The COVID-19 pandemic caused different types of harms and benefits, but the combined patterns of perceived harms and benefits are unclear. We aimed to identify the patterns of perceived harms and benefits of the COVID-19 outbreak and to examine their associations with socio-demographic characteristics, happiness, and changes in smoking and drinking. A population-based cross-sectional online survey was conducted in May 2020 on Hong Kong adults (N = 4520). Patterns of perceived harms and benefits of COVID-19 were identified using latent profile analysis. Their associations with socio-demographic characteristics, happiness, and changes in smoking and drinking were examined using multinomial logistic regression. We identified three distinct patterns: indifferent (66.37%), harm (13.28%), and benefit (20.35%). Compared with the indifferent subgroup, the harm subgroup was younger, less happy, and had increased drinking, and hence might be at higher risk, whereas the benefit subgroup was more likely to be female, live with one or more cohabitants, have postsecondary education, be happier, and have decreased drinking, and could be more adaptive. Future studies can target the harm subgroup to facilitate their positive adjustments.
Keywords: COVID-19; latent profile analysis; meaning making; perceived benefit; perceived harm.