JMIR Publications

ABSTRACT

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 co-developed a thematic framework with carers to understand the forms these misconceptions take on Twitter.

Objective:

To identify and analyse types of dementia conversations on Twitter using participatory methods.

Methods:

Three 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 API using neutral and negative keywords defined by the literature and carers (N48,211). A sample of these tweets was selected with equal numbers of neutral and negative words (N1497), which was validated in individual ratings by carers. We then used the framework to analyse in detail a sample of carer-rated negative tweets (N863).

Results:

Twenty-six percent (N12,507) of our tweet corpus (N48,211) contained negative keywords about dementia. The carers’ framework had three negative and three neutral categories. Our thematic analysis of carer-rated negative tweets found nine themes including weaponising language to ‘insult politicians’ (54%), using ‘dehumanising or outdated words or statements’ about members of the public (17%), unfounded claims about the ‘causes of dementia’ (1%), or providing ‘armchair diagnoses’ of dementia (2%).

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 stigmatising language are not rare. They manifest through minimising and underestimating language. Online campaigns aiming to reduce discrimination and stigma about dementia could target those who use negative vocabulary and reduce the misconceptions that are being propagated and thus improving general awareness.