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Pre-Exposure Prophylaxis (PrEP) and 'Risk' in the news

Research output: Contribution to journalJournal articlepeer-review

E-pub ahead of print
<mark>Journal publication date</mark>8/03/2021
<mark>Journal</mark>Journal of Risk Research
Number of pages16
Publication StatusE-pub ahead of print
Early online date8/03/21
<mark>Original language</mark>English

Abstract

This study investigates 'risk' as discussed in news coverage and in relation to Pre-Exposure Prophylaxis (PrEP): a treatment that has been proven to restrict the transmission of the Human Immunodeficiency Virus (HIV). In the U.S. and the U.K. & Ireland, there are issues concerning the provision and take-up of PrEP, which can lead to health inequalities. Raising awareness and tackling stigma are priorities in ensuring that those who would benefit from PrEP can access it, since these are reported to be obstacles to potential users seeking out the treatment. The media has been shown to be an important resource for public understanding of health issues and there is evidence to suggest that the news media have contributed to the uncertainty and stigma around PrEP (Schwartz and Grimm 2016; Mowlabocus 2019), which has discouraged some from supporting and taking PrEP. In this study, I examine a corpus of 1424 news articles on PrEP (1 017 743 words) from the U.S. and the U.K. & Ireland, in the period 2016-2019. Using methods from corpus linguistics, I show that forms of 'risk' appear to a statistically significant degree in the data, providing a quantitative basis on which to explore these in more detail. Focusing on publications that use a high proportion of 'risk' words (compared with the overall average), I show that the focus on various risks associated with PrEP differs according to publication and that references to 'risk' are used both to advocate for the wider provision of PrEP and to caution against the effects of providing PrEP, i.e. concerns about 'risk compensation'. Corpus methods are shown to augment existing studies of PrEP coverage, providing a systematic method for identifying recurrent lexical features in the data and thereby showing how we can report the linguistic aspects of risk representation.