Pre- and post- COVID-19 trends related to dementia caregiving on Twitter

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Abstract

With the advent of new media, more people are turning to social media to share thoughts and emotions related to personal life experiences. We examined salient concerns of dementia caregivers on Twitter pre- and post-pandemic, aiming to shed light on how to better support and engage dementia caregivers post-COVID-19 pandemic. English tweets related to “dementia” and “caregiver” were extracted between 1st January 2013 and 31st December 2022. A supervised deep learning model (Bidirectional Encoder Representations from Transformers, BERT) was trained to select tweets describing individual’s experience related to dementia caregiving. An unsupervised deep learning approach (BERT-based topic modelling) was applied to identify topics from selected tweets, with each topic further grouped into themes manually using thematic analysis. A total of 44,527 tweets were analysed, and stratified using the emergence of COVID-19 pandemic as a threshold. Three themes were derived: challenges of caregiving in dementia, strategies to inspire caregivers, and dementia-related stigmatization. Over time, there is a rising trend of tweets relating to dementia caregiving. Post-pandemic, challenges of caregiving remained the top discussed topic; with a notable increase in tweets related to dementia-related stigmatization (p < 0.001), especially in North America and other continents (and less so in Europe). The findings uncover a worrying trend of growing dementia-related stigmatization among the caregivers, manifested by caregivers internalizing publicly-held stigma and projecting negative stereotypes externally as a means to devalue others. The challenges faced by caregivers also remained a significant concern, highlighting the need for continued support and resources for caregivers even post-pandemic.

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APA

Ang, L. C., Malhotra, R., Roy Chowdhury, A., & Liew, T. M. (2025). Pre- and post- COVID-19 trends related to dementia caregiving on Twitter. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-024-82405-8

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