A novel approach based on the concepts of a generalized pivotal quantity (GPQ) is developed to construct confidence intervals for the mediated effect. Thereafter, its performance is compared with six interval estimation approaches in terms of empirical coverage probability and expected length via simulation and two real examples. The results show that the GPQ-based and bootstrap percentile methods outperform other methods when mediated effects exist in small and medium samples. Moreover, the GPQ-based method exhibits a more stable performance in small and non-normal samples. A discussion on how to choose the best interval estimation method for mediated effects is presented.