Why scientific publications are contradictory. Interesting article.
samko1976
Posts: 125 Member
http://io9.com/i-fooled-millions-into-thinking-chocolate-helps-weight-1707251800
This has come up in my facebook feed today.
It explains how pants the papers published on weight loss can be and why contradictory results are published in the media and in journals.
No wonder people are confused and battle each other because every diet is right and every diet is wrong.
I personally feel that most diets work its just what works for the individual, generally speaking, as long as you get fresh veg, fresh meat and oil. Most diets involve this concept and claim to reverse diabetes associated obesity. Watch "Fat, Sick and Nearly dead", "Vegucated" on USA netflix. Not evidence- anecdotal I know but you can see that the concepts are similar.
So get on with what you are doing just stick to it and Peace man!!
This has come up in my facebook feed today.
It explains how pants the papers published on weight loss can be and why contradictory results are published in the media and in journals.
No wonder people are confused and battle each other because every diet is right and every diet is wrong.
I personally feel that most diets work its just what works for the individual, generally speaking, as long as you get fresh veg, fresh meat and oil. Most diets involve this concept and claim to reverse diabetes associated obesity. Watch "Fat, Sick and Nearly dead", "Vegucated" on USA netflix. Not evidence- anecdotal I know but you can see that the concepts are similar.
So get on with what you are doing just stick to it and Peace man!!
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That was a great article, but I'm still going to eat chocolate.
Entire books have been written on the subject of bad science, like this one:
http://www.amazon.com/Doctoring-Data-medical-advice-nonsense-ebook/dp/B00TCG3X4S/0 -
Me too definitely
I knew chocolate does not help with weight loss directly but helps with any craving. That book looks good too. 0 -
I forget who it was, but someone a while back posted a fantastic "how to" guide for actually reading and interpreting research studies. I will see if I can find it, when I get home. The basics include the fact that "significant" does not mean what most people think it means (it means the difference is probably not from chance alone... not that the difference between the two results was a large one). Always look at the data and sample sizes. And so on. I forget all of the points. I know it suggested reading it in a different order than you might (top to bottom) because you don't want to be told what you should be seeing, before you look to see what actually happened. You want to look to see what happened first, then you can see what the authors claim it means.
I don't remember what examples were used, but there were some good ones. Like the fact that dramatically reducing sodium significantly lowers blood pressure, in that the lowering is very unlikely to just be random. But, the actual amount it was lowered was by like a couple points.0 -
The above article also makes some of those points @FIT_Goat. Artificially implying significance from small data sets etc is called p-hacking meaning the p-values (and therefore significance of a study) is meaningless
From the article referring to "statistical significance"
"Whenever you hear that phrase, it means that some result has a small p value. The letter p seems to have totemic power, but it’s just a way to gauge the signal-to-noise ratio in the data. The conventional cutoff for being “significant” is 0.05, which means that there is just a 5 percent chance that your result is a random fluctuation. The more lottery tickets, the better your chances of getting a false positive. So how many tickets do you need to buy?
P(winning) = 1 - (1 - p)n
With our 18 measurements, we had a 60% chance of getting some“significant” result with p < 0.05. (The measurements weren’t independent, so it could be even higher.) The game was stacked in our favor.
It’s called p-hacking—fiddling with your experimental design and data to push p under 0.05—and it’s a big problem. Most scientists are honest and do it unconsciously. They get negative results, convince themselves they goofed, and repeat the experiment until it “works”. Or they drop “outlier” data points."0 -
You do enough experiments you're pretty much guaranteed to get conflicting data.0
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This is very interesting and well worth the read...0
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Just a question since chocolate got mentioned
I eat the 85% dark chocolate, 10 g a day which is a half serving, for my heart health.
I see lots of good articles. It has lots of fiber and less sugar.
Anyone else do chocolate for heart health? It does not mess up my weight loss at all
I have it with morning coffee and treadmill time0 -
I eat chocolate because I love it, and it might be good for me. Pretty good source of potassium and magnesium, if nothing else. I have a large hoard -- everything from 70%-100% cacao.0
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