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ObjectivesMicrointeraction-based Ecological Momentary Assessment (micro-EMA) is a smartwatch-based tool that delivers single-question surveys, enabling respondents to quickly report their real-time experiences. The objectives of the two studies presented here were to evaluate micro-EMA's psychometric characteristics and feasibility across three response formats (2-point, 5-point, and 10-point scales) for adults with hearing loss. DesignIn the first study, thirty-two participants completed a dual-task experiment aimed at assessing the construct validity, responsiveness, intrusiveness, and test-retest reliability of micro-EMA across the three response formats. Participants listened to sentences at five signal-to-noise ratios (SNRs) ranging from −3 to 9 dB relative to the SNR for 50% speech understanding, answered the question “Hearing well?” on smartwatches, and repeated the sentences. In the second study, twenty-one participants wore smartwatches over 6 days. Every 15 min, participants were prompted to answer the question “Hearing well?” using one of the three response formats for 2 days. Participants provided feedback on their experience with micro-EMA. ResultsIn the dual-task experiment, participants reported improved hearing performance in micro-EMA as SNRs and speech recognition scores increased across all three response formats, supporting the tool's construct validity. Statistical models indicated that the 5-point and 10-point scales yielded larger relative changes between SNRs, suggesting higher responsiveness, compared to the 2-point scale. Participants completed surveys significantly faster with the 2-point scale, indicating lower intrusiveness, compared to the 5-point and 10-point scales. Correlation analysis revealed that over two visits 1 week apart, the 2-point scale had the poorest test-retest reliability, while the 5-point scale had the highest. In the field trial, participants completed 79.6% of the prompted surveys, with each participant averaging 42.9 surveys per day. Although participants experienced interruptions due to frequent prompts, annoyance and distraction levels were low. Most participants preferred the 5-point scale. ConclusionsThe dual-task experiment suggested that micro-EMA using the 5-point scale demonstrated superior psychometric characteristics compared to the 2-point and 10-point scales at the tested SNRs. The field trial further supported its feasibility for evaluating hearing performance in adults with hearing loss. Additional research is needed to explore the potential applications of micro-EMA in audiology research. 

Adults with mild-to-moderate hearing loss can use over-the-counter hearing aids to treat their hearing loss at a fraction of traditional hearing care costs. These products incorporate self-fitting methods that allow end-users to configure their hearing aids without the help of an audiologist. A self-fitting method helps users configure the gain-frequency responses that control the amplification for each frequency band of the incoming sound. This paper considers how to guide the design of self-fitting methods by evaluating certain aspects of their design using computational tools before performing user studies. Most existing fitting methods provide various user interfaces to allow users to select a configuration from a predetermined set of presets. Accordingly, it is essential for the presets to meet the hearing needs of a large fraction of users who suffer from varying degrees of hearing loss and have unique hearing preferences. To this end, we propose a novel metric for evaluating the effectiveness of preset-based approaches by computing their population coverage. The population coverage estimates the fraction of users for which a self-fitting method can find a configuration they prefer. A unique aspect of our approach is a probabilistic model that captures how a user's unique preferences differ from other users with similar hearing loss. Next, we propose methods for building preset-based and slider-based self-fitting methods that maximize the population coverage. Simulation results demonstrate that the proposed algorithms can effectively select a small number of presets that provide higher population coverage than clustering-based approaches. Moreover, we may use our algorithms to configure the number of increments of slider-based methods. We expect that the computational tools presented in this article will help reduce the cost of developing new self-fitting methods by allowing researchers to evaluate population coverage before performing user studies. 

Introduction Using data collected from hearing aid users’ own hearing aids could improve the customization of hearing aid processing for different users based on the auditory environments they encounter in daily life. Prior studies characterizing hearing aid users’ auditory environments have focused on mean sound pressure levels and proportions of environments based on classifications. In this study, we extend these approaches by introducing entropy to quantify the diversity of auditory environments hearing aid users encounter. Materials and Methods Participants from 4 groups (younger listeners with normal hearing and older listeners with hearing loss from an urban or rural area) wore research hearing aids and completed ecological momentary assessments on a smartphone for 1 week. The smartphone was programmed to sample the processing state (input sound pressure level and environment classification) of the hearing aids every 10 min and deliver an ecological momentary assessment every 40 min. Entropy values for sound pressure levels, environment classifications, and ecological momentary assessment responses were calculated for each participant to quantify the diversity of auditory environments encountered over the course of the week. Entropy values between groups were compared. Group differences in entropy were compared to prior work reporting differences in mean sound pressure levels and proportions of environment classifications. Group differences in entropy measured objectively from the hearing aid data were also compared to differences in entropy measured from the self-report ecological momentary assessment data. Results Auditory environment diversity, quantified using entropy from the hearing aid data, was significantly higher for younger listeners than older listeners. Entropy measured using ecological momentary assessment was also significantly higher for younger listeners than older listeners. Discussion Using entropy, we show that younger listeners experience a greater diversity of auditory environments than older listeners. Alignment of group entropy differences with differences in sound pressure levels and hearing aid feature activation previously reported, along with alignment with ecological momentary response entropy, suggests that entropy is a valid and useful metric. We conclude that entropy is a simple and intuitive way to measure auditory environment diversity using hearing aid data. 

