A dynamical system is said to have bounded sensitivity if an additive disturbance leads to a change in the state trajectory that is bounded by a constant multiple of the size of the cumulative disturbance.It was shown in [1] that the (negative) (sub)gradient field of a piecewise constant and convex function with finitely many pieces has always bounded sensitivity. In this paper, we investigate sensitivity of some generalizations of this class of systems, as well as other classes of practical interest. In particular, we show that the result in [1] does not generalize to the (negative) gradient field of a convex function.More concretely, we provide examples of gradient field of a twice continuously differentiable convex function, and subgradient field of a piecewise constant convex function with infinitely many pieces, that have unbounded sensitivity. Moreover, we give a necessary and sufficient condition for a linear dynamical system to have bounded sensitivity, in terms of the spectrum of the underlying matrix.The proofs and the development of our examples involve some intermediate results concerning transformations of dynamical systems, which are also of independent interest. More specifically, we study some transformations that when applied on a dynamical system with bounded sensitivity, preserve the bounded sensitivity property. These transformations include discretization of time and spreading of a system; a transformation that captures approximate solutions of the original system in a certain sense.