Hostname: page-component-6766d58669-kn6lq Total loading time: 0 Render date: 2026-05-23T17:42:00.860Z Has data issue: false hasContentIssue false

Battles and breakthroughs: representations of dementia in the British press

Published online by Cambridge University Press:  17 September 2019

Annika Bailey*
Affiliation:
School of English, University of Nottingham, Nottingham, UK
Tom Dening
Affiliation:
Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, Nottingham, UK
Kevin Harvey
Affiliation:
School of English, University of Nottingham, Nottingham, UK
*
*Corresponding author. Email: annika.bailey@nottingham.ac.uk
Rights & Permissions [Opens in a new window]

Abstract

Media coverage of dementia can influence public and professional attitudes towards the syndrome, shaping societal knowledge of dementia and impacting how people with dementia are cared for. This paper reports on a study of news articles about dementia published in the British press in the years 2012–2017. The analysis combines the tools of corpus linguistics, a methodology for quantitatively surveying a vast amount of electronic linguistic data, with the qualitative perspectives of Critical Discourse Analysis, which seeks to uncover dominant discourses and ideologies. The most salient discourse that emerged from this analysis was the portrayal of dementia in biomedical terms, with a particular focus on the pathological processes of dementia, and pharmaceutical treatments and research. Keywords relating to this discourse are interrogated in detail, illuminating the linguistic strategies through which the pathology of dementia and people with dementia are depicted. This study highlights the challenges that this type of reporting presents to people living with dementia and their families, and points to the relevance of a discursive approach to understanding societal perceptions of dementia.

Information

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © Cambridge University Press 2019
Figure 0

Table 1. Top 30 keywords identified when comparing corpus of news articles with the British National Corpus