The self-fitting Bose SoundControl™ hearing aid is the first of its kind to gain FDA clearance. In the self-fitting process, the Bose Hear app uses the Bose CustomTune™ interface for mapping to a wide range of target gain profiles, derived from a hearing loss database. This article compares the population coverage—or the percentage of people who would be able to find a frequency gain profile similar to a NAL-NL2 prescription fit—of SoundControl to other self-fitting amplification devices which typically feature only 1 to 4 preset gain profiles. 

Abstract Background Ecological momentary assessment (EMA) is a methodology involving repeated surveys to collect in situ data that describe respondents' current or recent experiences and related contexts in their natural environments. Audiology literature investigating the test-retest reliability of EMA is scarce. Purpose This article examines the test-retest reliability of EMA in measuring the characteristics of listening contexts and listening experiences. Research Design An observational study. Study Sample Fifty-one older adults with hearing loss. Data Collection and Analysis The study was part of a larger study that examined the effect of hearing aid technologies. The larger study had four trial conditions and outcome was measured using a smartphone-based EMA system. After completing the four trial conditions, participants repeated one of the conditions to examine the EMA test-retest reliability. The EMA surveys contained questions that assessed listening context characteristics including talker familiarity, talker location, and noise location, as well as listening experiences including speech understanding, listening effort, loudness satisfaction, and hearing aid satisfaction. The data from multiple EMA surveys collected by each participant were aggregated in each of the test and retest conditions. Test-retest correlation on the aggregated data was then calculated for each EMA survey question to determine the reliability of EMA. Results At the group level, listening context characteristics and listening experience did not change between the test and retest conditions. The test-retest correlation varied across the EMA questions, with the highest being the questions that assessed talker location (median r = 1.0), reverberation (r = 0.89), and speech understanding (r = 0.85), and the lowest being the items that quantified noise location (median r = 0.63), talker familiarity (r = 0.46), listening effort (r = 0.61), loudness satisfaction (r = 0.60), and hearing aid satisfaction (r = 0.61). Conclusion Several EMA questions yielded appropriate test-retest reliability results. The lower test-retest correlations for some EMA survey questions were likely due to fewer surveys completed by participants and poorly designed questions. Therefore, the present study stresses the importance of using validated questions in EMA. With sufficient numbers of surveys completed by respondents and with appropriately designed survey questions, EMA could have reasonable test-retest reliability in audiology research. 

Abstract Background Ecological momentary assessment (EMA) is a methodology involving repeated surveys to collect in-situ self-reports that describe respondents' current or recent experiences. Audiology literature comparing in-situ and retrospective self-reports is scarce. Purpose To compare the sensitivity of in-situ and retrospective self-reports in detecting the outcome difference between hearing aid technologies, and to determine the association between in-situ and retrospective self-reports. Research Design An observational study. Study Sample Thirty-nine older adults with hearing loss. Data Collection and Analysis The study was part of a larger clinical trial that compared the outcomes of a prototype hearing aid (denoted as HA1) and a commercially available device (HA2). In each trial condition, participants wore hearing aids for 4 weeks. Outcomes were measured using EMA and retrospective questionnaires. To ensure that the outcome data could be directly compared, the Glasgow Hearing Aid Benefit Profile was administered as an in-situ self-report (denoted as EMA-GHABP) and as a retrospective questionnaire (retro-GHABP). Linear mixed models were used to determine if the EMA- and retro-GHABP could detect the outcome difference between HA1 and HA2. Correlation analyses were used to examine the association between EMA- and retro-GHABP. Results For the EMA-GHABP, HA2 had significantly higher (better) scores than HA1 in the GHABP subscales of benefit, residual disability, and satisfaction (p = 0.029–0.0015). In contrast, the difference in the retro-GHABP score between HA1 and HA2 was significant only in the satisfaction subscale (p = 0.0004). The correlations between the EMA- and retro-GHABP were significant in all subscales (p = 0.0004 to <0.0001). The strength of the association ranged from weak to moderate (r = 0.28–0.58). Finally, the exit interview indicated that 29 participants (74.4%) preferred HA2 over HA1. Conclusion The study suggests that in-situ self-reports collected using EMA could have a higher sensitivity than retrospective questionnaires. Therefore, EMA is worth considering in clinical trials that aim to compare the outcomes of different hearing aid technologies. The weak to moderate association between in-situ and retrospective self-reports suggests that these two types of measures assess different aspects of hearing aid outcomes.