Leveraging Artificial Intelligence for Digital Symptom Management in Oncology: The Development of CRCWeb.

Journal: JMIR cancer
Published Date:

Abstract

UNSTRUCTURED: Digital health interventions offer promise for scalable and accessible healthcare, but access is still limited by some participatory challenges, especially for disadvantaged families facing limited health literacy, language barriers, low income, or living in marginalized areas. These issues are particularly pronounced for colorectal cancer (CRC) patients, who often experience distressing symptoms and struggle with educational materials due to complex jargon, fatigue, or reading level mismatches. To address these issues, we developed and assessed the feasibility of a digital health platform, CRCWeb, to improve the accessibility of educational resources on symptom management for disadvantaged CRC patients and their caregivers facing limited health literacy or low income. CRCWeb was developed through a stakeholder-centered participatory design approach. Two-phase semi-structured interviews with patients, caregivers, and oncology experts informed the iterative design process. From the interviews, we developed the following five key design principles: user-friendly navigation, multimedia integration, concise and clear content, enhanced accessibility for individuals with vision and reading disabilities, and scalability for future content expansion. Initial feedback from iterative stakeholder engagements confirmed high user satisfaction, with participants rating CRCWeb an average of 3.98 out of 5 on the post-intervention survey. Additionally, using GenAI tools, including large language models (LLMs) like ChatGPT and multimedia generation tools such as Pictory, complex healthcare guidelines were transformed into concise, easily comprehensible multimedia content, and made accessible through CRCWeb. User engagement was notably higher among disadvantaged participants with limited health literacy or low income, who logged into the platform 2.52 times more frequently than non-disadvantaged participants. The structured development approach of CRCWeb demonstrates that GenAI-powered multimedia interventions can effectively address healthcare accessibility barriers faced by disadvantaged CRC patients and caregivers with limited health literacy or low income. This structured approach highlights how digital innovations can enhance healthcare.

Authors

  • Sizuo Liu
    Department of Computer Science, Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, US.
  • Yufen Lin
    Nell Hodgson Woodruff School of Nursing, Winship Cancer Institute, Emory University, Atlanta, US.
  • Runze Yan
    Center for Data Science, Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GE.
  • Zhiyuan Wang
    Department of Systems and Information Engineering, University of Virginia, USA.
  • Delgersuren Bold
    Center for Data Science, Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GE.
  • Xiao Hu
    Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, United States.

Keywords

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