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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Apr 17, 2024
Date Accepted: Feb 20, 2025

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

AI Applications for Chronic Condition Self-Management: Scoping Review

Hwang M, Zheng Y, Cho Y, Jiang Y

AI Applications for Chronic Condition Self-Management: Scoping Review

J Med Internet Res 2025;27:e59632

DOI: 10.2196/59632

PMID: 40198108

PMCID: 12015343

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Artificial Intelligence Applications for Chronic Condition Self-Management: A Narrative Review

  • Misun Hwang; 
  • Yaguang Zheng; 
  • Youmin Cho; 
  • Yun Jiang

ABSTRACT

Background:

Artificial intelligence (AI) has significant potential in promoting and supporting self-management in patients with chronic conditions. However, there is a lack of understanding of how current AI technologies apply to address specific chronic condition self-management issues. Evidence is needed to guide the development and selection of appropriate AI solutions to support self-management in patients with chronic conditions.

Objective:

This study aims to provide a narrative review of the literature on AI applications for chronic condition self-management, categorizing self-management components supported by AI technologies based on three essential self-management tasks: medical, behavioral, and emotional management, and identify the current developmental stages of AI applications for chronic condition self-management.

Methods:

A literature review was conducted for studies published in English between January 2011 and March 2023. Four databases, including PubMed, Web of Science, CINAHL, and PsycINFO, were searched using combined terms related to self-management and artificial intelligence. The inclusion criteria included studies focused on the adult population with any type of chronic conditions and AI technologies supporting self-management.

Results:

Of the 1288 articles retrieved from the search, 49 (3.8%) were eligible and included in this review. The most commonly studied chronic condition was diabetes (15/49, 30.6%). Regarding self-management tasks, the majority of studies aim to support medical (31/49, 63.3%) and/or behavioral self-management (20/49, 40.8%), but there is a lack of focus on emotional self-management (9/49, 18.4%). Conversational AI (13/49, 26.5%) and multiple machine learning algorithms (13/49, 26.5%) were frequently used types of AI technologies. Categorization of the technology development stage identified that most studies remain in the algorithm development or early feasibility testing stages.

Conclusions:

The application of AI technologies in chronic condition management promises to empower patients to effectively perform self-management. AI technology has been widely applied in varied chronic condition self-management; however, most studies remain in the early stages. More studies are needed to generate evidence for integrating AI in self-management to obtain optimal outcomes.


 Citation

Please cite as:

Hwang M, Zheng Y, Cho Y, Jiang Y

AI Applications for Chronic Condition Self-Management: Scoping Review

J Med Internet Res 2025;27:e59632

DOI: 10.2196/59632

PMID: 40198108

PMCID: 12015343

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