I think the problem is just the methods like SCMs are extremely complicated for a lot of researchers in applied fields where they want these causal inferences. These fields would rather do a simple model and try to reason out causality in non-statistical ways.

I had an MD I work with tell me once (I do biomarker stuff) that “confounding is very overrated, this is all discovery and everything would have to be verified scientifically later anyways, and in the right clinical context even a marker with confounding can still be useful”. Essentially “clinical context” implies domain expertise (which actually is “adjusting” for the other factors anyways just in a human way)