The explanation of a complex problem: A content analysis of causality in cancer news

Understanding causality is a critical part of developing preventive and treatment actions against cancer. Three main causality models—necessary, sufficient-component, and probabilistic causality have been commonly used to explain the causation between causal factors and risks in health science. Howe...

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Bibliographic Details
Published in:Public understanding of science (Bristol, England) England), 2022-01, Vol.31 (1), p.53-69
Main Authors: Peng, Wei, de Tuya, Gabriel Alexander, Eduardo, Andrea Alexandra, Vishny, Jessica Allison, Huang, Qian
Format: Article
Language:English
Subjects:
Cancer
Causality
Causation
Content analysis
Health risks
Humans
Intervention
Mass Media
Medical treatment
Neoplasms - etiology
News media
Risk
Risk analysis
Risk assessment
Risk factors
United States
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Summary:Understanding causality is a critical part of developing preventive and treatment actions against cancer. Three main causality models—necessary, sufficient-component, and probabilistic causality have been commonly used to explain the causation between causal factors and risks in health science. However, news media do not usually follow a strict protocol to report the causality of health risks. The purpose of this study was to describe and understand how the causation of cancer was articulated on news media. A content analysis of 471 newspaper articles published in the United States during two time-frames (2007–2008 and 2017–2018) was conducted. The analysis showed that probabilistic causality was most frequently used to explain the causal relationship between risk factors and cancer. The findings also uncovered other important details of news framing, including types and characteristics of risk factors, intervention measures, and sources of evidence. The results provided theoretical and practical implications for public understanding and assessment of cancer risks.
ISSN:0963-6625
1361-6609
DOI:10.1177/09636625211005249