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通过全国性横断面调查评估态度和行为,描述 COVID-19 非药物干预措施不采纳者的特征。

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

机构信息

Department of Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.

Department of Economics, Faculty of Arts, University of Calgary, Calgary, AB, Canada.

出版信息

Sci Rep. 2021 Nov 5;11(1):21751. doi: 10.1038/s41598-021-01279-2.

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.

摘要

采用非药物干预措施(NPIs)对于遏制 COVID-19 的传播仍然至关重要。本研究利用加拿大一项全国性横断面调查的 4498 名受访者对 NPI 的自我报告依从性,旨在确定和描述 NPI 的不依从者,评估他们的态度和行为,以了解采用 NPI 的障碍和促进因素。使用聚类分析将 NPI 的依从者和不依从者分开。使用逻辑回归模型比较不依从者和依从者,评估与社会人口因素、对 COVID-19 的态度和公共卫生应对相关的关联。在 4498 名受访者中,有 994 名(22%)被聚类为不依从者。与不依从者聚类显著相关的社会人口因素包括:(1)男性,(2)年龄 18-34 岁,(3)艾伯塔省人,(4)教育水平较低,(5)政治立场偏保守。对 COVID-19 关注度低和对多个机构不信任的参与者更有可能不依从 NPI。这些信息描述了最不可能采用 NPI 的个体特征,以便为有针对性的营销干预提供信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49e5/8571421/3ee44b210e0a/41598_2021_1279_Fig1_HTML.jpg

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