corsi block-tapping and trail-making tests). Principal component analyses were applied to extract the dominant sources of variance both within individual tests producing many variables and within the three types of tests. Multiple linear regression analyses performed on the extracted components showed that auditory factors were related to aided speech recognition in noise but not to subjective SIN outcome. Cognitive factors were unrelated to aided SIN outcome. Overall, these findings provide limited support for adding those two cognitive tests to the profiling of HA users.