Daily sound exposure of hearing aids users during COVID-19 pandemic in Europe.

Introduction: This study aimed to investigate the daily sound exposure of hearing aid (HA) users during the COVID-19 pandemic, with a specific focus on the impact of different governance intervention levels. Methods: Modern HA technology was employed to measure and compare the sound exposure of HA users in three distinct periods: pre-pandemic, and two 14-day periods during the pandemic, corresponding to varying levels of governance interventions. The study sample comprised a total of 386 HA users in Europe during the pandemic, with daily sound exposure data collected as part of the main dataset. Results: The results revealed that, during the pandemic, the equivalent continuous sound pressure level (SPL) experienced by HA users decreased, while the signal-to-noise ratio (SNR) increased compared to the pre-pandemic period. Notably, this impact was found to be more pronounced (p < 0.05) when individuals were subjected to stronger governance intervention levels, characterized by lower SPL and higher SNR. Discussion: This study highlights the changes in daily sound exposure experienced by HA users during the COVID-19 pandemic, particularly influenced by the extent of governance interventions that restricted social activities. These findings emphasize the importance of considering the effects of pandemic-related governance measures on the sound environments of HA users and have implications for audiological interventions and support strategies during similar crises.

Real-World Hearing Aid Usage Patterns and Smartphone Connectivity.

Data for monitoring individual hearing aid usage has historically been limited to retrospective questionnaires or data logged intrinsically in the hearing aid cumulatively over time (e. g., days or more). This limits the investigation of longitudinal interactions between hearing aid use and environmental or behavioral factors. Recently it has become possible to analyze remotely logged hearing aid data from in-market and smartphone compatible hearing aids. This can provide access to novel insights about individual hearing aid usage patterns and their association to environmental factors. Here, we use remotely logged longitudinal data from 64 hearing aid users to establish basic norms regarding smartphone connectivity (i.e., comparing remotely logged data with cumulative true hearing aid on-time) and to assess whether such data can provide representative information about ecological usage patterns. The remotely logged data consists of minute-by-minute timestamped logs of cumulative hearing aid on-time and characteristics of the momentary acoustic environment. Using K-means clustering, we demonstrate that hourly hearing aid usage patterns (i.e., usage as minutes/hour) across participants are separated by four clusters that account for almost 50% of the day-to-day variation. The clusters indicate that hearing aids are worn either sparsely throughout the day; early morning to afternoon; from noon to late evening; or across the day from morning to late evening. Using linear mixed-effects regression modeling, we document significant associations between daily signal-to-noise, sound intensity, and sound diversity with hearing aid usage. Participants encounter louder, noisier, and more diverse sound environments the longer the hearing aids are worn. Finally, we find that remote logging via smartphones underestimates the daily hearing aid usage with a pooled median of 1.25 h, suggesting an overall connectivity of 85%. The 1.25 h difference is constant across days varying in total hearing aid on-time, and across participants varying in average daily hearing aid-on-time, and it does not depend on the identified patterns of daily hearing aid usage. In sum, remote data logging with hearing aids has high representativeness and face-validity, and can offer ecologically true information about individual usage patterns and the interaction between usage and everyday contexts.

The everyday acoustic environment and its association with human heart rate: evidence from real-world data logging with hearing aids and wearables.

We investigate the short-term association between multidimensional acoustic characteristics of everyday ambient sound and continuous mean heart rate. We used in-market data from hearing aid users who logged ambient acoustics via smartphone-connected hearing aids and continuous mean heart rate in 5 min intervals from their own wearables. We find that acoustic characteristics explain approximately 4% of the fluctuation in mean heart rate throughout the day. Specifically, increases in ambient sound pressure intensity are significantly related to increases in mean heart rate, corroborating prior laboratory and short-term real-world data. In addition, increases in ambient sound quality-that is, more favourable signal to noise ratios-are associated with decreases in mean heart rate. Our findings document a previously unrecognized mixed influence of everyday sounds on cardiovascular stress, and that the relationship is more complex than is seen from an examination of sound intensity alone. Thus, our findings highlight the relevance of ambient environmental sound in models of human ecophysiology.

