While the importance of government transparency is extensively discussed in risk communication literature, its practical application in risk contexts presents intricate challenges. This study introduces a redefined concept of transparency in the context of risk, covering two dimensions: information disclosure and uncertainty reduction. To investigate the impact of transparency, ranging from mere information disclosure to significant uncertainty reduction, a hierarchical multiple regression model is employed. Specifically, trust in government serves as a benchmark for information disclosure, while indicators for information disclosure strategies and public vulnerability are incorporated into the model as proxies for uncertainty reduction. The proposed model undergoes validation in a city lockdown scenario in China using self-report data from 435 college students, with anxiety serving as a benchmark for transparency outcomes. The findings suggest that indicators of uncertainty reduction (information disclosure strategies, individual vulnerability) exert much larger effects on anxiety than mere information disclosure (indicated by government trust). This implies that government transparency should prioritize uncertainty reduction, involving diverse strategies and addressing public vulnerabilities.