As predicted, perceptions of personal risk and intention to obtain vaccination against HBV were highest after presentation of narrative evidence, and risk perception mediated the effect of type of message evidence on intention. We propose that narrative evidence effectively promotes a sense of personal risk because it is less affected by defensive message processing resulting from the threat to important self-beliefs that seems inherent in health risk communication.
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Highly disconcerting at the time, in retrospective, the 2009 H1N1 influenza pandemic looks like much ado about nothing. As a consequence, many accused the media of having created an artificial hype or hysteria around the new virus, thus contributing to unwarranted public fear. The current paper set out to examine the validity of such accusations. We integrated empirical findings on whether the media dramatized H1N1 on a global scale through systematically reviewing prior content-analytic studies. We developed a coding scheme specifying three indicators of dramatized media coverage thattogetherinform about how mass media coverage about H1N1 may amplify risk perceptions in the public: (a) the volume of media coverage, (b) the media content presented, particularly an overemphasis of threat while neglecting measures of self-protection and (c) the tone of coverage. Results show that media attention was immense, that news content stressed threat over precautionary measures, while the pattern of coverage tonality remained nebulous due to conflicting findings. The present review also revealed a critical gap in existing knowledge about the tone of media coverage on H1N1, and discusses implications for future research on dramatization of public health risks by the media.
BackgroundIn May 2013, a measles outbreak began in the Netherlands among Orthodox Protestants who often refuse vaccination for religious reasons.ObjectiveOur aim was to compare the number of messages expressed on Twitter and other social media during the measles outbreak with the number of online news articles and the number of reported measles cases to answer the question if and when social media reflect public opinion patterns versus disease patterns.MethodsWe analyzed measles-related tweets, other social media messages, and online newspaper articles over a 7-month period (April 15 to November 11, 2013) with regard to topic and sentiment. Thematic analysis was used to structure and analyze the topics.ResultsThere was a stronger correlation between the weekly number of social media messages and the weekly number of online news articles (P<.001 for both tweets and other social media messages) than between the weekly number of social media messages and the weekly number of reported measles cases (P=.003 and P=.048 for tweets and other social media messages, respectively), especially after the summer break. All data sources showed 3 large peaks, possibly triggered by announcements about the measles outbreak by the Dutch National Institute for Public Health and the Environment and statements made by well-known politicians. Most messages informed the public about the measles outbreak (ie, about the number of measles cases) (93/165, 56.4%) followed by messages about preventive measures taken to control the measles spread (47/132, 35.6%). The leading opinion expressed was frustration regarding people who do not vaccinate because of religious reasons (42/88, 48%).ConclusionsThe monitoring of online (social) media might be useful for improving communication policies aiming to preserve vaccination acceptability among the general public. Data extracted from online (social) media provide insight into the opinions that are at a certain moment salient among the public, which enables public health institutes to respond immediately and appropriately to those public concerns. More research is required to develop an automatic coding system that captures content and user’s characteristics that are most relevant to the diseases within the National Immunization Program and related public health events and can inform official responses.
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