Cargando…
Real-life and real-time hearing aid experiences: Insights from self-initiated ecological momentary assessments and natural language analysis
INTRODUCTION: Smartphone technology can provide an effective means to bring real-life and (near-)real-time feedback from hearing aid wearers into the clinic. Ecological Momentary Assessment (EMA) encourages listeners to report on their experiences during or shortly after they take place in order to...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10050550/ https://www.ncbi.nlm.nih.gov/pubmed/37006819 http://dx.doi.org/10.3389/fdgth.2023.1104308 |
_version_ | 1785014663852851200 |
---|---|
author | Vercammen, Charlotte Oosthuizen, Ilze Manchaiah, Vinaya Ratinaud, Pierre Launer, Stefan Swanepoel, De Wet |
author_facet | Vercammen, Charlotte Oosthuizen, Ilze Manchaiah, Vinaya Ratinaud, Pierre Launer, Stefan Swanepoel, De Wet |
author_sort | Vercammen, Charlotte |
collection | PubMed |
description | INTRODUCTION: Smartphone technology can provide an effective means to bring real-life and (near-)real-time feedback from hearing aid wearers into the clinic. Ecological Momentary Assessment (EMA) encourages listeners to report on their experiences during or shortly after they take place in order to minimize recall bias, e.g., guided by surveys in a mobile application. Allowing listeners to describe experiences in their own words, further, ensures that answers are independent of predefined jargon or of how survey questions are formulated. Through these means, one can obtain ecologically valid sets of data, for instance during a hearing aid trial, which can support clinicians to assess the needs of their clients, provide directions for fine-tuning, and counselling. At a larger scale, such datasets would facilitate training of machine learning algorithms that could help hearing technology to anticipate user needs. METHODS: In this retrospective, exploratory analysis of a clinical data set, we performed a cluster analysis on 8,793 open-text statements, which were collected through self-initiated EMAs, provided by 2,301 hearing aid wearers as part of their hearing care. Our aim was to explore how listeners describe their daily life experiences with hearing technology in (near-)real-time, in their own words, by identifying emerging themes in the reports. We also explored whether identified themes correlated with the nature of the experiences, i.e., self-reported satisfaction ratings indicating a positive or negative experience. RESULTS: Results showed that close to 60% of listeners' reports related to speech intelligibility in challenging situations and sound quality dimensions, and tended to be valued as positive experiences. In comparison, close to 40% of reports related to hearing aid management, and tended to be valued as negative experiences. DISCUSSION: This first report of open-text statements, collected through self-initiated EMAs as part of clinical practice, shows that, while EMA can come with a participant burden, at least a subsample of motivated hearing aid wearers could use these novel tools to provide feedback to inform more responsive, personalized, and family-centered hearing care. |
format | Online Article Text |
id | pubmed-10050550 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100505502023-03-30 Real-life and real-time hearing aid experiences: Insights from self-initiated ecological momentary assessments and natural language analysis Vercammen, Charlotte Oosthuizen, Ilze Manchaiah, Vinaya Ratinaud, Pierre Launer, Stefan Swanepoel, De Wet Front Digit Health Digital Health INTRODUCTION: Smartphone technology can provide an effective means to bring real-life and (near-)real-time feedback from hearing aid wearers into the clinic. Ecological Momentary Assessment (EMA) encourages listeners to report on their experiences during or shortly after they take place in order to minimize recall bias, e.g., guided by surveys in a mobile application. Allowing listeners to describe experiences in their own words, further, ensures that answers are independent of predefined jargon or of how survey questions are formulated. Through these means, one can obtain ecologically valid sets of data, for instance during a hearing aid trial, which can support clinicians to assess the needs of their clients, provide directions for fine-tuning, and counselling. At a larger scale, such datasets would facilitate training of machine learning algorithms that could help hearing technology to anticipate user needs. METHODS: In this retrospective, exploratory analysis of a clinical data set, we performed a cluster analysis on 8,793 open-text statements, which were collected through self-initiated EMAs, provided by 2,301 hearing aid wearers as part of their hearing care. Our aim was to explore how listeners describe their daily life experiences with hearing technology in (near-)real-time, in their own words, by identifying emerging themes in the reports. We also explored whether identified themes correlated with the nature of the experiences, i.e., self-reported satisfaction ratings indicating a positive or negative experience. RESULTS: Results showed that close to 60% of listeners' reports related to speech intelligibility in challenging situations and sound quality dimensions, and tended to be valued as positive experiences. In comparison, close to 40% of reports related to hearing aid management, and tended to be valued as negative experiences. DISCUSSION: This first report of open-text statements, collected through self-initiated EMAs as part of clinical practice, shows that, while EMA can come with a participant burden, at least a subsample of motivated hearing aid wearers could use these novel tools to provide feedback to inform more responsive, personalized, and family-centered hearing care. Frontiers Media S.A. 2023-03-15 /pmc/articles/PMC10050550/ /pubmed/37006819 http://dx.doi.org/10.3389/fdgth.2023.1104308 Text en © 2023 Vercammen, Oosthuizen, Manchaiah, Ratinaud, Launer and Swanepoel. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Digital Health Vercammen, Charlotte Oosthuizen, Ilze Manchaiah, Vinaya Ratinaud, Pierre Launer, Stefan Swanepoel, De Wet Real-life and real-time hearing aid experiences: Insights from self-initiated ecological momentary assessments and natural language analysis |
title | Real-life and real-time hearing aid experiences: Insights from self-initiated ecological momentary assessments and natural language analysis |
title_full | Real-life and real-time hearing aid experiences: Insights from self-initiated ecological momentary assessments and natural language analysis |
title_fullStr | Real-life and real-time hearing aid experiences: Insights from self-initiated ecological momentary assessments and natural language analysis |
title_full_unstemmed | Real-life and real-time hearing aid experiences: Insights from self-initiated ecological momentary assessments and natural language analysis |
title_short | Real-life and real-time hearing aid experiences: Insights from self-initiated ecological momentary assessments and natural language analysis |
title_sort | real-life and real-time hearing aid experiences: insights from self-initiated ecological momentary assessments and natural language analysis |
topic | Digital Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10050550/ https://www.ncbi.nlm.nih.gov/pubmed/37006819 http://dx.doi.org/10.3389/fdgth.2023.1104308 |
work_keys_str_mv | AT vercammencharlotte reallifeandrealtimehearingaidexperiencesinsightsfromselfinitiatedecologicalmomentaryassessmentsandnaturallanguageanalysis AT oosthuizenilze reallifeandrealtimehearingaidexperiencesinsightsfromselfinitiatedecologicalmomentaryassessmentsandnaturallanguageanalysis AT manchaiahvinaya reallifeandrealtimehearingaidexperiencesinsightsfromselfinitiatedecologicalmomentaryassessmentsandnaturallanguageanalysis AT ratinaudpierre reallifeandrealtimehearingaidexperiencesinsightsfromselfinitiatedecologicalmomentaryassessmentsandnaturallanguageanalysis AT launerstefan reallifeandrealtimehearingaidexperiencesinsightsfromselfinitiatedecologicalmomentaryassessmentsandnaturallanguageanalysis AT swanepoeldewet reallifeandrealtimehearingaidexperiencesinsightsfromselfinitiatedecologicalmomentaryassessmentsandnaturallanguageanalysis |