As I said before, my day job is an engineer. Which, right now, consists of looking up past studies to get a good background on a topic. Looking at different articles and journals day in and day out is only made efficient by being able to weed out the not-so-credible studies.
Health studies are no different. Every day there is a different headline of “Eat oranges and lose five pounds in a day!” or “Study shows exercise actually makes you fatter!” To keep this crap out of your blog and out of your readers’ mind, you have to be able to weed them out for yourself.
Here are some things to look for:
Who sponsored the study? Yes, researchers are required to be biased and blah blah blah. But really, if a study is sponsored by, say, the Dairy Industry and it talks about how great dairy is for you…we’d like to believe it’s true, but who knows? Money talks.
Who participated in the study? Look at the number of them, (just because ten people had something great happen…is that really enough to say everyone will benefit?) and look at the demographics (age, sex, health status) — a study of healthy 24-year-old marathoners might not be relevant to the 55-year-old water aerobics crowd.
Distinguish between results and interpretation of results. Results could be “Group taking fish oil dropped two pounds in one week while control group dropped one pound.” Interpretation of these results would be “Fish oil increases weight loss 100%!” That’s what researchers call a “huge effing leap” (technical term).
Check out the “methodology” section. This details how the study was done. While some of it is about as exciting as watching paint dry, it lets you know if there was a control group (there should be), the time frame (can one day results really count?), what was monitored (outside factors might affect it) and other study specific items.
These are just a few items to check out when you’re reading a study. It’s always better to go directly to the source and not an article referencing it. You really don’t have to read the entire 200 page study but you should be able to pick out where the important information is!
Follow these rules and it’ll help you keep a “Umm about that last post….” out of your blog!
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{ 4 comments… read them below or add one }
Bridget, thanks for this post. I am an aspiring scientist myself and love to look at and quote health studies. While I try to pick good studies, I’m not always confident in the validity of them so I will be referring back to this checklist! I worked in a lab and we found it took a very long time to get our paper published, so it really surprises me that people can publish some ridiculously thin studies!!!
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Great post! It’s so important for people to understand that studies are not always 100% conclusive and that the science behind them needs to be carefully examined and weighed. In my line of work, I often have to write about health issues and health stories, and it’s pretty sobering to look at the details of some of the studies that are published. It’s really easy for a story that says “X might help do Y” to turn into “X is the definite answer for problem Y.”
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Great guidelines and call for accountability in presentation! There are many very well-known sites that present research in the “eating chocolate chip cookies led to a reversal in diabetes” format and report other absurd conclusions from poorly designed experiments. I cite my sources and tell my readers, when appropriate, more research is necessary. Finally, I leave them with the caveat that ultimately they should draw their own conclusions on a presented topic and if it integrates into their lifestyles. I’m a researcher by day (public health at a major university in SoCal). Your “technical term” brought a big smile to my face.
And let me add – you should not draw a conclusion based on just 1 study. I think that’s why people get confused. A study is like an investigation into something, where a scientist says this is what I found. A responsible scientist in the study will not say this is definitive. Instead, the study – unlike journalists who report the study – will probably say if this follows work that has already been established. If it does – great – then you can make some inference. If it does not, then further work will be done by that scientists and others, and the study should say so.
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