Trust in science and scientists among university students, staff, and faculty of a large, diverse university in Los Angeles during the COVID-19 pandemic, the Trojan Pandemic Response Initiative

Abstract

Abstract Background Mistrust in science and scientists may adversely influence the rate of COVID-19 vaccination and undermine public health initiatives to reduce virus transmission. Methods Students, staff and faculty responded to an email invitation to complete an electronic survey. Surveys included 21-items from the Trust in Science and Scientists Inventory questionnaire. Responses were coded so higher scores indicated a higher trust in science and scientists, A linear regression model including sex, age group, division, race and ethnicity, political affiliation, and history of COVID-19, was used to determine variables significantly associated with trust in science and scientists scores at the p < 0.05 level. Results Participants were mostly female (62.1%), Asian (34.7%) and White (39.5%) and students (70.6%). More than half identified their political affiliation as Democrat (65%). In the final regression model, all races and ethnicities had significantly lower mean trust in science and scientists scores than White participants [Black ($$B$$= -0.42, 95% CI: -0.55, -0.43, p < 0.001); Asian ($$B$$= -0.20, 95% CI: -0.24, -0.17, p < 0.001); Latinx ($$B$$= -0.22, 95% CI: -0.27, -0.18, p < 0.001); Other ($$B$$= -0.19, 95% CI: -0.26, -0.11, p < 0.001)]. Compared to those identifying as Democrat, all other political affiliations had significantly lower mean scores. [Republican ($$B$$ =-0.49, 95% CI: -0.55, -0.43, p < 0.0001); Independent ($$B$$ =-0.29, 95% CI: -0.33, -0.25, p < 0.0001); something else ($$B$$ =-0.19, 95% CI: -0.25, -0.12, p < 0.0001)]. Having had COVID-19 ($$B$$= -0.10, 95% CI: -0.15, -0.06, p < 0.001) had significantly lower scores compared to those who did not have COVID-19. Conclusion Despite the setting of a major research University, trust in science is highly variable. This study identifies characteristics that could be used to target and curate educational campaigns and university policies to address the COVID19 and future pandemics.