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Med."],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>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; <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.01; non-parametric Mann\u2013Whitney\u2013Wilcoxon 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.<\/jats:p>","DOI":"10.1038\/s41746-023-00862-3","type":"journal-article","created":{"date-parts":[[2023,6,21]],"date-time":"2023-06-21T05:03:38Z","timestamp":1687323818000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":52,"title":["Rating analysis and BERTopic modeling of consumer versus regulated mHealth app reviews in Germany"],"prefix":"10.1038","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0694-7970","authenticated-orcid":false,"given":"Marie","family":"Uncovska","sequence":"first","affiliation":[]},{"given":"Bettina","family":"Freitag","sequence":"additional","affiliation":[]},{"given":"Sven","family":"Meister","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3322-3724","authenticated-orcid":false,"given":"Leonard","family":"Fehring","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,6,21]]},"reference":[{"key":"862_CR1","unstructured":"Grand View Research. mHealth Apps Market Size & Share Report, 2022\u20132030 (2022)."},{"key":"862_CR2","doi-asserted-by":"publisher","first-page":"1975","DOI":"10.1001\/jama.2018.14378","volume":"320","author":"DW Bates","year":"2018","unstructured":"Bates, D. 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