Unimodality is one of the building structures of distributions that like skewness, kurtosis and symmetry is visible in the shape of a function. Comparing two different distributions, can be a very difficult task. But if both the distributions are of the same types, for example both are unimodal, for comparison we may just compare the modes, dispersions and skewness. So, the concept of unimodality of distributions and its characterizations, is important. In this paper, we discuss the concept of unimodality and its generalizations, namely a-unimodality, for discrete and continuous random variables. We shall also review the concept of a-monotonicity of distributions. Finally, we shall reveal certain upper bounds for the variance of a discrete a-unimodal distribution.