For linear system models, the approximate massage passing (AMP) is one of the effective iterative sparse recovery algorithms. However, depending on a measurement matrix ensemble, AMP may face convergence issues. Some algorithms are proposed so far to avoid the convergence issues, e.g., the orthogonal AMP (OAMP) and the mean removal. One of the simplest ways to avoid the convergence issues is to introduce a damping effect into AMP. In this paper, we derive a simple recursive equations that characterizes the damped OAMP, which is an OAMP in which the damping effect is introduced, and show that the result can be applied to the damped version of the original AMP.