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AI Applications for Chronic Condition Self-Management: Scoping Review.

Misun Hwang1, Yaguang Zheng2, Youmin Cho3

  • 1School of Nursing, University of Michigan, Ann Arbor, MI, United States.

Journal of Medical Internet Research
|April 8, 2025
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) shows promise for chronic condition self-management, but most applications are in early development. Further research is needed to optimize AI for better patient outcomes in medical, behavioral, and emotional self-care.

Keywords:
artificial intelligencechronic diseaseemotional self-managementgenerative AIself-management

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Area of Science:

  • Digital Health
  • Artificial Intelligence in Healthcare
  • Patient Self-Management

Background:

  • Artificial intelligence (AI) offers significant potential to enhance self-management support for individuals with chronic conditions.
  • Current AI applications often fall short of patient needs and performance expectations in chronic condition self-management.
  • Understanding AI's role in self-management is crucial for developing effective, tailored solutions.

Purpose of the Study:

  • To comprehensively review AI applications for chronic condition self-management, focusing on medical, behavioral, and emotional tasks.
  • To identify the developmental stages of current AI technologies in this domain.
  • To pinpoint existing knowledge gaps in AI for chronic condition self-management.

Main Methods:

  • A systematic literature review was performed using data from January 2011 to October 2024.
  • Searches were conducted across four databases: PubMed, Web of Science, CINAHL, and PsycINFO.
  • Studies included adult populations with chronic conditions, focusing on AI technologies supporting self-management, adhering to PRISMA-ScR guidelines.

Main Results:

  • Out of 1873 retrieved articles, 66 met the inclusion criteria.
  • Diabetes was the most frequently studied condition (30%).
  • AI primarily supported medical (68%) and behavioral (41%) self-management, with less focus on emotional self-management (21%). Conversational AI (32%) and machine learning (24%) were common. Most AI technologies were in early development (algorithm development or feasibility testing).

Conclusions:

  • AI technologies are being developed for various chronic condition self-management aspects, including medication, symptoms, and lifestyle.
  • Emotional self-management currently has fewer AI applications, and most AI tools are in preliminary developmental stages.
  • Further research is essential to validate AI integration for optimal chronic condition self-management outcomes.