First, if the conclusions are counterintuitive or unexpected, then when you look closer, you will find that the methodology is garbage and that it does not support the conclusions given.
Second, if the conclusions reflect things that you believe are true, when you look closer, you will find that the methodology is garbage and that it does not support the conclusions given.
If you have specific criticism regarding the methodology of this study - which doesn't, prima facie, appear unsound - please let the rest of us participate.
"The have used a correlational model, not a causal model. There are several confounding variables the paper doesn't consider, hence it is not proven from the evidence that Facebook has a negative impact "
The article discusses how the study looked at different universities during the same time period, some of which had access to facebook and some of which didn't, and discovered that in the first case there was an increase in mental health issues over that period. There could still be confounders, sure, (or the sample size could be too small etc.), but at a first glance, that's not an unreasonable approach, as it tries to isolate the variable "facebook yes/no".
That said, if you haven't read the article, I'm not sure why you even felt the need to comment? This is exactly the same kind of shallow dismissal I was calling out.
Going back to your specific comments. Clearly the universities were not randomly assigned the treatment and control. And the actual number of independent sample sizes is extremely unlikely to give stat sig results at the single percentage digit impact shown. And no matter what they do, for something as complex as mental health, listing out all the confounding factors is hopeless - unlike lung cancer where you are literally sucking tar into your lungs and the sample sizes and effects are huge. Its a useful observational study, but it is ridiculous to call it a proof.
> We know that smoking is linked to cancer through decades of correlational studies and careful analysis of confounding factors, for example.
Yes, it took decades, when there is no proper control set. There are work arounds like backdoor and front door criteria, but yeah - it will take decades of work and looking inside the "black box".
Proofs are for mathematics, not for science. (I share your distaste for science journalism that throws big words like "prove" around without much care, but that's probably not something you can fault the study authors for.)
This is evidence in favour of a theory. It is to be understood within a larger body of evidence. Eventually, hopefully, there is enough evidence in one direction or another that we may draw more or less definitive conclusions.
> I made it a point to not read it, because virtually all social science papers are like these. It's really not worth my time
Nobody is forcing you to read this study, but somehow you seem to assume that your shallow dismissals (to which you are of course entitled privately) are worth anyone's time.