Of course, but what you're requesting is science. It's a meta-analysis. A work that studies other studies and tries to provide aggregate data while controlling

Of course, but what you're requesting is science. It's a meta-analysis. A work that studies other studies and tries to provide aggregate data while controlling for whatever the meta-analysis creators determine to be relevant. What I was pointing out here is how studies like this would generally be considered high-reliability studies for these meta-analyses. It ticks all the right boxes, probably by design. Yet at the same time when you look at it, it's something I think few would find worthy of basing their decisions on. But qualifying exactly which studies you should, or should not, give weight to is a task that's ultimately going to also involve substantial bias. If I want to argue that digitech is good for kids, I'm going to be able to create very reasonable sounding criteria that would include studies such as this. If I want to argue that digitech is bad for kids, I'm still going to be able to create very reasonable sounding criteria yet one that would exclude studies such as this. The same problem inherent in the individual studies also ends up emerging in the meta-analyses as well. Aggregating data in some ways takes you even further away from the truth. Here you can reasonably show that this study is not so great, yet imagine this was part of hundreds of different studies all packed together with a sample size aggregate of hundreds of thousands. It may very well be that that meta-analysis was also loaded with dubious work, such as this, yet it becomes vastly more tedious to illustrate such. And as the rate of publication continues to exponentially increase, then going forward into the future we will eventually be faced with things such as meta-analyses of meta-analyses. Meta-meta-analysis I suppose?