||5R37CA259156-02 Interpret this number
||Iowa State University
||Using Natural Language Processing and Crowdsourcing to Monitor and Evaluate Public Information and Communication Disparities About Colon Cancer Screening
Colorectal cancer (CRC) incidence and death rates are higher among Black Americans than non-Hispanic
White Americans. While some CRC-related disparities have decreased (e.g., incidence and stage of
presentation), disparities persist in the context of CRC screening (CRCS). Studies suggest that supportive and
information-rich social networks, both online and offline, could improve CRCS among Black Americans. A
growing body of evidence indicates the importance of online sources of health information seeking and
scanning about CRC and CRCS, but little is known about the impact of the messages that individuals are
encountering on these platforms. Research on the content and volume of messages White and Black
Americans encounter from online health information sources is still unclear—particularly regarding any
disparities that exist about what specific information is sought, scanned, or shared by Black Americans. There
is a critical need to understand which messages resonate among populations at-risk for specific diseases (e.g.,
CRC) and who may have concerns about engaging in early detection behaviors (e.g., CRCS) and may face
disparities in exposure to public information online. The proposed project utilizes and applies novel cancer
communication surveillance approaches (e.g., natural language processing and crowdsourcing) to examine
public health communication about CRC prevention and control. Aim 1 will use computational, natural
language processing approaches to capture and analyze digital and social media information about CRC and
CRCS to identify prominent messages, sources and types of misinformation, and information inequalities. This
approach offers an efficient, effective, and responsive method to monitor (mis)information and emerging
messages about CRCS. Aim 2 will use a crowdsourcing approach (wiki surveys) to assess population
perceptions of public information and messages about CRCS. Recruiting nationally representative samples of
White (N = 1,000) and Black American (N = 1,000) adults ages 45-74, we will use an innovative data collection
procedure known as wiki surveys to rank candidate messages as potential message targets in strategic efforts
to promote CRCS. For Aim 3, we will conduct a randomized controlled message trial (N = 1,600) to determine
the validity of the wiki survey approach to selecting messages for targeted audience segments. We will use
data collected from Study 2 to identify four sets of messages with strong arguments respective to each target
audience’s rankings: highest rated messages for both audiences, highest rated messages for target in-group,
highest rated messages for target out-group, and middle-/median-rated messages. We will cross those
message categories with target audience (White/Black American) to test if messages selected via the wiki
survey are associated with intentions to adhere to screening recommendations in the future and share CRCS
messages. The project will offer evidence to help determine the validity and scalability of these novel methods,
which is essential to innovate formative research and evaluation approaches in the future.
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