"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.
> While many studies have found a correlation between the use of social media and various symptoms related to mental health, so far, it has been challenging to ascertain whether social media was actually the cause of poor mental health. By applying a novel research method, researchers have now succeeded in establishing such a causality
But doesn't elaborate on the new method. We'll have to wait for the study to be published I guess.
Some were surely acting in their own personal financial interests but I'm also certain that a lot of it was more nuanced and personal. People need to think of themselves as, for the most part, good people who do mostly good things. Knowingly contributing to something that makes life much worse for many people doesn't align with that and they will need to deny it. I know if you polled phillip morris employees about cancer in the late 60s after the link was confirmed you'd hear a lot about correlation and uncertainty.
HN isn't a random slice of the population. A lot of us here work in this domain or on similar products. There are certainly people in this comment section who directly worked on the core facebook product being discussed. They need to think of themselves as good still, too.
They looked at the mental health (as measured by self-reported surveys) among schools over time and cross-referenced that with the rollout of Facebook over time. So they could compare the change in mental health at schools the received Facebook access and compare it to the change in mental health at schools that did not receive Facebook access at the same time.
The methodology appears to be fairly novel and does isolate them from several reverse-causation biases, as it is difficult to imagine that the rollout of Facebook was influenced by factors that led to the decline of mental health in student bodies.
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".
These 2 are vastly different situations.
To give an example. Establishing causal effect between nicotine and lung cancer is an open question, even as the causal effect of smoking on cancer is very clear.
I assume to do that you have to establish the complete pathway and mechanism from someone using facebook to an increase in depression, like showing observations of changes in neurotransmitters or brain structure that have been proven to cause changes in mental health, and then proving that facebook caused the changes in those levels. (FWIW I assume this could be done and that we may see those kinds of results if it were done, but I haven't actually seen a study like that. I also assume the hypothesis in general.)
For instance, using the example of smoking from another commenter, from the CDC website [0]:
> - Poisons in cigarette smoke can weaken the body’s immune system, making it harder to kill cancer cells. When this happens, cancer cells keep growing without being stopped.
> - Poisons in tobacco smoke can damage or change a cell’s DNA. DNA is the cell’s “instruction manual” that controls a cell’s normal growth and function. When DNA is damaged, a cell can begin growing out of control and create a cancer tumor.
These seem more like things that can be tested in laboratory settings that are easily reproducible and rely on more objective observations than self-reporting.
I'm neither a neuroscientist or social scientist so I'm just trying to understand, not saying they're wrong or that the research is even flawed.
[0]: https://www.cdc.gov/tobacco/campaign/tips/diseases/cancer.ht...
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.
I agree it's not unreasonable, but you have to account for the fact that back then, most of the colleges that had it were top tier/high stress/highly selective colleges. Facebook started at Harvard, then went to Yale and Princeton, and then on to basically most of the US News top 50.