Common frames for conceptualizing mental illness in news media and their effect on public attitudes

Stigmatizing attitudes towards mental illness pose a significant societal problem and its adverse effects permeate all areas of life for those affected. Among others, stigma leads to barriers in accessing care and a decreased likelihood of remaining in treatment (Corrigan et al. 2014), difficulty obtaining and retaining employment (Corrigan and Watson 2002) as well as increased social distance in community settings (Henderson et al. 2016). According to the Stigma Shout survey, 9 in 10 service users feel that stigmatization is negatively affecting their lives ('Time to Change', 2008).

The largest anti-stigma campaign in England to date is the 'Time to Change' campaign. 'Time to Change' has so far operated in three phases (2007-2011; 2011-2015; 2016-2021) and focuses on de-stigmatizing mental. While this campaign has contributed to changing attitudes towards mental illness, in order to decrease stigma successfully and lastingly, there needs to be further research into how mental illness is constructed in public disocurse and in what ways certain discursive framings of mental illness contribute to different attitudes.

In this project I will examine the language used to construct mental illness in mass media before and during the 'Time to Change' campaign, and how this language instantiates and affects attitudes, by developing corpus-based methods to identify metaphors as they emerge in discourse. Currently, the effect of anti-stigma campaigns is predominantly measured using attitude surveys (Rossetto et al., 2019). Attitude surveys are problematic for measuring attitudes because participants are often inclined to misrepresent themselves (e.g. to appear more favourably) and it is virtually impossible to access less overt attitudes, such as implicit stigma (Stull et al., 2013).

One way to indirectly gauge public attitudes is through metaphor. Essentially, metaphors structure one domain (target domain) in terms of another (source domain), thereby highlighting certain aspects in the target domain, while hiding others (Lakoff and Johnson, 1980). In more recent work, this has been described as the 'framing power' of metaphor (Semino, Demjen, Demmen, 2016). Regarding attitudes, this makes metaphor a powerful tool in both investigating implicit conceptualizations of mental illness expressed through language. However, to study public attitudes effectively, it is necessary to draw on large amounts of data, which requires the development of corpus-based methods.

The aims of this research are:

- to develop to develop a corpus-based semi-automatic method for large-scale identification and tracking of systematic metaphor use in discourse
- to apply this method to a large corpus of media discourse and identify common metaphors and their framing power before and during the phases of the 'Time to Change' campaign
- to evaluate the effects of dominant frames and metaphors on attitudes of discourse participants in an experimental setting

Overall, this project will involve the development of novel methods for the corpus-based identification and analysis of metaphors and their framing effects and apply this to the portrayal of mental illness in the news. It will contribute to a better understanding of how the linguistic construction of mental illness in the UK has changed over time, especially before and during the 'Time to Change' anti-stigma campaign. Ultimately, this research can be utilized to improve future anti-stigma campaigns, but also in general to gauge public attitudes towards various issues on basis of their language behaviour.