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Accepted for/Published in: JMIR Diabetes

Date Submitted: Aug 28, 2023
Date Accepted: Jun 4, 2024

The final, peer-reviewed published version of this preprint can be found here:

Scientific Production Dynamics in mHealth for Diabetes: Scientometric Analysis

Castillo-Valdez PF, Rodriguez-Salvador M, Ho YS

Scientific Production Dynamics in mHealth for Diabetes: Scientometric Analysis

JMIR Diabetes 2024;9:e52196

DOI: 10.2196/52196

PMID: 39172508

PMCID: 11377915

Research Dynamics in mHealth for Diabetes: Revealing Scientific Production Progress

  • Pedro Fernando Castillo-Valdez; 
  • Marisela Rodriguez-Salvador; 
  • Yuh-Shan Ho

ABSTRACT

Background:

The widespread use of mobile technologies in healthcare (mHealth) has facilitated disease management, especially for chronic illnesses such as diabetes. mHealth for Diabetes is an attractive alternative to reduce costs and overcome geographical and temporal barriers to improve patients’ conditions.

Objective:

To reveal the dynamics of scientific publications on mHealth for Diabetes to gain insights into who are the most prominent authors, countries, institutions, journals, and most cited documents.

Methods:

A Scientometric analysis based on a Competitive Technology Intelligence (CTI) methodology was developed. An innovative eight-step methodology, supported by experts was executed, considering scientific documents published between 1998 and 2021 in the SCI-Expanded database. Publication language, publication output characteristics, journals, countries and institutions, authors, and most cited and most impactful articles were identified.

Results:

Insights obtained show that a total of 1,574 scientific articles were published by 7,922 authors from 90 countries, with an average of 15 citations and 6.5 authors per article. These documents were published in 491 journals and 92 Web of Science categories. The most productive countries were the USA, followed by the UK, China, Australia, and South Korea. And the top three most productive institutions come from the USA. While the top three most cited articles were published in 2016, 2009, and 2017, and the top three most impactful articles were published in 2016 and 2017.

Conclusions:

This approach provides a comprehensive knowledge panorama of research productivity in mHealth for Diabetes, identifying new insights and opportunities for R&D and innovation, including collaboration with other entities, new areas of specialization and human resource development. The findings provided are useful for decision making in policy planning, resource allocation and identification of research opportunities. Benefiting researchers, health professionals, and decision-makers in their efforts to make significant contributions to the advancement of diabetes science.


 Citation

Please cite as:

Castillo-Valdez PF, Rodriguez-Salvador M, Ho YS

Scientific Production Dynamics in mHealth for Diabetes: Scientometric Analysis

JMIR Diabetes 2024;9:e52196

DOI: 10.2196/52196

PMID: 39172508

PMCID: 11377915

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© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.