Centre for Longitudinal Studies, Institute of Education, University College London, London, UK.
Department of Behavioural Science and Health, University College London, London, UK.
Ann Behav Med. 2022 Aug 2;56(8):781-790. doi: 10.1093/abm/kaac023.
Governments have implemented a range of measures focused on changing citizens' behaviors to lower the transmission of COVID-19. While international data shows that compliance did decline from the start of the pandemic, average trends could mask considerable heterogeneity in compliance behaviors.
To explore trajectories of compliance with COVID-19 guidelines.
We used longitudinal data on self-reported compliance from 50,851 adults in the COVID-19 Social Study collected across two waves of the pandemic in the UK (April 01, 2020-February 22, 2021). We modeled typical compliance trajectories using latent class growth analysis (LCGA) and used multinomial logistic regression to examine whether individual personality and demographic characteristics were related to compliance trajectories.
We selected a four-class LCGA solution. Most individuals maintained high levels of compliance and reported similar levels of compliance across the first and second waves. Approximately 15% of participants had decreasing levels of compliance across the pandemic, reporting noticeably lower levels of compliance in the second wave. Individuals with declining compliance levels were younger on average, in better physical health, had lower empathy and conscientiousness and greater general willingness to take risks.
While a minority, not all individuals have maintained high compliance across the pandemic. Decreasing compliance is related to several psychological traits. The results suggest that targeting of behavior change messages later in the pandemic may be needed to increase compliance.
政府已采取多项措施,旨在改变公民行为,以降低 COVID-19 的传播风险。尽管国际数据显示,从疫情开始以来,民众的遵守率确实有所下降,但平均趋势可能掩盖了遵守行为的相当大的异质性。
探索 COVID-19 指南遵守情况的轨迹。
我们使用了英国 COVID-19 社会研究中 50851 名成年人在两次大流行期间(2020 年 4 月 1 日至 2021 年 2 月 22 日)自我报告的合规性的纵向数据。我们使用潜在类别增长分析(LCGA)对典型的合规性轨迹进行建模,并使用多项逻辑回归来检验个体人格和人口统计学特征是否与合规性轨迹相关。
我们选择了一个四分类 LCGA 解决方案。大多数人保持高水平的合规性,并在第一波和第二波报告了相似的合规水平。大约 15%的参与者在整个大流行期间的合规水平下降,在第二波报告的合规水平明显较低。合规水平下降的个体平均年龄较小,身体健康状况较好,同理心和尽责性较低,普遍更愿意冒险。
虽然只有少数人,但并非所有人在整个大流行期间都保持了高度的合规性。合规性下降与几个心理特征有关。结果表明,在大流行后期可能需要针对行为改变信息进行目标定位,以提高合规性。