So what you're saying is we should never fully trust these journals? We should always be skeptical?
That's what I'm saying too...
YES, you should be skeptical, but mostly not at the journal-level. You need to be skeptical at the article-level. That is why it's so important to be actually TRAINED to interpret the studies.
The abstract of a trial is like an "advertisement" for the study. You quickly scan it to see if the study is worth reading. If it is, you make multiple passes of the article, identifying biases, understanding the study context, calculating ratios and numbers, reading through the lens of your own practice, and a bunch of other things.
So yes, I'd argue that brand names are a big problem. You just have to see how proud people are when they are accepted in one of the major publication venues, and the prestige that results.
I think you are not being objective.
"No, the real scandal is that the respected medical journal Lancet aids and abets in poor research practices by serving as a kind of shield for the authors of a questionable paper, by acting as if secret pre-publication review has more validity than open post-publication review." [1]
[1] https://statmodeling.stat.columbia.edu/2020/06/01/this-ones-...
HN isn’t the ideal venue for hyperbole.
One should always be skeptical of research and have dicsussions on the reported data and to what extent and in what context it makes sense. The media outlets summarizing the research papers very often fail to do that so as to skip the details and keep the readers happy because they assume "readers just want to know the superficial abstract knowledge, they can't possibly be interested in the critical analysis of the figures and the numbers so let's exclude that".
I think that exactly how good scientists proceed. This isn't my field, but my understanding is that research groups don't "fully trust" peer reviewed research, so they usually attempt to replicate the key results they plan to cite in their new research.
In fact, scientists often say, somewhat tongue-in-cheek, "It's published in Nature, so it's probably wrong" (the more revolutionary a result, the more likely it is to be wrong, but also the more likely it is to get into one of the top journals).