The #longcovid revolution: A reflexive thematic analysis

Abstract

Research has identified long COVID as the first virtual patient-made condition (Callard and Perego, 2021). It originated from Twitter users sharing their experiences using the hashtag #longcovid. Over the first two years of the pandemic, long COVID affected as many as 17 million people in Europe (WHO, 2023). This study focuses on the initial #longcovid tweets in 2020 (as previous studies have focused on 2021–2022), from the first tweet in May to August 2020, when the World Health Organization recognised the condition.We collected over 31,000 tweets containing #longcovid from Twitter. Using Braun and Clarke's reflexive thematic analysis (2020), informed by the first author's experience of long COVID and drawing on Ian Hacking's perspective on social constructionism (1999), we identified different grades of social constructionism in the tweets. The themes we generated reflected that long COVID was a multi-system, cyclical condition initially stigmatised and misunderstood. These findings align with existing literature (Ladds et al., 2020; Rushforth et al., 2021).We add to the existing literature by suggesting that Twitter users raised awareness of long COVID by providing social consensus on their long COVID symptoms. Despite the challenge for traditional evidence-based medicine to capture the varied and intermittent symptoms, the social consensus highlighted that these variations were a consistent and collective experience. This social consensus fostered a collective social movement, overcoming stigma through supportive tweets and highlighting their healthcare needs using #researchrehabrecognition. The #longcovid movement's work was revolutionary, as it showed a revolutionary grade of social constructionism, because it brought about real-world change for long COVID sufferers in terms of recognition and the potential for healthcare provisions.Twitter users' accounts expose the limitations of traditional evidence-based medicine in identifying new conditions. Future research on novel conditions should consider various research paradigms, such as Evidence-Based Medicine Plus (Greenhalgh et al., 2022).