![]() Another complexity occurs when sensors (e.g., continuously recorded sound pressure level) are used with EMA. ![]() Further complicating the data is the fact that EMA often uses adaptive questions (e.g., if participants indicate that they are not listening to speech, the Speech Understanding question will not be presented). For example, the EMA methodology requires each respondent to complete multiple EMA surveys during the trial, resulting in EMA survey data typically being nested within individuals. This is largely because EMA data are observational with very few, if any, clinically controlled settings. Although the examples in this tutorial focus on audiology research, the results apply to speech-language pathology research as well.Īlthough EMA is a useful tool in audiology research, analyzing EMA data is often challenging due to the complex structures it exhibits. EMA is also used in speech-language pathology research ( Constantino et al., 2020). More recently, EMA has been used with sensors or devices (e.g., audio recorders and hearing aids) that can collect objective information about the respondents' listening environments (e.g., sound pressure level) in audiology research ( Andersson et al., 2020 Wu, Xu, et al., 2020). It has been implemented using paper-and-pencil journals ( Preminger & Cunningham, 2003 Walden et al., 2004 Wu & Bentler, 2010, 2012), daily diaries ( Bentler et al., 2008), portable computers ( Galvez et al., 2012), and smartphones ( Timmer et al., 2018 Wu et al., 2019). EMA has been used in various ways to assess real-world listening difficulty, listening fatigue, and hearing aid outcomes. Due to these advantages, EMA methodology use in audiology research has become more popular over the past decades. EMA is a validated research methodology in audiology ( Timmer et al., 2017 Wu et al., 2015), has test–retest reliability comparable to retrospective questionnaires ( Wu, Stangl, Chipara, & Zhang, 2020), and is more sensitive than retrospective self-reports when detecting differences in outcomes between different hearing aid technologies ( Wu, Stangl, Chipara, Gudjonsdottir, et al., 2020). EMA can allow researchers to examine the interaction between context and experience by collecting detailed contextual information (e.g., characteristics of the listening situation) with self-reported experience. EMA can provide a wealth of information on moments in a respondent's life without the distortions caused by recalling memories and delayed evaluation of experiences associated with retrospective self-reports. Ecological Momentary Assessment (EMA) methodology involves collecting self-reported data through repeated surveys to describe respondents' current or very recent (i.e., momentary) experiences and related contexts in their natural (i.e., ecological) environments ( Shiffman et al., 2008).
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