ArticleJMIR aging2022
Investigation of Carers' Perspectives of Dementia Misconceptions on Twitter: Focus Group Study.
Article in JMIR aging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- Understanding the public knowledge and awareness of parkinson's disease in Ireland: a cross-sectional survey.BMC public health · 2025Article
- Designing Inclusive Qualitative Research with Carers of People Living with Dementia: Methodological Insights.Healthcare (Basel, Switzerland) · 2023Article
- Psychosocial Basis of Human Sufferings and Poverty in Patients with Neurological and Psychiatric Disorders.Medical research archives · 2023Article
- Article
- Comparing Professional and Consumer Ratings of Mental Health Apps: Mixed Methods Study.JMIR formative research · 2022Article
- Investigating mental health service user views of stigma on Twitter during COVID-19: a mixed-methods study.Journal of mental health (Abingdon, England) · 2022Article
- Codeveloping and Evaluating a Campaign to Reduce Dementia Misconceptions on Twitter: Machine Learning Study.JMIR infodemiologyArticle
Corrections and comments
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Authors and funding
14 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDementia misconceptions on social media are common, with negative effects on people with the condition, their carers, and those who know them. This study codeveloped a thematic framework with carers to understand the forms these misconceptions take on Twitter.
objectiveThe aim of this study is to identify and analyze types of dementia conversations on Twitter using participatory methods.
methodsA total of 3 focus groups with dementia carers were held to develop a framework of dementia misconceptions based on their experiences. Dementia-related tweets were collected from Twitter's official application programming interface using neutral and negative search terms defined by the literature and by carers (N=48,211). A sample of these tweets was selected with equal numbers of neutral and negative words (n=1497), which was validated in individual ratings by carers. We then used the framework to analyze, in detail, a sample of carer-rated negative tweets (n=863).
resultsA total of 25.94% (12,507/48,211) of our tweet corpus contained negative search terms about dementia. The carers' framework had 3 negative and 3 neutral categories. Our thematic analysis of carer-rated negative tweets found 9 themes, including the use of weaponizing language to insult politicians (469/863, 54.3%), using dehumanizing or outdated words or statements about members of the public (n=143, 16.6%), unfounded claims about the cures or causes of dementia (n=11, 1.3%), or providing armchair diagnoses of dementia (n=21, 2.4%).
conclusionsThis is the first study to use participatory methods to develop a framework that identifies dementia misconceptions on Twitter. We show that misconceptions and stigmatizing language are not rare. They manifest through minimizing and underestimating language. Web-based campaigns aiming to reduce discrimination and stigma about dementia could target those who use negative vocabulary and reduce the misconceptions that are being propagated, thus improving general awareness.
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