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Rating analysis and BERTopic modeling of consumer versus regulated mHealth app reviews in Germany
Germany introduced prescription-based mobile health (mHealth) apps in October 2020, becoming the first country to offer them fully reimbursed by health insurance. These regulated apps, known as DiGAs, undergo a rigorous approval process similar to pharmaceuticals, including data protection measures...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10285024/ https://www.ncbi.nlm.nih.gov/pubmed/37344556 http://dx.doi.org/10.1038/s41746-023-00862-3 |
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author | Uncovska, Marie Freitag, Bettina Meister, Sven Fehring, Leonard |
author_facet | Uncovska, Marie Freitag, Bettina Meister, Sven Fehring, Leonard |
author_sort | Uncovska, Marie |
collection | PubMed |
description | Germany introduced prescription-based mobile health (mHealth) apps in October 2020, becoming the first country to offer them fully reimbursed by health insurance. These regulated apps, known as DiGAs, undergo a rigorous approval process similar to pharmaceuticals, including data protection measures and sometimes clinical trials. This study compares the user experience of DiGAs with non-prescription mHealth apps in Germany, analyzing both average app store ratings and written reviews. Our study pioneers the use of BERTopic for sentiment analysis and topic modeling in the mHealth research domain. The dataset comprises 15 DiGAs and 50 comparable apps, totaling 17,588 German-language reviews. Results reveal that DiGAs receive higher contemporary ratings than non-regulated apps (Android: 3.82 vs. 3.77; iOS: 3.78 vs. 3.53; p < 0.01; non-parametric Mann–Whitney–Wilcoxon test). Key factors contributing to positive user experience with DiGAs are customer service and personalization (15%) and ease of use (13%). However, challenges for DiGAs include software bugs (24%) and a cumbersome registration process (20%). Negative user reviews highlight concerns about therapy effectiveness (11%). Excessive pricing is the main concern for the non-regulated group (27%). Data privacy and security receive limited attention from users (DiGAs: 0.5%; comparators: 2%). In conclusion, DiGAs are generally perceived positively based on ratings and sentiment analysis of reviews. However, addressing pricing concerns in the non-regulated mHealth sector is crucial. Integrating user experience evaluation into the review process could improve adherence and health outcomes. |
format | Online Article Text |
id | pubmed-10285024 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-102850242023-06-23 Rating analysis and BERTopic modeling of consumer versus regulated mHealth app reviews in Germany Uncovska, Marie Freitag, Bettina Meister, Sven Fehring, Leonard NPJ Digit Med Article Germany introduced prescription-based mobile health (mHealth) apps in October 2020, becoming the first country to offer them fully reimbursed by health insurance. These regulated apps, known as DiGAs, undergo a rigorous approval process similar to pharmaceuticals, including data protection measures and sometimes clinical trials. This study compares the user experience of DiGAs with non-prescription mHealth apps in Germany, analyzing both average app store ratings and written reviews. Our study pioneers the use of BERTopic for sentiment analysis and topic modeling in the mHealth research domain. The dataset comprises 15 DiGAs and 50 comparable apps, totaling 17,588 German-language reviews. Results reveal that DiGAs receive higher contemporary ratings than non-regulated apps (Android: 3.82 vs. 3.77; iOS: 3.78 vs. 3.53; p < 0.01; non-parametric Mann–Whitney–Wilcoxon test). Key factors contributing to positive user experience with DiGAs are customer service and personalization (15%) and ease of use (13%). However, challenges for DiGAs include software bugs (24%) and a cumbersome registration process (20%). Negative user reviews highlight concerns about therapy effectiveness (11%). Excessive pricing is the main concern for the non-regulated group (27%). Data privacy and security receive limited attention from users (DiGAs: 0.5%; comparators: 2%). In conclusion, DiGAs are generally perceived positively based on ratings and sentiment analysis of reviews. However, addressing pricing concerns in the non-regulated mHealth sector is crucial. Integrating user experience evaluation into the review process could improve adherence and health outcomes. Nature Publishing Group UK 2023-06-21 /pmc/articles/PMC10285024/ /pubmed/37344556 http://dx.doi.org/10.1038/s41746-023-00862-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Uncovska, Marie Freitag, Bettina Meister, Sven Fehring, Leonard Rating analysis and BERTopic modeling of consumer versus regulated mHealth app reviews in Germany |
title | Rating analysis and BERTopic modeling of consumer versus regulated mHealth app reviews in Germany |
title_full | Rating analysis and BERTopic modeling of consumer versus regulated mHealth app reviews in Germany |
title_fullStr | Rating analysis and BERTopic modeling of consumer versus regulated mHealth app reviews in Germany |
title_full_unstemmed | Rating analysis and BERTopic modeling of consumer versus regulated mHealth app reviews in Germany |
title_short | Rating analysis and BERTopic modeling of consumer versus regulated mHealth app reviews in Germany |
title_sort | rating analysis and bertopic modeling of consumer versus regulated mhealth app reviews in germany |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10285024/ https://www.ncbi.nlm.nih.gov/pubmed/37344556 http://dx.doi.org/10.1038/s41746-023-00862-3 |
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