Abstract
Citizens’ trust in government is crucial in managing crises that require coordination as it is linked to cooperative behaviour and sociability. Willingness to adopt appropriate health measures plays a decisive role in the effective containment of COVID-19 and other pandemics. Preventive health measures such as physical distancing, avoiding crowded places, wearing masks, and frequent hand washing reduce the spread of the virus. In this study, we examined how trust in government, risk perception, and knowledge were separately and jointly related to compliance with preventive health measures. We focused on young adults who are less prone to the disease than older demographics, who therefore have fewer incentives to protect themselves, and are accordingly pertinent for the study of public health and understandings of risk. Using recent data from a survey completed by 2,455 young people in Luxembourg, we employed structural equation modelling to assess our hypotheses. We found that trust in government, risk perceptions, and COVID-19 knowledge are important predictors of young people’s adherence to health measures and prosocial protection. Additionally, these factors are interrelated in several complex and non-linear ways. Our findings provide insights into young people’s specific health behaviours, highlighting the roles of risk perception and trust in government in mitigating the spread of COVID-19 and other infectious diseases.
Acknowledgments
We would like to thank Patrick Brown, Daniele Nosenzo, Wouter Poortinga, Caroline Residori, and the anonymous reviewers for their invaluable and insightful comments.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1. A detailed review of Luxembourg’s response to the COVID-19 crisis in terms of risk preparation, crisis management, public health, education, and economic, social and labour market policies is provided by the OECD (Citation2022).
2. To estimate the confidence intervals of the direct and indirect effects, we obtained the standard errors by non-parametric bootstrapping as indirect effect point estimates often follow a non-normal distribution and, therefore, are not easily derived analytically (Pesigan & Cheung, Citation2020).