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Theme Trends and Knowledge Structure on Mobile Health Apps: Bibliometric Analysis

BACKGROUND: Due to the widespread and unprecedented popularity of mobile phones, the use of digital medicine and mobile health apps has seen significant growth. Mobile health apps have tremendous potential for monitoring and treating diseases, improving patient care, and promoting health. OBJECTIVE:...

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Detalles Bibliográficos
Autores principales: Peng, Cheng, He, Miao, Cutrona, Sarah L, Kiefe, Catarina I, Liu, Feifan, Wang, Zhongqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7418015/
https://www.ncbi.nlm.nih.gov/pubmed/32716312
http://dx.doi.org/10.2196/18212
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author Peng, Cheng
He, Miao
Cutrona, Sarah L
Kiefe, Catarina I
Liu, Feifan
Wang, Zhongqing
author_facet Peng, Cheng
He, Miao
Cutrona, Sarah L
Kiefe, Catarina I
Liu, Feifan
Wang, Zhongqing
author_sort Peng, Cheng
collection PubMed
description BACKGROUND: Due to the widespread and unprecedented popularity of mobile phones, the use of digital medicine and mobile health apps has seen significant growth. Mobile health apps have tremendous potential for monitoring and treating diseases, improving patient care, and promoting health. OBJECTIVE: This paper aims to explore research trends, coauthorship networks, and the research hot spots of mobile health app research. METHODS: Publications related to mobile health apps were retrieved and extracted from the Web of Science database with no language restrictions. Bibliographic Item Co-Occurrence Matrix Builder was employed to extract bibliographic information (publication year and journal source) and perform a descriptive analysis. We then used the VOSviewer (Leiden University) tool to construct and visualize the co-occurrence networks of researchers, research institutions, countries/regions, citations, and keywords. RESULTS: We retrieved 2802 research papers on mobile health apps published from 2000 to 2019. The number of annual publications increased over the past 19 years. JMIR mHealth and uHealth (323/2802, 11.53%), Journal of Medical Internet Research (106/2802, 3.78%), and JMIR Research Protocols (82/2802, 2.93%) were the most common journals for these publications. The United States (1186/2802, 42.33%), England (235/2802, 8.39%), Australia (215/2802, 7.67%), and Canada (112/2802, 4.00%) were the most productive countries of origin. The University of California San Francisco, the University of Washington, and the University of Toronto were the most productive institutions. As for the authors’ contributions, Schnall R, Kuhn E, Lopez-Coronado M, and Kim J were the most active researchers. The co-occurrence cluster analysis of the top 100 keywords forms 5 clusters: (1) the technology and system development of mobile health apps; (2) mobile health apps for mental health; (3) mobile health apps in telemedicine, chronic disease, and medication adherence management; (4) mobile health apps in health behavior and health promotion; and (5) mobile health apps in disease prevention via the internet. CONCLUSIONS: We summarize the recent advances in mobile health app research and shed light on their research frontier, trends, and hot topics through bibliometric analysis and network visualization. These findings may provide valuable guidance on future research directions and perspectives in this rapidly developing field.
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spelling pubmed-74180152020-08-20 Theme Trends and Knowledge Structure on Mobile Health Apps: Bibliometric Analysis Peng, Cheng He, Miao Cutrona, Sarah L Kiefe, Catarina I Liu, Feifan Wang, Zhongqing JMIR Mhealth Uhealth Original Paper BACKGROUND: Due to the widespread and unprecedented popularity of mobile phones, the use of digital medicine and mobile health apps has seen significant growth. Mobile health apps have tremendous potential for monitoring and treating diseases, improving patient care, and promoting health. OBJECTIVE: This paper aims to explore research trends, coauthorship networks, and the research hot spots of mobile health app research. METHODS: Publications related to mobile health apps were retrieved and extracted from the Web of Science database with no language restrictions. Bibliographic Item Co-Occurrence Matrix Builder was employed to extract bibliographic information (publication year and journal source) and perform a descriptive analysis. We then used the VOSviewer (Leiden University) tool to construct and visualize the co-occurrence networks of researchers, research institutions, countries/regions, citations, and keywords. RESULTS: We retrieved 2802 research papers on mobile health apps published from 2000 to 2019. The number of annual publications increased over the past 19 years. JMIR mHealth and uHealth (323/2802, 11.53%), Journal of Medical Internet Research (106/2802, 3.78%), and JMIR Research Protocols (82/2802, 2.93%) were the most common journals for these publications. The United States (1186/2802, 42.33%), England (235/2802, 8.39%), Australia (215/2802, 7.67%), and Canada (112/2802, 4.00%) were the most productive countries of origin. The University of California San Francisco, the University of Washington, and the University of Toronto were the most productive institutions. As for the authors’ contributions, Schnall R, Kuhn E, Lopez-Coronado M, and Kim J were the most active researchers. The co-occurrence cluster analysis of the top 100 keywords forms 5 clusters: (1) the technology and system development of mobile health apps; (2) mobile health apps for mental health; (3) mobile health apps in telemedicine, chronic disease, and medication adherence management; (4) mobile health apps in health behavior and health promotion; and (5) mobile health apps in disease prevention via the internet. CONCLUSIONS: We summarize the recent advances in mobile health app research and shed light on their research frontier, trends, and hot topics through bibliometric analysis and network visualization. These findings may provide valuable guidance on future research directions and perspectives in this rapidly developing field. JMIR Publications 2020-07-27 /pmc/articles/PMC7418015/ /pubmed/32716312 http://dx.doi.org/10.2196/18212 Text en ©Cheng Peng, Miao He, Sarah L Cutrona, Catarina I Kiefe, Feifan Liu, Zhongqing Wang. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 27.07.2020. 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
Peng, Cheng
He, Miao
Cutrona, Sarah L
Kiefe, Catarina I
Liu, Feifan
Wang, Zhongqing
Theme Trends and Knowledge Structure on Mobile Health Apps: Bibliometric Analysis
title Theme Trends and Knowledge Structure on Mobile Health Apps: Bibliometric Analysis
title_full Theme Trends and Knowledge Structure on Mobile Health Apps: Bibliometric Analysis
title_fullStr Theme Trends and Knowledge Structure on Mobile Health Apps: Bibliometric Analysis
title_full_unstemmed Theme Trends and Knowledge Structure on Mobile Health Apps: Bibliometric Analysis
title_short Theme Trends and Knowledge Structure on Mobile Health Apps: Bibliometric Analysis
title_sort theme trends and knowledge structure on mobile health apps: bibliometric analysis
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7418015/
https://www.ncbi.nlm.nih.gov/pubmed/32716312
http://dx.doi.org/10.2196/18212
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