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

IF 3.3 Q2 ONCOLOGY
JMIR Cancer Pub Date : 2025-06-16 DOI:10.2196/68516
Darren Liu, Yufen Lin, Runze Yan, Zhiyuan Wang, Delgersuren Bold, Xiao Hu
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引用次数: 0

Abstract

Unlabelled: Digital health interventions offer promise for scalable and accessible health care, 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 patients with colorectal cancer (CRC), 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 patients with CRC and their caregivers facing limited health literacy or low income. CRCWeb was developed through a stakeholder-centered participatory design approach. Two-phase semistructured interviews with patients, caregivers, and oncology experts informed the iterative design process. From the interviews, we developed the following 5 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 postintervention survey. Additionally, using generative artificial intelligence tools, including large language models like ChatGPT and multimedia generation tools such as Pictory, complex health care 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 nondisadvantaged participants. The structured development approach of CRCWeb demonstrates that generative artificial intelligence-powered multimedia interventions can effectively address health care accessibility barriers faced by disadvantaged patients with CRC and caregivers with limited health literacy or low income. This structured approach highlights how digital innovations can enhance health care.

利用人工智能进行肿瘤数字症状管理:CRCWeb的发展。
未标记:数字卫生干预措施为可扩展和可获得的卫生保健提供了希望,但可获得性仍然受到一些参与性挑战的限制,特别是对于卫生知识有限、语言障碍、低收入或生活在边缘地区的弱势家庭。这些问题对于结直肠癌(CRC)患者尤其明显,他们经常经历令人痛苦的症状,并且由于复杂的术语,疲劳或阅读水平不匹配而与教育材料作斗争。为了解决这些问题,我们开发并评估了数字健康平台CRCWeb的可行性,以改善健康素养有限或收入较低的CRC弱势患者及其护理人员对症状管理教育资源的可及性。CRCWeb是通过以利益相关者为中心的参与式设计方法开发的。与患者、护理人员和肿瘤专家进行的两阶段半结构化访谈为迭代设计过程提供了信息。从采访中,我们制定了以下5个关键设计原则:用户友好的导航,多媒体集成,简洁清晰的内容,增强视力和阅读障碍人士的可访问性,以及未来内容扩展的可扩展性。从迭代的涉众参与中获得的初始反馈证实了用户的高满意度,参与者在干预后的调查中平均给CRCWeb打分3.98分(满分5分)。此外,使用生成式人工智能工具,包括ChatGPT等大型语言模型和Pictory等多媒体生成工具,将复杂的医疗指南转换为简洁、易于理解的多媒体内容,并通过CRCWeb提供访问。健康知识有限或收入较低的弱势参与者的用户参与度明显较高,他们登录平台的频率是非弱势参与者的2.52倍。CRCWeb的结构化开发方法表明,生成式人工智能驱动的多媒体干预措施可以有效解决CRC弱势患者和健康素养有限或收入较低的护理人员面临的卫生保健可及性障碍。这种结构化方法突出了数字创新如何能够加强医疗保健。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
JMIR Cancer
JMIR Cancer ONCOLOGY-
CiteScore
4.10
自引率
0.00%
发文量
64
审稿时长
12 weeks
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