A separate problem, not dealt with in that particular essay, is the quite hideous degree to which average scientists don't understand the statistics they use.
I would put a good deal of the blame for this squarely on frequentism as well. Bayesianism isn't hard to understand, it's just takes an effort of the teacher to explain well - I've made certain notable efforts in that direction myself. Once you do get it, you get it.
I think, roughly, the blame goes out to Fisher and anyone else who promoted the "Recipe for Understanding the World" style statistics. It's not that people are being blocked by their understanding of complex frequentist methods but instead the idea that they don't need to understand anything more because statistics is just a black box you use for verification.
Insert results, get a green or red "significance" light, move on.
I would put a good deal of the blame for this squarely on frequentism as well. Bayesianism isn't hard to understand, it's just takes an effort of the teacher to explain well - I've made certain notable efforts in that direction myself. Once you do get it, you get it.