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.

了解因果关系是制定癌症预防和治疗措施的关键部分。三种主要的因果关系模型——必要、充分分量和概率因果关系已被普遍用于解释健康科学中因果因素与风险之间的因果关系。然而，新闻媒体通常不会遵循严格的协议来报道健康风险的因果关系。这项研究的目的是描述和了解癌症的病因是如何在新闻媒体上表达的。对两个时间段（2007-2008 年和 2017-2018 年）在美国发表的 471 篇报纸文章进行了内容分析。分析表明，概率因果关系最常用于解释危险因素与癌症之间的因果关系。调查结果还揭示了新闻框架的其他重要细节，包括风险因素的类型和特征、干预措施和证据来源。该结果为公众理解和评估癌症风险提供了理论和实践意义。