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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorArentshorst, M.E.
dc.contributor.authorVissers, S.M.R.
dc.date.accessioned2017-08-12T17:01:09Z
dc.date.available2017-08-12T17:01:09Z
dc.date.issued2017
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/26826
dc.description.abstractIn this thesis the Dutch media coverage on personalized medicine (PM) is analyzed in order to distinguish frames used by the media that can influence the public opinion on this potentially beneficial innovative medical therapy. Frames are a way to structure an event in which it emphasizes a certain aspect of it. When scientific events, linked to PM, are framed as negatively influencing the health of individuals, the public opinion can as a result be negative about PM. This can influence the diffusion and implementation activity within the innovation process that PM is currently engaged in. This information can be in the interest of risk managers in business and policy makers in the public sphere when being engaged in PM. The frames are identified by conducting a content analysis on the Dutch news articles, using LexisNexis Academic databank for the collection of the media sources. Following was a qualitative analysis by NVivo which resulted in coding of the articles based on the 4 elements of a frame according to Entman (1993). Frames are derived from a pattern of elements across several newspapers identified by the Wards method, a hierarchical cluster analysis by SPSS. This resulted in one frame with an explicit judgement of value: “PM: a benefit to (future) research” and one less explicit frame: “PM: it’s challenges and (potential) benefits”. On the latter frame was elaborated with a second analysis from which two additional frames could be distinguished: “PM: ethics meets economics” and “PM: practical genetics”.
dc.description.sponsorshipUtrecht University
dc.format.extent676319
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.titleDutch media framing personalized medicine
dc.type.contentBachelor Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordspersonalized medicine, innovation management, media framing, hierarchical cluster analysis, content analysis, media frame analysis
dc.subject.courseuuLiberal Arts and Sciences


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