One of the slides/tabulation in your study should be explicitly identifying the % missing for all the variables that are used in the study.
Explain why missing values for each of the study variables occur.
Sometimes, missing values are confused with naturally occurring non-availablity (existence) of values due to the construction/definition of variable. This should be differentiated in the explanation of the % missing in the study variables. For example, in surveys that use hierarchical rule based questions, there will be missing situations that would occur because of the structure of the questions.
Use multiple imputation methods for application situations for best results.
Both “Delete Strategy” and “Mean Strategy” could be very biased methods, more so with the first one, than the later, depending on how much data is missing.