(WIP) News coverage about cancer screening in the Netherlands: A content analysis: Presenter(s): Inge Stortenbeker, Radboud University, Netherlands

News media content and social media discussions affect cancer screening behavior (e.g. Niederdeppe et al., 2013). Though participation rates of cancer screening programs in the Netherlands (i.e. cervical, breast and colorectal cancer screening) are generally high, negative news reports and misinformation may negatively affect the public perception of and participation in cancer screening programs. Yet, it is unknown how the news media report about cancer screening, and how this may affect informed decision making. The current study will therefore analyze news media coverage about cancer screening in the Netherlands. We aim to investigate 1) the volume, tone and content of news media reports, 2) how media coverage may differ for different cancer types, and 3) how it may have changed over time (2010 to 2022). A quantitative content analysis of Dutch news reports from 2010 to 2022. News reports will be retrieved from the LexisNexis database with a search query including strings related to cancer and screening methods. We will manually (double-)code approximately 1.000 news articles. Content of news media reports will be coded in term of framing (e.g. risk framing), costs and benefits (e.g. overdiagnosis vs. early detection) and linguistic features (e.g. metaphors). The manual annotation will serve as a ground truth dataset to develop machine learning classifiers using traditional models (e.g. Support Vector Machines) and state-of-the art models (e.g. Bidirectional Encoder Representations from Transformers; BERT) to classify the full corpus (approximately 10.000 news articles). The codebook is currently being developed, and we intend to use a similar codebook to annotate social media posts related to cancer screening. Relevant questions for feedback are: What are important topics that should be involved in the codebook? Could this be different for our social media data? What are the potential implications of this project for patient-provider interactions?