Insights into the Technological Evolution and Research Trends of Mobile Health: Bibliometric Analysis

Abstract

Background/Objectives: Smartphones, with their widespread popularity and diverse apps, have become essential in our daily lives, and ongoing advancements in information technology have unlocked their significant potential in healthcare. Our goal is to identify the future research directions of mobile health (mHealth) by examining its research trends and emerging hotspots. Methods: This study collected mHealth-related literature published between 2005 and 2024 from the Web of Science database. We conducted a descriptive statistic of the annual publication count and categorized the data by authors and institutions. In addition, we developed visualization maps to display the frequency of keyword co-occurrences. Furthermore, overlay visualizations were created to showcase the average publication year of specific keywords, helping to track the changing trends in mHealth research over time. Results: Between 2005 and 2024, a total of 6093 research papers related to mHealth were published. The data have revealed a rapid increase in the number of publications since 2011. However, it was found that research on mHealth has reached a saturation point since 2021. The University of California was the dominant force in mHealth research, with 248 articles. The University of California, the University of London, Harvard University, and Duke University are actively collaborating, which shows a geographical pattern of collaboration. From the analysis of keyword co-occurrence and timeline, the research focus has gradually shifted from solely mHealth technologies to exploring how new technologies, such as artificial intelligence (AI) in mobile apps, can actively intervene in patient conditions, including breast cancer, diabetes, and other chronic diseases. Privacy protection policies and transparency mechanisms have emerged as an active research focus in current mHealth development. Notably, cutting-edge technologies such as the Internet of Things (IoT), blockchain, and virtual reality (VR) are being increasingly integrated into mHealth systems. These technological convergences are likely to constitute key research priorities in the field, particularly in addressing security vulnerabilities while enhancing service scalability. Conclusions: Although the volume of core research in mobile health (mHealth) is gradually declining, its practical applications continue to expand across diverse domains, increasingly integrating with multiple emerging technologies. It is believed that mobile health still holds enormous potential.

Keywords: bibliometric analysis; data visualization; digital intervention; mHealth app; mental health; mobile health (mHealth).

Figure A1

Number of publications per journal from 2005 to 2024.

Figure A2

Top 10 journals by citation count.

Figure A3

Keyword clustering analysis of mHealth research using CiteSpace. Note: Node colors represent different thematic clusters labeled with their dominant topics, node size reflects the importance or frequency of the terms, and edges show relationships or co-occurrence between terms within and across clusters.

Figure 1

Flowchart of the literature selection all the data were collected from Web of Science core collection. Notes. TS: topic search.

Figure 2

Number of publications about mHealth from 2005 to 2024 in WOS. Note: This figure shows the annual publication counts related to mobile health (mHealth) indexed in Web of Science from 2005 to 2024. The data reveals significant growth since 2010, with acceleration after 2015, corresponding to smartphone proliferation and digital health advances.

Figure 3

Number of publications about mHealth from 2005 to 2024 in PubMed. Note: This figure shows publications on mHealth in PubMed which shows potential growth from 2005 (<10 publications/year) to 2022 (peak of 1472 publications). After 2022, publication numbers slightly decreased but remained high (>1300/year).

Figure 4

Number of publications about mHealth from 2021 to 2024 in Google Scholar. Note: This figure displays the number of mHealth publications in Google Scholar from 2021 to 2024. Publications increased dramatically from 162,900 in 2021 to a peak of 256,900 in 2022. After 2022, there was a sharp decline to 73,600 publications in 2023, followed by a moderate recovery to 99,300 in 2024.

Figure 5

Trend in Digital Health Keywords from 2022 to 2024. Note: Digital health trends (2022–2024) show Digital Diagnostics surging early and then plateauing, while AI-driven Health dramatically increased in the final year. Machine learning in healthcare grew steadily throughout. Precision Medicine showed modest growth, while Digital Health and Digital Health Tools remained relatively unchanged. This suggests a shift from diagnostic technologies toward AI applications in healthcare.

Figure 6

Networks of publications from different institutions about mHealth. Note: Node size represents academic influence, color indicates active years (red for 2011, yellow for 2021), edge thickness reflects collaboration strength, and purple rings highlight high-centrality institutions.

Figure 7

The top 20 high-frequency keywords in the field of mHealth research. Note: Figure shows the top 20 keywords in mHealth research. Mobile health leads with 580 occurrences, followed by health (548), intervention (539), smartphone (508), and mobile application (457). This distribution highlights the field’s focus on mobile technologies for health interventions, with technical and implementation aspects as key research priorities.

Figure 8

Keyword Clustering in mHealth Research Visualized Using VOSviewer. Note: Node colors represent different thematic clusters labeled with their dominant topics. This network visualization maps the digital health research landscape, showing distinct clusters: mental health (blue), digital technologies (red), lifestyle interventions (green), and chronic disease management (yellow). Key bridging concepts include smartphones and mobile applications.

Figure 9

Keyword Clustering Analysis of mHealth Research Using CiteSpace. Note: This visualization presents a thematic clustering of digital health research areas, organized into 11 distinct clusters identified by numbers (#0–#10). Each cluster represents a key research domain: children’s health (pink, top left), privacy concerns (light green, top), artificial intelligence applications (light blue, top right), technology acceptance (green, top), mobile health and telemedicine (yellow, center right), digital health interventions (red, center right), mobile applications (light blue, center left), physical activity (light green, bottom center), mental health (orange, center), contact tracing (deep blue, bottom left), and ecological momentary assessment methods (purple, bottom).

Figure 10

Timeline of Research Trends and Clusters in mHealth: 2005–2024. Note: This horizontal flow visualization displays the digital health research landscape as a timeline progression, with 11 color-coded thematic streams (#0–#10) running left to right. The red nodes represent research publications, with node size indicating citation impact. Key themes include digital health (red), mental health (orange), mobile health (yellow), physical activity (light green), technology acceptance (green), privacy (dark green), artificial intelligence (light blue), mobile applications (blue), contact tracing (dark blue), ecological momentary assessment (deep purple) and children (pink).

Figure 11

Top 30 Keywords with the Strongest Citation Bursts. Note: Figure 11 shows keyword citation burst patterns in mHealth research (2005–2024). Early bursts (2006–2012) focused on foundational concepts like healthcare and cell phones, with “mobile phones” having the strongest burst (13.44) in 2011. Mid-period (2013–2017) emphasized applications like weight loss and text messaging. Recent bursts (2020–2024) concentrate on digital interventions, young people, and mobile health apps, reflecting the field’s current priorities. This keyword citation burst visualization employs a three-color system to effectively represent temporal patterns in research focus. The light blue background spans the entire study period (2005–2024), providing a consistent reference frame. Overlaid on this, darker blue/teal segments indicate when specific keywords actively appeared in the literature, marking their presence in academic discourse from first emergence to final mention. The striking red sections highlight periods of citation bursts–moments when particular keywords experienced dramatic spikes in scholarly attention.