Characterization of non-adopters of COVID-19 non-pharmaceutical interventions through a national cross-sectional survey to assess attitudes and behaviours

Abstract

Adoption of non-pharmaceutical interventions (NPIs) remains critical to curtail the spread of COVID-19. Using self-reported adherence to NPIs in Canada, assessed through a national cross-sectional survey of 4498 respondents, we aimed to identify and characterize non-adopters of NPIs, evaluating their attitudes and behaviours to understand barriers and facilitators of adoption. A cluster analysis was used to group adopters separately from non-adopters of NPIs. Associations with sociodemographic factors, attitudes towards COVID-19 and the public health response were assessed using logistic regression models comparing non-adopters to adopters. Of the 4498 respondents, 994 (22%) were clustered as non-adopters. Sociodemographic factors significantly associated with the non-adoption cluster were: (1) being male, (2) age 18–34 years, (3) Albertans, (4) lower education level and (5) higher conservative political leaning. Participants who expressed low concern for COVID-19 and distrust towards several institutions had greater odds of being non-adopters. This information characterizes individuals at greatest odds for non-adoption of NPIs to inform targeted marketing interventions.

Predictors for adherent behavior in the COVID-19 pandemic: A cross-sectional telephone survey

“…This means the more dangerous the virus is considered to be, the more willing a person is to take protective action. These findings confirm further crosssectional studies such as Lang et al (37) showing that people who were unconcerned that an infection with the virus might lead to severe symptoms had higher odds of being non-adopters of non-pharmaceutical preventive interventions. Furthermore, in a sample of over 6,600 persons in the US, Bruine de Bruin and Bennett also found people that considered high risk to be associated with an infection with the coronavirus to be more likely to adopt protective behaviors (44).…”

“…The survey revealed that higher age and female gender were independent predictors of adherent behavior. Even though previously published studies were inconclusive, a large percentage of studies support our results (23,24,(37)(38)(39). For example, one Canadian study of over 2,000 persons between 18 and 100 years old showed that age and male gender were associated with lower adherence to different COVID-19 protective measures such as working remotely from home, social distancing, and maintaining a physical distance of 2 m from others (23).…”

“…Nevertheless, we have assumed that while the amount of corona fatigue may change over time, its impact in terms of β or OR will be comparable over time. This is supported by Lang et al ( 37 ) who clustered data from almost 4,500 persons from a Canadian cross-sectional survey and found similar rates among adopters and non-adopters of COVID-19 measures. He effectively confirmed our results as non-adopters tend to be younger males that are less worried about COVID-19.…”

“…For example, one Canadian study of over 2,000 persons between 18 and 100 years old showed that age and male gender were associated with lower adherence to different COVID-19 protective measures such as working remotely from home, social distancing, and maintaining a physical distance of 2 m from others ( 23 ). Another study that used cluster analysis to compare adopters and non-adopters of COVID-19 measures in 5,893 persons between 18 and 94 years old confirmed that older and female persons had lower odds of being in the non-adapter cluster ( 37 ). No influence of age or gender was found in a survey of elderly persons (aged over 60 years), which may reflect homogeneity across these variables within the study group ( 22 ).…”

A comparative study of eight COVID-19 protective measures and their impact on Swiss tourists’ travel intentions

“…In the fields of public health and social psychology, many studies reflect on attitudes towards and the adoption of specific NPIs (e.g., Kantor & Kantor, 2020 ; Lang et al, 2021 ; Shen et al, 2021 ; Xu et al, 2020 ), as well as on pharmaceutical interventions (PIs) like vaccines (e.g., Cascini et al, 2021 ; Seddig et al, 2022 ; Soveri et al, 2021 ). Among the few who have investigated NPIs in a tourism context, Lee et al (2012) , for example, showed that they had a positive effect on tourists’ intentions to travel internationally during the 2009 H1N1 influenza pandemic.…”