%0 Journal Article
%@ 2561-7605
%I JMIR Publications
%V 5
%N 1
%P e30388
%T Investigation of Carers’ Perspectives of Dementia Misconceptions on Twitter: Focus Group Study
%A Hudson,Georgie
%A Jansli,Sonja M
%A Erturk,Sinan
%A Morris,Daniel
%A Odoi,Clarissa M
%A Clayton-Turner,Angela
%A Bray,Vanessa
%A Yourston,Gill
%A Clouden,Doreen
%A Proudfoot,David
%A Cornwall,Andrew
%A Waldron,Claire
%A Wykes,Til
%A Jilka,Sagar
%+ Institute of Psychiatry, Psychology, and Neuroscience, King's College London, 2.13 Henry Wellcome Building, 16 De Crespigny Park, London, SE5 8AF, United Kingdom, 44 7708715627, sagar.jilka@kcl.ac.uk
%K patient and public involvement
%K dementia
%K co-production
%K misconceptions
%K stigma
%K Twitter
%K social media
%K Alzheimer’s Disease
%D 2022
%7 24.1.2022
%9 Original Paper
%J JMIR Aging
%G English
%X Background: Dementia 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. Objective: The aim of this study is to identify and analyze types of dementia conversations on Twitter using participatory methods. Methods: A 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). Results: A 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found 9 themes, including the use of weaponizing language to insult politicians (469/863, 54.3%), using dehumanizing or outdated words or statements about members of the public (n=143, 16.6%), unfounded claims about the cures or causes of dementia (n=11, 1.3%), or providing armchair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%). Conclusions: This 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. 
%M 35072637
%R 10.2196/30388
%U https://aging.jmir.org/2022/1/e30388
%U https://doi.org/10.2196/30388
%U http://www.ncbi.nlm.nih.gov/pubmed/35072637