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Online Newspaper Framing of Non-Communicable Diseases: Comparison of Mainland China, Taiwan, Hong Kong and Macao

Author

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  • Angela Chang

    (Department of Communication, Faculty of Social Sciences, University of Macau, Macao, China)

  • Peter J. Schulz

    (Institute of Communication and Health, Lugano University, 6900 Lugano, Switzerland)

  • Angus Wenghin Cheong

    (ERS e-Research & Solutions, Macao, China)

Abstract

As non-communicable diseases (NCDs) are now well recognized as the leading cause of mortality among adult populations worldwide, they are also increasingly the focus of media coverage. As such, the objective of this study is to describe the framing of NCDs in the coverage of newspapers, with the understanding that it says something about the society producing it. Automatic content analysis was employed to examine disease topics, risks, and cost consequences, thus providing lay people with a chance of learning the etiology of NCDs and information available for fighting diseases. The result of the computational method identified a total of 152,810 news articles with one of the seven supra-categories of NCDs. The category of metabolic diseases was covered most frequently in the past ten years. Three health risks received ample attention in all 11 newspapers: stress burden, tobacco use, and genetic predispositions. The results evidenced how media framed risk information of illnesses would distort the way in which diseases were selected, interpreted, and the outcome communicated. Future research building on our findings can further examine whether news framing affects the way the readers perceive and prevent NCDs.

Suggested Citation

  • Angela Chang & Peter J. Schulz & Angus Wenghin Cheong, 2020. "Online Newspaper Framing of Non-Communicable Diseases: Comparison of Mainland China, Taiwan, Hong Kong and Macao," IJERPH, MDPI, vol. 17(15), pages 1-15, August.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:15:p:5593-:d:393964
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    References listed on IDEAS

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    1. Grimmer, Justin & Stewart, Brandon M., 2013. "Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts," Political Analysis, Cambridge University Press, vol. 21(3), pages 267-297, July.
    2. Chun‐Chih Chen & Ying‐Tzu Lin, 2018. "Impact of chronic disease on the mid‐age employment in Taiwan," International Journal of Health Planning and Management, Wiley Blackwell, vol. 33(2), pages 321-328, April.
    3. Daniel J. Hopkins & Gary King, 2010. "A Method of Automated Nonparametric Content Analysis for Social Science," American Journal of Political Science, John Wiley & Sons, vol. 54(1), pages 229-247, January.
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    Cited by:

    1. Angela Chang & Xuechang Xian & Matthew Tingchi Liu & Xinshu Zhao, 2022. "Health Communication through Positive and Solidarity Messages Amid the COVID-19 Pandemic: Automated Content Analysis of Facebook Uses," IJERPH, MDPI, vol. 19(10), pages 1-16, May.

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