JMIR Publications

ABSTRACT

Background:

Background:

The rapid expansion of generative artificial intelligence (AI) and AI-enabled digital health platforms has transformed the broader online health information environment. Cancer survivors increasingly rely on digital resources to obtain information related to diagnosis, treatment, survivorship, and follow-up care. However, limited research has examined whether cancer information burden and online information comprehension differ across population groups during the early generative-AI era.

Objective:

Objective:

This study examined cancer information burden, online cancer information comprehension, and related digital inequities among U.S. cancer survivors during the early generative-AI period using nationally representative survey data.

Methods:

Methods:

Data were drawn from pooled cycles of the Health Information National Trends Survey (HINTS) conducted in 2022 and 2024. Survey-weighted regression analyses were used to evaluate factors associated with cancer information burden among cancer survivors. Outcomes included perceived effort required to obtain cancer information, frustration during information seeking, difficulty understanding cancer information, and concerns regarding information quality. Composite measures of cancer information burden were also examined. Models adjusted for demographic and socioeconomic characteristics, including age, sex, race and ethnicity, educational attainment, household income, geographic region, and survey cycle.

Results:

Results:

Hispanic cancer survivors reported significantly greater cancer information burden, including higher levels of perceived effort and frustration associated with obtaining and understanding cancer-related information, compared with non-Hispanic White survivors. Non-Hispanic Asian survivors also demonstrated elevated levels of information burden, although estimates were less precise because of smaller subgroup sample sizes. Higher educational attainment was generally associated with lower levels of frustration and information burden. Female survivors reported lower levels of difficulty understanding cancer-related information and lower overall information burden than male survivors. Differences between survey cycles were not statistically significant after adjustment, suggesting that longstanding disparities in cancer information navigation may persist despite rapid changes in the digital health information environment during the early generative-AI era.

Conclusions:

Conclusions:

Significant inequities in cancer information burden persist among U.S. cancer survivors in the evolving digital health landscape. Racial and ethnic minority survivors and individuals with lower educational attainment may experience greater challenges navigating and understanding online cancer information. These findings highlight the importance of developing accessible, culturally responsive, and health literacy-sensitive digital communication strategies as AI-enabled health information systems continue to expand.