EHealth and Its Role in Supporting Audiological Rehabilitation: Patient Perspectives on Barriers and Facilitators of Using a Personal Hearing Support System With Mobile Application as Part of the EVOTION Study.

BACKGROUND: Hearing loss is a major public health challenge. Audiology services need to utilise a range of rehabilitative services and maximise innovative practice afforded by technology to actively promote personalized, participatory, preventative and predictive care if they are to cope with the social and economic burden placed on the population by the rapidly rising prevalence of hearing loss. Digital interventions and teleaudiology could be a key part of providing high quality, cost-effective, patient-centred management. There is currently very limited evidence that assesses the hearing impaired patient perspective on the acceptance and usability of this type of technology. AIM: This study aims to identify patient perceptions of the use of a hearing support system including a mobile smartphone app when used with Bluetooth-connected hearing aids across the everyday life of users, as part of the EVOTION project. METHODS: We applied a questionnaire to 564 participants in three countries across Europe and analysed the following topics: connectivity, hearing aid controls, instructional videos, audiological tests and auditory training. KEY FINDINGS: Older users were just as satisfied as younger users when operating this type of technology. Technical problems such as Bluetooth connectivity need to be minimised as this issue is highly critical for user satisfaction, engagement and uptake. A system that promotes user-controllability of hearing aids that is more accessible and easier to use is highly valued. Participants are happy to utilise monitoring tests and auditory training on a mobile phone out of the clinic but in order to have value the test battery needs to be relevant and tailored to each user, easy to understand and use. Such functions can elicit a negative as well as positive experience for each user. CONCLUSION: Older and younger adults can utilise an eHealth mobile app to complement their rehabilitation and health care. If the technology works well, is tailored to the individual and in-depth personalised guidance and support is provided, it could assist maximisation of hearing aid uptake, promotion of self-management and improving outcomes.

Application of Big Data to Support Evidence-Based Public Health Policy Decision-Making for Hearing.

Ideally, public health policies are formulated from scientific data; however, policy-specific data are often unavailable. Big data can generate ecologically-valid, high-quality scientific evidence, and therefore has the potential to change how public health policies are formulated. Here, we discuss the use of big data for developing evidence-based hearing health policies, using data collected and analyzed with a research prototype of a data repository known as EVOTION (EVidence-based management of hearing impairments: public health pOlicy-making based on fusing big data analytics and simulaTION), to illustrate our points. Data in the repository consist of audiometric clinical data, prospective real-world data collected from hearing aids and an app, and responses to questionnaires collected for research purposes. To date, we have used the platform and a synthetic dataset to model the estimated risk of noise-induced hearing loss and have shown novel evidence of ways in which external factors influence hearing aid usage patterns. We contend that this research prototype data repository illustrates the value of using big data for policy-making by providing high-quality evidence that could be used to formulate and evaluate the impact of hearing health care policies.

Electrophysiological and behavioural processing of complex acoustic cues.

OBJECTIVES: To examine behavioural and neural processing of pitch cues in adults with normal hearing (NH) and adults with sensorineural hearing loss (SNHL). METHODS: All participants completed a test of behavioural sensitivity to pitch cues using the TFS1 test (Moore and Sek, 2009a). Cortical potentials (N1, P2 and acoustic change complex) were recorded in response to frequency shifted (deltaF) tone complexes in an 'ABA' pattern. RESULTS: The SNHL group performed more poorly than the NH group for the TFS1 test. P2 was more reflective of pitch differences between the complexes than N1. The presence of acoustic change complex in response to the TFS transitions in the ABA stimulus varied with deltaF. Acoustic change complex amplitudes were reduced for the group with SNHL compared to controls. CONCLUSION: Behavioural performance and cortical responses reflect pitch processing depending on the salience of pitch cues. SIGNIFICANCE: These data support the use of cortical potentials and behavioural sensitivity tests to measure processing of complex acoustic cues in people with hearing loss. This approach has potential for evaluation of benefit from auditory training and hearing instrument digital signal processing strategies.