Experiences of self-care during the COVID-19 pandemic among individuals with rheumatoid arthritis: A qualitative study

Objectives: This study aimed to explore the impact of the coronavirus disease 2019 (COVID-19) pandemic on self-care of individuals living with rheumatoid arthritis (RA).

Methods: Guided by a constructivist, qualitative design, we conducted one-to-one in-depth telephone interviews between March and October 2020 with participants with RA purposively sampled for maximum variation in age, sex and education, who were participating in one of two ongoing randomized-controlled trials. An inductive, reflexive thematic analysis approach was used.

Results: Twenty-six participants (aged 27-73 years; 23 females) in British Columbia, Canada were interviewed. We identified three themes: (1) Adapting to maintain self-care describes how participants took measures to continue self-care activities while preventing virus transmissions. While spending more time at home, some participants reported improved self-care. (2) Managing emotions describes resilience-building strategies such as keeping perspective, positive reframing and avoiding negative thoughts. Participants described both letting go and maintaining a sense of control to accommodate difficulties and emotional responses. (3) Changing communication with health professionals outlined positive experiences of remote consultations with health professionals, particularly if good relationships had been established prepandemic.

Conclusion: The insights gained may inform clinicians and researchers on ways to support the self-care strategies of individuals with RA and other chronic illnesses during and after the COVID-19 pandemic. The findings reveal opportunities to further examine remote consultations to optimize patient engagement and care.

Patient or public contribution: This project is jointly designed and conducted with patient partners in British Columbia, Canada. Patient partners across the United Kingdom also played in a key role in providing interpretations of themes during data analysis.