Meta Analysis with continues outcome - appropriate effect calculation

I am conducting a meta analysis with studies on psychological treatments with continues outcome variables. The included studies use two different scales (either 0-20 or 0-100) for each study i have the following data:

Pre treatment: Treatment group: N, mean outcome, SD outcome Control group: N, mean outcome, SD outcome

Post treatment: TG: N,mean outcome, SD outcome CG: N,mean outcome, SD outcome

From literature i learned, that in this case i could use the difference of difference as effect size i.e.:

(mean_post_tg-mean_pre_tg)-(mean_post_cg-mean_pre_cg)

Now i am trying to conduct the meta analysis with RevMan, i choose Random Effect model on continues data. It asks me for mean,sd and N for TG and CG, what exact values do i need to provide? Only the post_treatment values?

Further: What if studies use different control groups, e.g. waiting list vs. treatment as usual?

If you want to use this outcome/effect size measure, you also need to know the pre-post correlation of the outcome scores within groups. The standard deviation/error of $\bar{x}_{post} - \bar{x}_{pre}$ within a group is a function of the group size $n$, the standard deviations $\mbox{SD}_{pre}$ and $\mbox{SD}_{post}$, and the pre-post correlation $r_{pre, post}$. To be precise: $$\mbox{SD}(\bar{x}_{post} - \bar{x}_{pre}) = \sqrt{\frac{\mbox{SD}_{pre}^2 + \mbox{SD}_{post}^2 - 2 r_{pre, post}\mbox{SD}_{pre}\mbox{SD}_{post}}{n}}.$$ Note that the numerator is the SD of the change scores, so if that is reported, you have what you need. In fact, what you plug into RevMan are the mean change (i.e., $\bar{x}_{post} - \bar{x}_{pre}$), the SD of the change scores, and the group size (for each group).