Headline facts.
They’re the “facts” you get from only reading headlines. Almost all of us are guilty of it.
If you’ve ever used Reddit, Facebook, Twitter, or Instagram, it’s almost guaranteed to have happened. You read a headline someone posted about, but not the actual article, and later repeat the headline as truth.
Often times, if you had read the article, you’d have realized the original headline skewed or misinterpreted the facts. Whether it be malintent or incompetence, the end results remains the same: misinformation.
Most of the time this is done for clickbait purposes, to drive traffic to journalists’ articles and make money. However, incorrect headline facts can happen with science as well.
Results from low quality, flawed, or irrelevant studies can be presented as headline facts to the casual observer – if you read the original study, you realize the headline presented the findings incorrectly.
Why is this important?
Because when you read headlines about studies, especially when researching information to help heal your body (as we deal with), you must realize the headline is NOT the full picture and may, in fact, lead you astray.
An example:
While researching the best and newest evidence for treating shin splints to incorporate into our app’s tailored rehab protocols, we came across a meta-analysis and systematic review (cream of the crop of evidence that combines other pieces of evidence together for big conclusions) that stated for shin splints: “Weekly mileage was not a risk factor based on pooled data from 2 studies.”
This blanket statement seemed counterintuitive as shin splints are inherently an overuse injury, so mileage SHOULD matter. Usually the results from research papers like this are valid. However, due to the nature of the statement, we needed more information.
After diving into one of the actual studies, we concluded that the statement was neither accurate nor standing on a solid foundation of evidence, primarily for 3 reasons: running mileage was self-reported, the majority of the participants were cross country runners, and the population did not represent the general population.
The second of the two studies the statement above was based from was very similar in nature, so for simplicity’s sake we’ll talk about just one.
Reason 1: The mileage was self-reported.
The participants in the study were all division 1 and division 2 athletes at a single college. The sports were: cross country, track and field, soccer, tennis, volleyball, and cheer. The authors collected data, including weekly mileage, at the beginning of the season, then waited to see who developed shin splints during the season.
The big problem was how the mileage was collected: by self-report. Cross country athletes would know exactly their mileage, but soccer, cheer, and tennis? How many miles did they run in a game, match, or practice? Extremely hard to know, let alone estimate on the spot on a questionnaire for researchers. This leads to over and underestimations that skew the data and thus the results.
Reason 2: The majority of the participants were cross country runners.
Of the 146 athletes, 74 were cross country runners. They are, of course, notorious for running extremely large weekly mileages, especially compared to tennis, cheer, and volleyball.
At the end of the study, when there were two groups (one group that developed shin splints and the other that did not), the cross country athletes made up about half of both groups. Because they run so much more than the other groups, their large mileages would heavily outweigh the other participants’ mileages. Since there were also equal ratios of cross country runners between the two groups, you would expect the averages to be equal as well.
Well, they were.
However, since the average weekly mileage was the same between the group that stayed healthy and the group that got shin splints, the statement was made that mileage didn’t matter with shin splints, based on that exact data.
Now we hope you see why a technically true statement about a single study can be off-base from reality.
Reason 3: The population does not represent the general population
Though we know the flaws in the study design, lets, for a second, grant that the statement “mileage doesn’t matter” in this study was actually valid. What would that even mean?
It could ONLY mean that mileage does not matter for that specific population: 20-year-old college athletes. Is that the general population? NO, so you cannot generalize the results as such. However, as the meta-analysis states “weekly mileage was not a risk factor”, it does not specify the population type. Instead the meta-analysis only noted it was based on data from two studies. It would have been up to you (and us) to look into the exact data the claim was based off of.
But, honestly, how many people take the time to comb through original pieces of research? This is how headline facts can make their way into science, and into your own life.
End example.
So why are we writing this and why do you care?
Because when it comes to your body, you need to do what’s ACTUALLY good for it. You don’t want to start running endless miles because you think mileage doesn’t relate to shin splints.
You don’t want to headline fact your health.
You need to either look into the research yourself or use resources from those that have. In this case, we can be that resource. For daily prevention of injuries to tailored rehab programs, we look into the details to ensure the i’s are dotted and t’s crossed. We ensure you are getting appropriate and good rehab and prehab programs for your body.
Whatever you choose to do, just don’t be a headliner. Stay functional, stay fit, and build healthy habits using solid evidence to lead a more productive life.
References:
Hubbard TJ, Carpenter EM, Cordova ML. Contributing factors to medial tibial stress syndrome: a prospective investigation. Med Sci Sports Exerc. 2009;41(3):490-496.
Reinking MF, Austin TM, Richter RR, Krieger MM. Medial Tibial Stress Syndrome in Active Individuals: A Systematic Review and Meta-analysis of Risk Factors. Sports Health. 2017;9(3):252-261.