- News Media's Surveillance and Gatekeeping in Representing Health Risk.
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Myoungsoon You, Youngkee Ju
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J Prev Med Public Health. 2010;43(3):279-282.
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DOI: https://doi.org/10.3961/jpmph.2010.43.3.279
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- OBJECTIVES
This study investigates whether Korean news media pay more attention to emerging diseases than chronic ones, and whether they closely follow the changes in the magnitude of health risks of chronic or well-known diseases. These two features are expected to appear as the result of surveillance function served by health journalism that should be the main source of the public's risk perception. METHODS: The number of stories published in 10 newspapers containing the words, 'SARS,' 'Bovine Spongiform Encephalopathy,' 'Avian Influenza,' and 'Influenza A virus' was compared with the number of stories on chronic or well-known diseases. We also counted the annual number of stories, published in a 12-year period, containing following terms: 'cancer,' 'diabetes,' 'hypertension,' 'pneumonia,' and 'tuberculosis.' The number was compared with the actual mortality of each disease. RESULTS: Although cancer represented the primary cause of mortality, the newspapers covered key emerging diseases more than cancer or other well-known diseases. Also, media coverage of 'pneumonia' and 'tuberculosis' did not vary in accordance with changes in the mortality of each disease. However, the news media coverage did vary in accordance with the mortality of 'cancer,' 'diabetes,' and 'hypertension.' CONCLUSIONS: Korean health journalism was found to have both strong and weak points. The news media reduced the relative level of attention given to pneumonia and tuberculosis. Bearing in mind the major influence of news coverage on risk perception, health professionals need to be more proactive about helping to improve Korean health journalism.
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Summary
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Citations
Citations to this article as recorded by  - Coronavirus mapping in scientific publications: When science advances rapidly and collectively, is access to this knowledge open to society?
Simone Belli, Rogério Mugnaini, Joan Baltà, Ernest Abadal
Scientometrics.2020; 124(3): 2661. CrossRef
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