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Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis
The mobile health (mHealth) industry is an enormous global market; however, the dropout or continuance of mHealth is a major challenge that is affecting its positive outcomes. To date, the results of studies on the impact factors have been inconsistent. Consequently, research on the pooled effects o...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9476418/ https://www.ncbi.nlm.nih.gov/pubmed/36109594 http://dx.doi.org/10.1038/s41746-022-00692-9 |
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author | Wang, Tong Wang, Wei Liang, Jun Nuo, Mingfu Wen, Qinglian Wei, Wei Han, Hongbin Lei, Jianbo |
author_facet | Wang, Tong Wang, Wei Liang, Jun Nuo, Mingfu Wen, Qinglian Wei, Wei Han, Hongbin Lei, Jianbo |
author_sort | Wang, Tong |
collection | PubMed |
description | The mobile health (mHealth) industry is an enormous global market; however, the dropout or continuance of mHealth is a major challenge that is affecting its positive outcomes. To date, the results of studies on the impact factors have been inconsistent. Consequently, research on the pooled effects of impact factors on the continuance intention of mHealth is limited. Therefore, this study aims to systematically analyze quantitative studies on the continuance intention of mHealth and explore the pooled effect of each direct and indirect impact factor. Until October 2021, eight literature databases were searched. Fifty-eight peer-reviewed studies on the impact factors and effects on continuance intention of mHealth were included. Out of the 19 direct impact factors of continuance intention, 15 are significant, with attitude (β = 0.450; 95% CI: 0.135, 0.683), satisfaction (β = 0.406; 95% CI: 0.292, 0.509), health empowerment (β = 0.359; 95% CI: 0.204, 0.497), perceived usefulness (β = 0.343; 95% CI: 0.280, 0.403), and perceived quality of health life (β = 0.315, 95% CI: 0.211, 0.412) having the largest pooled effect coefficients on continuance intention. There is high heterogeneity between the studies; thus, we conducted a subgroup analysis to explore the moderating effect of different characteristics on the impact effects. The geographic region, user type, mHealth type, user age, and publication year significantly moderate influential relationships, such as trust and continuance intention. Thus, mHealth developers should develop personalized continuous use promotion strategies based on user characteristics. |
format | Online Article Text |
id | pubmed-9476418 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-94764182022-09-15 Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis Wang, Tong Wang, Wei Liang, Jun Nuo, Mingfu Wen, Qinglian Wei, Wei Han, Hongbin Lei, Jianbo NPJ Digit Med Review Article The mobile health (mHealth) industry is an enormous global market; however, the dropout or continuance of mHealth is a major challenge that is affecting its positive outcomes. To date, the results of studies on the impact factors have been inconsistent. Consequently, research on the pooled effects of impact factors on the continuance intention of mHealth is limited. Therefore, this study aims to systematically analyze quantitative studies on the continuance intention of mHealth and explore the pooled effect of each direct and indirect impact factor. Until October 2021, eight literature databases were searched. Fifty-eight peer-reviewed studies on the impact factors and effects on continuance intention of mHealth were included. Out of the 19 direct impact factors of continuance intention, 15 are significant, with attitude (β = 0.450; 95% CI: 0.135, 0.683), satisfaction (β = 0.406; 95% CI: 0.292, 0.509), health empowerment (β = 0.359; 95% CI: 0.204, 0.497), perceived usefulness (β = 0.343; 95% CI: 0.280, 0.403), and perceived quality of health life (β = 0.315, 95% CI: 0.211, 0.412) having the largest pooled effect coefficients on continuance intention. There is high heterogeneity between the studies; thus, we conducted a subgroup analysis to explore the moderating effect of different characteristics on the impact effects. The geographic region, user type, mHealth type, user age, and publication year significantly moderate influential relationships, such as trust and continuance intention. Thus, mHealth developers should develop personalized continuous use promotion strategies based on user characteristics. Nature Publishing Group UK 2022-09-15 /pmc/articles/PMC9476418/ /pubmed/36109594 http://dx.doi.org/10.1038/s41746-022-00692-9 Text en © The Author(s) 2022 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 | Review Article Wang, Tong Wang, Wei Liang, Jun Nuo, Mingfu Wen, Qinglian Wei, Wei Han, Hongbin Lei, Jianbo Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis |
title | Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis |
title_full | Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis |
title_fullStr | Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis |
title_full_unstemmed | Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis |
title_short | Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis |
title_sort | identifying major impact factors affecting the continuance intention of mhealth: a systematic review and multi-subgroup meta-analysis |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9476418/ https://www.ncbi.nlm.nih.gov/pubmed/36109594 http://dx.doi.org/10.1038/s41746-022-00692-9 |
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