This is a plain English summary of an original research article
Misconceptions and negative attitudes to dementia are widespread on Twitter. Researchers worked with carers of people living with dementia. They found that 1 in 4 tweets about dementia used language that carers considered dehumanising or outdated. Tweets described politicians, for example, as demented or senile.
The language used about dementia can have a profoundly negative impact on people directly or indirectly affected by the condition. It can increase their feelings of hopelessness and social exclusion and reduce their ability to cope.
In this study, carers worked in focus groups to come up with search terms related to dementia. The researchers used these terms, along with those from previous research, to search Twitter. Over 4 days, they found 50,000 tweets that referred to dementia. They created a subset of 1,497 tweets (both neutral and negative) for carers to analyse.
Carers found that 44% tweets used stigmatising or weaponizing words (using dementia-related words as insults). Negative tweets included incorrect statements, or made armchair diagnoses (people diagnosed dementia in someone they had never met, often a public figure). Some tweets minimised the impact of dementia.
The researchers hope this study will help identify negative and misleading terms used about dementia. Specifically, they would like social media platforms to enable users to filter out tweets containing these terms. But the findings have broader implications because the use of negative terms was so widespread. The researchers would like their work to inform public awareness campaigns about dementia.
What’s the issue?
Social media platforms present a unique opportunity for sharing information. But they can also spread false information about conditions like dementia, accidentally or deliberately. Negative attitudes, language and misconceptions can have a profound impact on people affected by the condition. They can increase social exclusion, delays in diagnosis, shame, and guilt.
Twitter has an estimated 300 million active users, and most tweets are public. Previous research has found stigma about dementia on the platform.
This study was set up to identify themes, keywords and phrases that were commonly used about dementia. Researchers worked with carers of people with dementia to identify language they found acceptable, and unacceptable. They wanted to develop understanding of widespread misconceptions about dementia. This could inform future public awareness campaigns.
In order to search Twitter for tweets on dementia, the research team worked with 7 adult carers of people living with dementia. The researchers drew up a list of words and phrases about dementia from published research. Carers worked in focus groups to come up with another list. Together, the group then classed all terms on the combined list as either negative (senile, demented, for example) or neutral/positive (memory loss, dementia difficult behaviours).
The researchers collected data over 4 days in February 2020, which coincided with the US Presidential campaign. They used the combined list of search terms to capture almost 50,000 tweets that contained at least one of the search terms.
Of the total 50,000 tweets, 1 in 4 (26%) contained misconceptions or stigmatising words from the list of search terms.
Researchers and carers worked together to develop categories for tweets. Carers then categorised a subset of 1497 tweets and found:
- stigmatising or weaponising words, often ridiculing people by describing them as demented or senile, in 44% tweets
- incorrect words or statements, including armchair diagnoses (which diagnosed dementia, usually in a public figure), in 6%
- minimising or underestimating the seriousness of dementia or suggesting people with the condition have poor quality of life, in 1%.
Other tweets were neutral. For example, 21% were organisation or community group statements; 16% were individual comments on dementia and related topics; and 6% were lived experience.
Why is this important?
The researchers believe this is the first study to work with carers to develop a framework for identifying misconceptions about dementia on Twitter. Their results could help identify and target negative and factually incorrect tweets. They say this way of working with members of the public could be used to investigate public attitudes towards dementia on all social media platforms, and more widely in society.
Ableism (discrimination in favour of able-bodied people) is common in everyday speech and comes under less scrutiny than other forms of discrimination. These findings will be useful in planning public information to address negative views of dementia. More specifically, they could identify Twitter users who use negative terms. The researchers suggest targeting these users in an awareness campaign to reduce their misconceptions.
The approach taken in this study could be a template for researchers looking to build a similar framework for other conditions such as epilepsy. Many tweets using the word ‘seizure’, for example, have been shown to be negative.
The researchers acknowledge that only a small number of carers took part in this study, and most were White British. Even so, participants did not agree on all the terms they considered incorrect or stigmatising. Research including more diverse groups, including people living with dementia, is likely to add to the number of terms identified.
Data was collected during the 2020 US Presidential campaign. Some of the misconceptions about dementia might have been prompted by the campaign, and more common in this study than at other times.
The researchers are building a machine learning model based upon their findings. Their aim is for users to be able to filter dementia misconceptions on social media platforms without accidentally blocking useful information or interfering with others’ freedom of speech.
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This NIHR Alert is based on: Hudson G, and others. Investigation of Carers’ Perspectives of Dementia Misconceptions on Twitter: Focus Group Study. JMIR Aging 2022;5:1
Participants were recruited through the NIHR Maudsley Dementia service user and carer group (MALADY), and NIHR Join Dementia Research, a web-based platform hosted by the NIHR.
Research by the same team to identify schizophrenia stigma on Twitter. Jilka S, and others. Identifying schizophrenia stigma on Twitter: a proof of principle model using service user supervised machine learning. NPJ Schizophrenia 2022;8:1
A machine learning model that estimates people's happiness, based on their tweets: The Hedonometer project: Average Happiness for Twitter.
Funding: This work was funded by the NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, and Alzheimer’s Research UK’s Inspire Fund.
Conflicts of Interest: The study authors declare no conflicts of interest.
Disclaimer: NIHR Alerts are not a substitute for professional medical advice. They provide information about research which is funded or supported by the NIHR. Please note that views expressed in NIHR Alerts are those of the author(s) and reviewer(s) and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.