Middlebury College, Psychology Department, McCardell Bicentennial Hall, Middlebury, VT 05753, United States of America; University of Vermont, Department of Psychological Sciences, Vermont Psychological Services, Burlington, VT, United States of America.
Massachusetts General Hospital, Department of Psychiatry, Boston, MA, United States of America; Harvard Medical School, Department of Psychiatry, Boston, MA, United States of America.
J Psychosom Res. 2021 Jan;140:110299. doi: 10.1016/j.jpsychores.2020.110299. Epub 2020 Nov 15.
To identify the factors associated with perceived COVID-19 risk among people living in the US.
A cross-sectional representative sample of 485 US residents was collected in mid-April 2020. Participants were asked about (a) perceptions of COVID-19 risk, (b) demographic factors known to be associated with increased COVID-19 risk, and (c) the impact of COVID-19 on different life domains. We used a three-step hierarchical linear regression model to assess the differential contribution of the factors listed above on perceived COVID-19 risk.
The final model accounted for 16% of variability in perceived risk, F(18,458) = 4.8, p < .001. Participants who were White reported twice as much perceived risk as participants of color (B = -2.1, 95% CI[-3.4,-0.8]. Higher perceived risk was observed among those who reported a negative impact of the pandemic on their sleep (B = 1.5, 95% CI[0.8,2.1]) or work (B = 0.7, 95%CI[0.1,1.3]). The number of cases per capita in their state of residence, age, or proximity to someone with a COVID-19 diagnosis were not found to meaningfully predict perceived risk.
Perceived risk was not found to be associated with known demographic risk factors, except that the effect of race/ethnicity was in the opposite direction of existing evidence. Perception of COVID-19 risk was associated with the perceived personal impact of the pandemic.
确定与居住在美国的人对 COVID-19 风险的感知相关的因素。
在 2020 年 4 月中旬收集了美国 485 名居民的横断面代表性样本。参与者被问及(a)对 COVID-19 风险的看法,(b)已知与 COVID-19 风险增加相关的人口统计学因素,以及(c)COVID-19 对不同生活领域的影响。我们使用三步骤分层线性回归模型来评估上述因素对感知 COVID-19 风险的差异贡献。
最终模型解释了感知风险的 16%的变异性,F(18,458)=4.8,p<0.001。与有色人种相比,白人参与者报告的感知风险高两倍(B=-2.1,95%置信区间[-3.4,-0.8])。那些报告大流行对他们的睡眠(B=1.5,95%置信区间[0.8,2.1])或工作(B=0.7,95%置信区间[0.1,1.3])有负面影响的人,感知风险更高。他们居住州的病例数、年龄或与 COVID-19 诊断患者的接近程度,并没有被发现对感知风险有明显的预测作用。
感知风险与已知的人口统计学风险因素无关,除了种族/民族的影响与现有证据相反。对 COVID-19 风险的感知与大流行的个人感知影响有关。