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Review
. 2023 May 4:25:e44030.
doi: 10.2196/44030.

Quality, Usability, and Effectiveness of mHealth Apps and the Role of Artificial Intelligence: Current Scenario and Challenges

Alejandro Deniz-Garcia #  1 , Himar Fabelo #  2   3 , Antonio J Rodriguez-Almeida  3 , Garlene Zamora-Zamorano  1   4 , Maria Castro-Fernandez  3 , Maria Del Pino Alberiche Ruano  1   4 , Terje Solvoll  5   6 , Conceição Granja  5   6 , Thomas Roger Schopf  5 , Gustavo M Callico  3 , Cristina Soguero-Ruiz  7 , Ana M Wägner  1   4 ; WARIFA Consortium  8
Collaborators, Affiliations
Review

Quality, Usability, and Effectiveness of mHealth Apps and the Role of Artificial Intelligence: Current Scenario and Challenges

Alejandro Deniz-Garcia et al. J Med Internet Res. .

Abstract

The use of artificial intelligence (AI) and big data in medicine has increased in recent years. Indeed, the use of AI in mobile health (mHealth) apps could considerably assist both individuals and health care professionals in the prevention and management of chronic diseases, in a person-centered manner. Nonetheless, there are several challenges that must be overcome to provide high-quality, usable, and effective mHealth apps. Here, we review the rationale and guidelines for the implementation of mHealth apps and the challenges regarding quality, usability, and user engagement and behavior change, with a special focus on the prevention and management of noncommunicable diseases. We suggest that a cocreation-based framework is the best method to address these challenges. Finally, we describe the current and future roles of AI in improving personalized medicine and provide recommendations for developing AI-based mHealth apps. We conclude that the implementation of AI and mHealth apps for routine clinical practice and remote health care will not be feasible until we overcome the main challenges regarding data privacy and security, quality assessment, and the reproducibility and uncertainty of AI results. Moreover, there is a lack of both standardized methods to measure the clinical outcomes of mHealth apps and techniques to encourage user engagement and behavior changes in the long term. We expect that in the near future, these obstacles will be overcome and that the ongoing European project, Watching the risk factors (WARIFA), will provide considerable advances in the implementation of AI-based mHealth apps for disease prevention and health promotion.

Keywords: artificial intelligence; big data; chronic disease prevention and management; mHealth; mobile health; mobile phone; noncommunicable diseases.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Conceptual block diagram of mobile health (mHealth) app function.
Figure 2
Figure 2
Block diagram of common workflow to apply data analysis and artificial intelligence methods for personalized medicine.
Figure 3
Figure 3
Challenges for artificial intelligence (AI) implementation in medicine [11].
Figure 4
Figure 4
Graphical concept of the Watching the risk factors (WARIFA) App [136].
See this image and copyright information in PMC

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