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Understanding adherence to the recording of ecological momentary assessments in the example of tinnitus monitoring
The recording of Ecological Momentary Assessments (EMA) can assist people with chronic diseases in monitoring their health state. However, many users quickly lose interest in their respective EMA platforms. Therefore, we studied the adherence of users of the mHealth app TrackYourTinnitus (TYT). The...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775469/ https://www.ncbi.nlm.nih.gov/pubmed/33384428 http://dx.doi.org/10.1038/s41598-020-79527-0 |
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author | Schleicher, Miro Unnikrishnan, Vishnu Neff, Patrick Simoes, Jorge Probst, Thomas Pryss, Rüdiger Schlee, Winfried Spiliopoulou, Myra |
author_facet | Schleicher, Miro Unnikrishnan, Vishnu Neff, Patrick Simoes, Jorge Probst, Thomas Pryss, Rüdiger Schlee, Winfried Spiliopoulou, Myra |
author_sort | Schleicher, Miro |
collection | PubMed |
description | The recording of Ecological Momentary Assessments (EMA) can assist people with chronic diseases in monitoring their health state. However, many users quickly lose interest in their respective EMA platforms. Therefore, we studied the adherence of users of the mHealth app TrackYourTinnitus (TYT). The app is used to record EMA in people with tinnitus. 1292 users, who interacted with the app between April 2014 and February 2017, were analyzed in this work. We defined “adherence” based on the dimensions of interaction duration and interaction continuity. We propose methods that are able to predict the (dis)continuation of interaction with the app and identify user segments that are characterized by similar patterns of adherence. For the prediction task we used the data of the questionnaires MiniTF and TSCHQ, which are filled in when the users enter TYT for the first time. Additionally, time series of the eight items of the daily EMA questionnaire were used. The distribution of user activity pertaining to the adherence dimension of interaction duration revealed a very skewed distribution, with most users giving up after only 1 day of interaction. However, many users returned after interrupting for some time. Some of the MiniTF items indicated that the worries of users might have lead to an increased likelihood of returning back to the app. The MiniTF score itself was not predictive, though. The answers to the TSCHQ items, in turn, pointed to user strata (more than 65 years of age at registration), which tended towards higher interaction continuity. As the registration questionnaires predicted adherence only to a limited extent, it is promising to study the activities of the users in the very first days of interaction more deeply. It turned out in this context that the effects of interaction stimulants like personalized and non-personalized tips, pointers to information sources, and mechanisms used in online treatments for tinnitus (e.g., in iCBT) should be further investigated. |
format | Online Article Text |
id | pubmed-7775469 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-77754692021-01-07 Understanding adherence to the recording of ecological momentary assessments in the example of tinnitus monitoring Schleicher, Miro Unnikrishnan, Vishnu Neff, Patrick Simoes, Jorge Probst, Thomas Pryss, Rüdiger Schlee, Winfried Spiliopoulou, Myra Sci Rep Article The recording of Ecological Momentary Assessments (EMA) can assist people with chronic diseases in monitoring their health state. However, many users quickly lose interest in their respective EMA platforms. Therefore, we studied the adherence of users of the mHealth app TrackYourTinnitus (TYT). The app is used to record EMA in people with tinnitus. 1292 users, who interacted with the app between April 2014 and February 2017, were analyzed in this work. We defined “adherence” based on the dimensions of interaction duration and interaction continuity. We propose methods that are able to predict the (dis)continuation of interaction with the app and identify user segments that are characterized by similar patterns of adherence. For the prediction task we used the data of the questionnaires MiniTF and TSCHQ, which are filled in when the users enter TYT for the first time. Additionally, time series of the eight items of the daily EMA questionnaire were used. The distribution of user activity pertaining to the adherence dimension of interaction duration revealed a very skewed distribution, with most users giving up after only 1 day of interaction. However, many users returned after interrupting for some time. Some of the MiniTF items indicated that the worries of users might have lead to an increased likelihood of returning back to the app. The MiniTF score itself was not predictive, though. The answers to the TSCHQ items, in turn, pointed to user strata (more than 65 years of age at registration), which tended towards higher interaction continuity. As the registration questionnaires predicted adherence only to a limited extent, it is promising to study the activities of the users in the very first days of interaction more deeply. It turned out in this context that the effects of interaction stimulants like personalized and non-personalized tips, pointers to information sources, and mechanisms used in online treatments for tinnitus (e.g., in iCBT) should be further investigated. Nature Publishing Group UK 2020-12-31 /pmc/articles/PMC7775469/ /pubmed/33384428 http://dx.doi.org/10.1038/s41598-020-79527-0 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Schleicher, Miro Unnikrishnan, Vishnu Neff, Patrick Simoes, Jorge Probst, Thomas Pryss, Rüdiger Schlee, Winfried Spiliopoulou, Myra Understanding adherence to the recording of ecological momentary assessments in the example of tinnitus monitoring |
title | Understanding adherence to the recording of ecological momentary assessments in the example of tinnitus monitoring |
title_full | Understanding adherence to the recording of ecological momentary assessments in the example of tinnitus monitoring |
title_fullStr | Understanding adherence to the recording of ecological momentary assessments in the example of tinnitus monitoring |
title_full_unstemmed | Understanding adherence to the recording of ecological momentary assessments in the example of tinnitus monitoring |
title_short | Understanding adherence to the recording of ecological momentary assessments in the example of tinnitus monitoring |
title_sort | understanding adherence to the recording of ecological momentary assessments in the example of tinnitus monitoring |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7775469/ https://www.ncbi.nlm.nih.gov/pubmed/33384428 http://dx.doi.org/10.1038/s41598-020-79527-0 |
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