Characterising subgroups of people with severe COVID anxiety by latent profile analysis

Background: People with severe COVID anxiety have had experiences of the COVID-19 pandemic which are overwhelming, and have led to patterns of behaviours that add little protective benefit but are at the expense of other priorities in life. It appears to be a complex social and psychological phenomenon, influenced by demographic and social factors. Identifying subgroups of people with severe COVID anxiety would better place clinicians to assess and support this distress where indicated. Methods: Measurement tools assessing depression, generalised and health anxiety, obsessive-compulsive symptoms, personality difficulty and alcohol use from 284 people living in United Kingdom with severe COVID anxiety were explored with latent profile analysis. Further analyses examined the associations of identified clusters with demographic and social factors and daily functioning, quality of life and protective behaviours. Results: A model with 4 classes provided the best fit. Distinct patterns of psychopathology emerged which were variably associated with demographic factors and COVID behaviours. Limitations: Given the complex aetiology of COVID anxiety a number of factors which might better cluster subgroups are likely to have gone uncollected. Moreover, using data collected at a single time-point limits these results' ability to conclude whether observed relationships were the product of the pandemic or longstanding. Conclusions: People living with severe COVID anxiety are a heterogenous group. This analysis adds to evidence that certain health behaviours and demographic factors are inextricably linked to poor mental health in people with COVID anxiety, and that targeting health behaviours with specific intervention might be beneficial.