Hard to imagine how to design such study: (close to) 100% of people that adopt kid WANTED to have kid, and planned for them. Some XX% number of people having kid via pregnancy wasn't planning for them, and some even smaller YY% number doesn't want the kid at all.

Not to mention that unless the adoption of kids are done blind by parents, there has to be some biases there. As an example out of my ass, kids with behavioral problems might have way less adoption rate, and potentially those are the one with below median outcome in any case.

Compare adoptions of infants (handles the behavior issue) with parents who took blatant processes to improve pregnancy odds (IVF, etc).

That gets you two categories of people do definitely want kids, and only one is subject to the classes, interviews, and checkups.

There's certain to be natal/genetic/etc differences in the kids, though. (Are infants put up for adoption more likely to have been to mothers who are in poverty? Who smoke, drink or use drugs? Who are younger or older? Does IVF itself have positive or negative effects? Etc)

Really the ideal test would be, in order of preference:

1. randomization (some parents get the classes, some do not, chosen randomly)

2. geographic (parents in state/area A get classes, rest do not)

3. temporal (parents after year X get classes)

4. twins (parents of twin A get classes, twin B do not)

Obvious way to remove that bias would be to start by recruiting couples who are not parents but want to become parents and then follow them through their lives and their childrens lives. Within that cohort you would have a large number who would conceive naturally, some would go for IVF etc, some would adopt and some would not end up having children.