Leveraging Artificial Intelligence for Digital Symptom Management in Oncology: The Development of CRCWeb
AbstractDigital 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. T...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2025-06-01
|
| Series: | JMIR Cancer |
| Online Access: | https://cancer.jmir.org/2025/1/e68516 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850166038659858432 |
|---|---|
| author | Darren Liu Yufen Lin Runze Yan Zhiyuan Wang Delgersuren Bold Xiao Hu |
| author_facet | Darren Liu Yufen Lin Runze Yan Zhiyuan Wang Delgersuren Bold Xiao Hu |
| author_sort | Darren Liu |
| collection | DOAJ |
| description |
AbstractDigital 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. |
| format | Article |
| id | doaj-art-85c70d30bf3c45ee9ab21d08f3c7fcc4 |
| institution | OA Journals |
| issn | 2369-1999 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Cancer |
| spelling | doaj-art-85c70d30bf3c45ee9ab21d08f3c7fcc42025-08-20T02:21:34ZengJMIR PublicationsJMIR Cancer2369-19992025-06-0111e68516e6851610.2196/68516Leveraging Artificial Intelligence for Digital Symptom Management in Oncology: The Development of CRCWebDarren Liuhttp://orcid.org/0009-0004-5019-4402Yufen Linhttp://orcid.org/0000-0002-9182-2928Runze Yanhttp://orcid.org/0000-0002-6558-4567Zhiyuan Wanghttp://orcid.org/0000-0002-1611-2053Delgersuren Boldhttp://orcid.org/0000-0002-2983-571XXiao Huhttp://orcid.org/0000-0001-9478-5571 AbstractDigital 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.https://cancer.jmir.org/2025/1/e68516 |
| spellingShingle | Darren Liu Yufen Lin Runze Yan Zhiyuan Wang Delgersuren Bold Xiao Hu Leveraging Artificial Intelligence for Digital Symptom Management in Oncology: The Development of CRCWeb JMIR Cancer |
| title | Leveraging Artificial Intelligence for Digital Symptom Management in Oncology: The Development of CRCWeb |
| title_full | Leveraging Artificial Intelligence for Digital Symptom Management in Oncology: The Development of CRCWeb |
| title_fullStr | Leveraging Artificial Intelligence for Digital Symptom Management in Oncology: The Development of CRCWeb |
| title_full_unstemmed | Leveraging Artificial Intelligence for Digital Symptom Management in Oncology: The Development of CRCWeb |
| title_short | Leveraging Artificial Intelligence for Digital Symptom Management in Oncology: The Development of CRCWeb |
| title_sort | leveraging artificial intelligence for digital symptom management in oncology the development of crcweb |
| url | https://cancer.jmir.org/2025/1/e68516 |
| work_keys_str_mv | AT darrenliu leveragingartificialintelligencefordigitalsymptommanagementinoncologythedevelopmentofcrcweb AT yufenlin leveragingartificialintelligencefordigitalsymptommanagementinoncologythedevelopmentofcrcweb AT runzeyan leveragingartificialintelligencefordigitalsymptommanagementinoncologythedevelopmentofcrcweb AT zhiyuanwang leveragingartificialintelligencefordigitalsymptommanagementinoncologythedevelopmentofcrcweb AT delgersurenbold leveragingartificialintelligencefordigitalsymptommanagementinoncologythedevelopmentofcrcweb AT xiaohu leveragingartificialintelligencefordigitalsymptommanagementinoncologythedevelopmentofcrcweb |