ABSTRACT
INTRODUCTION: This study combines quantitative and qualitative analyses of social media data collected through three key stages of the pandemic, to highlight the following: 'First wave' (March to May, 2020): negative consequences arising from a disconnect between official health communications, and unofficial Long Covid sufferers' narratives online.'Second wave' (October 2020 to January 2021): closing the 'gap' between official health communications and unofficial patient narratives, leading to a better integration between patient voice, research and services.'Vaccination phase' (January 2021, early stages of the vaccination programme in the UK): continuing and new emerging concerns. METHODS: We adopted a mixed methods approach involving quantitative and qualitative analyses of 1.38 million posts mentioning long-term symptoms of Covid-19, gathered across social media and news platforms between 1 January 2020 and 1 January 2021, on Twitter, Facebook, Blogs, and Forums. Our inductive thematic analysis was informed by our discourse analysis of words, and sentiment analysis of hashtags and emojis. RESULTS: Results indicate that the negative impacts arise mostly from conflicting definitions of Covid-19 and fears around the Covid-19 vaccine for Long Covid sufferers. Key areas of concern are: time/duration; symptoms/testing; emotional impact; lack of support and resources. CONCLUSIONS: Whilst Covid-19 is a global issue, specific sociocultural, political and economic contexts mean patients experience Long Covid at a localised level, needing appropriate localised responses. This can only happen if we build a knowledge base that begins with the patient, ultimately informing treatment and rehabilitation strategies for Long Covid.
ABSTRACT
Presented as providing cost-, time- and labour- effective tools for the (self)management of health, health apps are often celebrated as beneficial to all. However, their negative effects - commodification of user data and infringement on privacy - are rarely addressed. This article focuses on one particularly troubling aspect: the difficulty of opting out of data sharing and aggregation during app use or after unsubscribing/uninstalling the app. Working in the context of the new European General Data Protection Regulation and its implementation in the UK health services, our analysis reveals the discrepancy between the information presented to users, and the apps' actual handling of user data. We also point to the fundamental tension in the digitisation of health, between the neoliberal model where both health and data concerns are viewed as an individual's responsibility, and the digital-capitalist model, which puts forward, and capitalises on, collective ('Big') data. Pulled between the 'biopolitics of the self' and the 'biopolitics of the population' (concepts coined by Btihaj Ajana), opting out of health datafication therefore cannot be resolved as a matter of individual right alone. The article offers two contributions. Methodologically, we present a toolkit for a multi-level assessment of apps from the perspective of opting out, which can be adapted and used in future research. Conceptually, the article brings together critical digital health scholarship with the perspective of data justice, offering a new approach to health apps, which focuses on opt-out as a legal, social and technical possibility, and as a collective citizen and user right.