The #longcovid revolution: A reflexive thematic analysis.

Area of Science:

• Social Sciences
• Digital Health
• Medical Sociology

Background:

• Long COVID is recognized as the first virtual patient-made condition, originating from social media discourse.
• The condition affected millions in Europe within the first two years of the pandemic.
• Previous research has focused on later periods, leaving the initial emergence and discourse under-examined.

Purpose of the Study:

• To analyze the initial social construction of long COVID through Twitter data from May to August 2020.
• To understand how patient experiences shared online contributed to the recognition of long COVID.
• To explore the role of social media in forming a collective understanding and movement around long COVID.

Main Methods:

• Collection of over 31,000 tweets containing the #longcovid hashtag from May to August 2020.
• Application of Braun and Clarke's reflexive thematic analysis.
• Theoretical framing using Ian Hacking's social constructionism and incorporating the first author's lived experience.

Main Results:

• Identified long COVID as a multi-system, cyclical condition that was initially stigmatized and misunderstood.
• Demonstrated how Twitter users built social consensus on symptoms, countering the challenges faced by traditional evidence-based medicine.
• Revealed a collective social movement that fostered support, overcame stigma, and highlighted unmet healthcare needs (#researchrehabrecognition).

Conclusions:

• The #longcovid movement exhibited a revolutionary grade of social constructionism, leading to real-world recognition and potential healthcare changes.
• Patient-generated online content exposed limitations of traditional evidence-based medicine in identifying novel conditions.
• Future research on emerging conditions should consider diverse paradigms, including 'Evidence-Based Medicine Plus'.