The headline is broadly defensible, but the qualifications matter. Effect sizes vary by population, the strongest claims rest on shorter trials, and credible voices push back on how it's typically framed.
epidemiology are population surveys and so what we see and this is true there are many epidemiology studies which show that the more fruits and vegetables we eat the better our outcomes does that mean that fruits and vegetables cause those outcomes we can't say it's a possibility we can generate that hypothesis but there are many other alternative hypotheses
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Bookmarking — the dossier-vs-overview split is the right call. Most of the time I want overview; sometimes I want receipts.
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epidemiology is definitely you know a opportunity to use epidemiology as a tool to get different hypotheses you know drawn down and then again like you're saying make more interventional studies based on these on those hypotheses from you know epidemiology and that kind of stuff and I think it should be used as a tool and and people unfortunately use it as as proof for so many different things that they shouldn't
epidemiology correlation is not causation but we can use a strong correlation to generate a hypothesis which we will then test with Interventional studies
this is the problem with epidemiology studies they are correlation not causation and they must be interpreted we can generate hypotheses which must then be tested by interventions
this is observational research and the problem with this type of research i get questions about this all the time in my direct messages my dms on instagram et cetera is that it has so much potential to be confounded by two things called healthy user bias and unhealthy user bias
epidemiology which is uh essentially synonymous with observational research so this is the caveat that I will try to always make when I am discussing epidemiology AKA observational research that this is observational research and the problem with this type of research I get questions about this all the time in my direct messages my DMs on Instagram Etc is that it has so much potential to be confounded by two things called healthy user bias and unhealthy user bias
but we often say that observational studies of this nature cannot prove a cause and effect relationship but they can generate hypotheses to be tested in randomized clinical trials