Live Evaluation of Auditory Preference, a Laboratory Test for Evaluating Auditory Preference

Implementing Ecological Momentary Assessment in Audiological Research: Opportunities and Challenges

Ecological momentary assessment (EMA) is a way to evaluate experiences in everyday life. It is a powerful research tool but can be complex and challenging for beginners. Application of EMA in audiological research brings with it opportunities and challenges that differ from other research disciplines. This tutorial discusses important considerations when conducting EMA studies in hearing care. While more research is needed to develop specific guidelines for the various potential applications of EMA in hearing research, we hope this article can alert hearing researchers new to EMA to pitfalls when using EMA and help strengthen their study design. The current article elaborates study design details, such as choice of participants, representativeness of the study period for participants' lives, and balancing participant burden with data requirements. Mobile devices and sensors to collect objective data on the acoustic situation are reviewed alongside different possibilities for EMA setups ranging from online questionnaires paired with a timer to proprietary apps that also have access to parameters of a hearing device. In addition to considerations for survey design, a list of questionnaire items from previous studies is provided. For each item, an example and a list of references are given. EMA typically provides data sets that are rich but also challenging in that they are noisy, and there is often unequal amount of data between participants. After recommendations on how to check the data for compliance, reactivity, and careless responses, methods for statistical analysis on the individual level and on the group level are discussed including special methods for direct comparison of hearing device programs.

Bayesian analysis of Ecological Momentary Assessment (EMA) data collected in adults before and after hearing rehabilitation

This paper presents a new Bayesian method for analyzing Ecological Momentary Assessment (EMA) data and applies this method in a re-analysis of data from a previous EMA study. The analysis method has been implemented as a freely available Python package EmaCalc, RRID:SCR 022943. The analysis model can use EMA input data including nominal categories in one or more situation dimensions, and ordinal ratings of several perceptual attributes. The analysis uses a variant of ordinal regression to estimate the statistical relation between these variables. The Bayesian method has no requirements related to the number of participants or the number of assessments by each participant. Instead, the method automatically includes measures of the statistical credibility of all analysis results, for the given amount of data. For the previously collected EMA data, the analysis results demonstrate how the new tool can handle heavily skewed, scarce, and clustered data that were collected on ordinal scales, and present results on interval scales. The new method revealed results for the population mean that were similar to those obtained in the previous analysis by an advanced regression model. The Bayesian approach automatically estimated the inter-individual variability in the population, based on the study sample, and could show some statistically credible intervention results also for an unseen random individual in the population. Such results may be interesting, for example, if the EMA methodology is used by a hearing-aid manufacturer in a study to predict the success of a new signal-processing method among future potential customers.

Conformities and gaps of clinical audiological data with the international classification of functioning disability and health core sets for hearing loss

OBJECTIVE

The International Classification of Functioning Disability and Health (ICF) is a classification of health and health-related domains created by the World Health Organization and can be used as a standard to evaluate the health and disability of individuals. The ICF Core Set for Hearing Loss (CSHL) refers to the ICF categories found to be relative to Hearing Loss (HL) and the consequences of it on daily life. This study aimed to adapt the content of a database gathered in Hörzentrum Oldenburg gGmbH that included HL medical assessments and audiological data to the ICF.

DESIGN

ICF linking rules were applied to these assessment methods including medical interviews, ear examinations, pure-tone audiometry, Adaptive Categorical Loudness Scaling, and speech intelligibility test.

STUDY SAMPLE

1316 subjects.

RESULTS

In total, 44% of the brief and 18% of the comprehensive CSHL categories were addressed. The hearing functions were broadly evaluated. "Activities and Participation" and "Environmental Factors" were poorly examined (17% and 12% of the comprehensive CSHL categories, respectively).

CONCLUSIONS

The HL correlation with day-to-day activities limitation, performance restriction, and environmental conditions were poorly addressed. This study showed the essence of incorporating these methodologies with approaches that assess the daily-life challenges caused by HL in rehabilitation.