skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Comparison of In-Situ and Retrospective Self-Reports on Assessing Hearing Aid Outcomes
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.  more » « less
Award ID(s):
1838830
PAR ID:
10309713
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
Journal of the American Academy of Audiology
Volume:
31
Issue:
10
ISSN:
1050-0545
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. null (Ed.)
    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. 
    more » « less
  2. Abstract Early home musical environments can significantly impact sensory, cognitive, and socioemotional development. While longitudinal studies may be resource-intensive, retrospective reports are a relatively quick and inexpensive way to examine associations between early home musical environments and adult outcomes. We present the Music@Home–Retrospective scale, derived partly from the Music@Home–Preschool scale (Politimou et al., 2018), to retrospectively assess the childhood home musical environment. In two studies (totaln = 578), we conducted an exploratory factor analysis (Study 1) and confirmatory factor analysis (Study 2) on items, including many adapted from the Music@Home–Preschool scale. This revealed a 20-item solution with five subscales. Items retained for three subscales (Caregiver Beliefs, Caregiver Initiation of Singing, Child Engagement with Music) load identically to three in the Music@Home-–Preschool Scale. We also identified two additional dimensions of the childhood home musical environment. The Attitude Toward Childhood Home Musical Environment subscale captures participants’ current adult attitudes toward their childhood home musical environment, and the Social Listening Contexts subscale indexes the degree to which participants listened to music at home with others (i.e., friends, siblings, and caregivers). Music@Home–Retrospective scores were related to adult self-reports of musicality, performance on a melodic perception task, and self-reports of well-being, demonstrating utility in measuring the early home music environment as captured through this scale. The Music@Home–Retrospective scale is freely available to enable future investigations exploring how the early home musical environment relates to adult cognition, affect, and behavior. 
    more » « less
  3. Abstract Background Ecological momentary assessment (EMA) often requires respondents to complete surveys in the moment to report real-time experiences. Because EMA may seem disruptive or intrusive, respondents may not complete surveys as directed in certain circumstances. Purpose This article aims to determine the effect of environmental characteristics on the likelihood of instances where respondents do not complete EMA surveys (referred to as survey incompletion), and to estimate the impact of survey incompletion on EMA self-report data. Research Design An observational study. Study Sample Ten adults hearing aid (HA) users. Data Collection and Analysis Experienced, bilateral HA users were recruited and fit with study HAs. The study HAs were equipped with real-time data loggers, an algorithm that logged the data generated by HAs (e.g., overall sound level, environment classification, and feature status including microphone mode and amount of gain reduction). The study HAs were also connected via Bluetooth to a smartphone app, which collected the real-time data logging data as well as presented the participants with EMA surveys about their listening environments and experiences. The participants were sent out to wear the HAs and complete surveys for 1 week. Real-time data logging was triggered when participants completed surveys and when participants ignored or snoozed surveys. Data logging data were used to estimate the effect of environmental characteristics on the likelihood of survey incompletion, and to predict participants' responses to survey questions in the instances of survey incompletion. Results Across the 10 participants, 715 surveys were completed and survey incompletion occurred 228 times. Mixed effects logistic regression models indicated that survey incompletion was more likely to happen in the environments that were less quiet and contained more speech, noise, and machine sounds, and in the environments wherein directional microphones and noise reduction algorithms were enabled. The results of survey response prediction further indicated that the participants could have reported more challenging environments and more listening difficulty in the instances of survey incompletion. However, the difference in the distribution of survey responses between the observed responses and the combined observed and predicted responses was small. Conclusion The present study indicates that EMA survey incompletion occurs systematically. Although survey incompletion could bias EMA self-report data, the impact is likely to be small. 
    more » « less
  4. Introduction: Back pain is one of the most common causes of pain in the United States. Spinal cord stimulation (SCS) is an intervention for patients with chronic back pain (CBP). However, SCS decreases pain in only 58% of patients and relies on self-reported pain scores as outcome measures. An SCS trial is temporarily implanted for seven days and helps to determine if a permanent SCS is needed. Patients that have a >50% reduction in pain from the trial stimulator makes them eligible for permanent implantation. However, self-reported measures reveal little on how mechanisms in the brain are altered. Other measurements of pain intensity, onset, medication, disabilities, depression, and anxiety have been used with machine learning to predict outcomes with accuracies <70%. We aim to predict long-term SCS responders at 6-months using baseline resting EEG and machine learning. Materials and Methods: We obtained 10-minutes of resting electroencephalography (EEG) and pain questionnaires from nine participants with CBP at two time points: 1) pre-trial baseline. 2) Six months after SCS permanent implant surgery. Subjects were designated as high or moderate responders based on the amount of pain relief provided by the long-term (post six months) SCS, and pain scored on a scale of 0-10 with 0 being no pain and 10 intolerable. We used the resting EEG from baseline to predict long-term treatment outcome. Resting EEG data was fed through a pipeline for classification and to map dipole sources. EEG signals were preprocessed using the EEGLAB toolbox. Independent component analysis and dipole fitting were used to linearly unmix the signal and to map dipole sources from the brain. Spectral analysis was performed to obtain the frequency distribution of the signal. Each power band, delta (1-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz), and gamma (30-100 Hz), as well as the entire spectrum (1-100 Hz), were used for classification. Furthermore, dipole sources were ranked based on classification feature weights to determine the significance of specific regions in the brain. We used support vector machines to predict pain outcomes. Results and Discussion: We found higher frequency powerbands provide overall classification performance of 88.89%. Differences in power are seen between moderate and high responders in both the frontal and parietal regions for theta, alpha, beta, and the entire spectrum (Fig.1). This can potentially be used to predict patient response to SCS. Conclusions: We found evidence of decreased power in theta, alpha, beta, and entire spectrum in the anterior regions of the parietal cortex and posterior regions of the frontal cortex between moderate and high responders, which can be used for predicting treatment outcomes in long-term pain relief from SCS. Long-term treatment outcome prediction using baseline EEG data has the potential to contribute to decision making in terms of permanent surgery, forgo trial periods, and improve clinical efficiency by beginning to understand the mechanism of action of SCS in the human brain. 
    more » « less
  5. 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. 
    more » « less