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Improvement for most, but not all: changes in newspaper coverage of mental illness from 2008 to 2019 in England

Published online by Cambridge University Press:  05 November 2020

R. Hildersley*
Affiliation:
Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England
L. Potts
Affiliation:
Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England
C. Anderson
Affiliation:
Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England
C. Henderson
Affiliation:
Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, England
*
Author for correspondence: Rosanna Hildersley, E-mail: rosanna.hildersley@kcl.ac.uk
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Abstract

Aims

Time to Change, an anti-stigma programme in England, has worked to reduce stigma relating to mental illness in many facets of life. Newspaper reports are an important factor in shaping public attitudes towards mental illnesses, as well as working as a barometer reflecting public opinion. This study aims to assess the way that coverage of mental health topics and different mental illnesses has changed since 2008.

Method

Articles covering mental health in 18 different newspapers were retrieved using keyword searches on two randomly chosen days of each month in 2008, 2009, 2010, 2011, 2013, 2014, 2016 and 2019. A content analysis approach using a structured coding framework was used to extract information from the articles. Logistic regression models were used to estimate the change in odds of each hypothesised stigmatising or anti-stigmatising element occurring in 2019 compared to 2008 and 2016 with a Wald test to assess the overall significance of year as a predictor in the model. Further logistic regression models were used to assess the association between the diagnosis that an article was about and the odds that it was stigmatising, and whether this relationship is moderated by year of publication.

Results

A total of 6731 articles were analysed, and there was a significant increase in anti-stigmatising articles in 2019 compared to 2008 (OR 3.16 (2.60–3.84), p < 0.001) and 2016 (OR 1.40 (1.16–1.69), p < 0.001). Of the 5142 articles that specified a diagnosis, articles about schizophrenia were 6.37 times more likely to be stigmatising than articles about other diagnoses (OR 6.37 (3.05–13.29) p < 0.001), and there was evidence that the strength of this relationship significantly interacted with the year an article was published (p = 0.010). Articles about depression were significantly less likely to be stigmatising (OR 0.59 (0.69–0.85) p = 0.018) than those about other diagnoses, while there was no difference in coverage of eating disorders v. other diagnoses (OR 1.37 (0.67–2.80) p = 0.386); neither of these relationships showed an interaction with the year of publication.

Conclusion

Anti-stigma programmes should continue to work with newspapers to improve coverage of mental illness. However, interventions should consider providing specific guidance and promote awareness of rarer mental illnesses, such as schizophrenia, and evaluation should examine whether reductions in stigma extend to people with all mental illness diagnoses.

Information

Type
Original 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 © The Author(s), 2020. Published by Cambridge University Press
Figure 0

Table 1. Elements or central themes and ideas included in the article

Figure 1

Table 2. Frequencies and proportions of elements and overall categories across articles, by year.

Figure 2

Table 3. Results from the logistic regression models comparing the association between the odds that a stigmatising element or anti-stigmatising element is present in 2019 compared to (a) 2008 and (b) 2016

Figure 3

Table 4. Frequencies and proportions of diagnoses across articles, by year

Figure 4

Fig. 1. Results from the predictive marginal models showing the probability that an article is stigmatising if the article discusses (a) schizophrenia, (b) depression or (c) eating disorders compared to other diagnoses, with 95% confidence intervals.

Figure 5

Table 5. Results from the logistic regression models (a) Odds ratio describing the odds that an article is stigmatising when the diagnosis is present v. the diagnosis not being present, adjusted for the year published and (b) Wald test showing the significance of the interaction between a diagnosis being associated with being stigmatising and the year published

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