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Influence of the Business Revenue, Recommendation, and Provider Models on Mobile Health App Adoption: Three-Country Experimental Vignette Study

BACKGROUND: Despite the worldwide growth in mobile health (mHealth) tools and the possible benefits of mHealth for patients and health care providers, scientific research examining factors explaining the adoption level of mHealth tools remains scarce. OBJECTIVE: We performed an experimental vignette...

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Autores principales: Lupiáñez-Villanueva, Francisco, Folkvord, Frans, Vanden Abeele, Mariek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303831/
https://www.ncbi.nlm.nih.gov/pubmed/32496204
http://dx.doi.org/10.2196/17272
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author Lupiáñez-Villanueva, Francisco
Folkvord, Frans
Vanden Abeele, Mariek
author_facet Lupiáñez-Villanueva, Francisco
Folkvord, Frans
Vanden Abeele, Mariek
author_sort Lupiáñez-Villanueva, Francisco
collection PubMed
description BACKGROUND: Despite the worldwide growth in mobile health (mHealth) tools and the possible benefits of mHealth for patients and health care providers, scientific research examining factors explaining the adoption level of mHealth tools remains scarce. OBJECTIVE: We performed an experimental vignette study to investigate how four factors related to the business model of an mHealth app affect its adoption and users’ willingness to pay: (1) the revenue model (ie, sharing data with third parties vs accepting advertisements); (2) the data protection model (General Data Protection Regulation [GDPR]-compliant data handling vs nonGDPR-compliant data handling); (3) the recommendation model (ie, doctor vs patient recommendation); and (4) the provider model (ie, pharmaceutical vs medical association provider). In addition, health consciousness, health information orientation, and electronic health literacy were explored as intrapersonal predictors of adoption. METHODS: We conducted an experimental study in three countries, Spain (N=800), Germany (N=800), and the Netherlands (N=416), to assess the influence of multiple business models and intrapersonal characteristics on the willingness to pay and intention to download a health app. RESULTS: The revenue model did not affect willingness to pay or intentions to download the app in all three countries. In the Netherlands, data protection increased willingness to pay for the health app (P<.001). Moreover, in all three countries, data protection increased the likelihood of downloading the app (P<.001). In Germany (P=.04) and the Netherlands (P=.007), a doctor recommendation increased both willingness to pay and intention to download the health app. For all three countries, apps manufactured in association with a medical organization were more likely to be downloaded (P<.001). Finally, in all three countries, men, younger individuals, those with higher levels of education, and people with a health information orientation were willing to pay more for adoption of the health app and had a higher intention to download the app. CONCLUSIONS: The finding that people want their data protected by legislation but are not willing to pay more for data protection suggests that in the context of mHealth, app privacy protection cannot be leveraged as a selling point. However, people do value a doctor recommendation and apps manufactured by a medical association, which particularly influence their intention to download an mHealth app.
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spelling pubmed-73038312020-06-24 Influence of the Business Revenue, Recommendation, and Provider Models on Mobile Health App Adoption: Three-Country Experimental Vignette Study Lupiáñez-Villanueva, Francisco Folkvord, Frans Vanden Abeele, Mariek JMIR Mhealth Uhealth Original Paper BACKGROUND: Despite the worldwide growth in mobile health (mHealth) tools and the possible benefits of mHealth for patients and health care providers, scientific research examining factors explaining the adoption level of mHealth tools remains scarce. OBJECTIVE: We performed an experimental vignette study to investigate how four factors related to the business model of an mHealth app affect its adoption and users’ willingness to pay: (1) the revenue model (ie, sharing data with third parties vs accepting advertisements); (2) the data protection model (General Data Protection Regulation [GDPR]-compliant data handling vs nonGDPR-compliant data handling); (3) the recommendation model (ie, doctor vs patient recommendation); and (4) the provider model (ie, pharmaceutical vs medical association provider). In addition, health consciousness, health information orientation, and electronic health literacy were explored as intrapersonal predictors of adoption. METHODS: We conducted an experimental study in three countries, Spain (N=800), Germany (N=800), and the Netherlands (N=416), to assess the influence of multiple business models and intrapersonal characteristics on the willingness to pay and intention to download a health app. RESULTS: The revenue model did not affect willingness to pay or intentions to download the app in all three countries. In the Netherlands, data protection increased willingness to pay for the health app (P<.001). Moreover, in all three countries, data protection increased the likelihood of downloading the app (P<.001). In Germany (P=.04) and the Netherlands (P=.007), a doctor recommendation increased both willingness to pay and intention to download the health app. For all three countries, apps manufactured in association with a medical organization were more likely to be downloaded (P<.001). Finally, in all three countries, men, younger individuals, those with higher levels of education, and people with a health information orientation were willing to pay more for adoption of the health app and had a higher intention to download the app. CONCLUSIONS: The finding that people want their data protected by legislation but are not willing to pay more for data protection suggests that in the context of mHealth, app privacy protection cannot be leveraged as a selling point. However, people do value a doctor recommendation and apps manufactured by a medical association, which particularly influence their intention to download an mHealth app. JMIR Publications 2020-06-04 /pmc/articles/PMC7303831/ /pubmed/32496204 http://dx.doi.org/10.2196/17272 Text en ©Francisco Lupiáñez-Villanueva, Frans Folkvord, Mariek Vanden Abeele. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 04.06.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Lupiáñez-Villanueva, Francisco
Folkvord, Frans
Vanden Abeele, Mariek
Influence of the Business Revenue, Recommendation, and Provider Models on Mobile Health App Adoption: Three-Country Experimental Vignette Study
title Influence of the Business Revenue, Recommendation, and Provider Models on Mobile Health App Adoption: Three-Country Experimental Vignette Study
title_full Influence of the Business Revenue, Recommendation, and Provider Models on Mobile Health App Adoption: Three-Country Experimental Vignette Study
title_fullStr Influence of the Business Revenue, Recommendation, and Provider Models on Mobile Health App Adoption: Three-Country Experimental Vignette Study
title_full_unstemmed Influence of the Business Revenue, Recommendation, and Provider Models on Mobile Health App Adoption: Three-Country Experimental Vignette Study
title_short Influence of the Business Revenue, Recommendation, and Provider Models on Mobile Health App Adoption: Three-Country Experimental Vignette Study
title_sort influence of the business revenue, recommendation, and provider models on mobile health app adoption: three-country experimental vignette study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303831/
https://www.ncbi.nlm.nih.gov/pubmed/32496204
http://dx.doi.org/10.2196/17272
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