I worked out all the time in high school, back when my teenage brain thought it was totally plausible that I could eventually become a professional basketball player (ahem).
But after that? I didn’t do much at all until I decided to commit to the Couch-to-5k thing last fall. I haven’t stopped working out since, mixing in everything from more running to strength training to HIIT (gosh that’s painful stuff). Naturally, as an athlete now (riiiightt), I started trying to learn more about effective recovery.
You don’t have to look hard to find endless articles and posts online detailing exactly what kinds of recovery you should be doing, and what types of recovery you should be avoiding. But like a lot of health advice, they can be very contradictory. There’s a lot of confusion and misunderstanding about not just which types of recovery are effective, but just when and how to best take advantage of them.
Good to Go is Christie Aschwanden’s attempt to parse through all the cruft to find out what recovery methods actually work. She does so in a very conversational, readable way. But this isn’t just a book for folks who like to exercise. Along the way, Aschwanden helps the reader to learn to think more critically about the research and studies that a lot of health advice is based on.
Many of the studies that these results come from, for example, are based on a very small sample size—10 or so people. Other data is far from conclusive, but the results were “marketable” (like research around sports drinks, for example) so they were promoted as more definitive than the data showed.
Sometimes the studies themselves were designed in a way that adhered to pre-existing biases. Take, again, sports drinks. It turns out, what you use as a placebo ends up dramatically impacting the significance of the benefits of drinking something like Gatorade.
When people volunteer for a study to test a new sports drink, they come to it with an expectation that the product will have some performance benefits. Studies use a placebo group to factor out such effects, but a placebo only controls for these expectations when it’s indistinguishable from the real deal. So it’s telling, Cohen says, that studies using plain water for the control group found positive effects, while the ones that used taste-matched placebos didn’t.
Other times, the results of a study get widely spread, but not the context. Ice baths were a good example. It’s a commonly cited recovery method, but it depends quite a bit on context. Turns out, if you’re in the “building phase” (trying to get faster, stronger, etc) it’s probably best to avoid the ice bath. If, however, you want short-term recovery (say, a long run with another soon to follow) then it can be beneficial.
Over and over, Aschwanden breaks down advice being spread without consideration of the size, biases and overall validity of the underlying studies. It’s a good lesson in critical thinking. It is also, likely, a little discouraging to anyone who was hoping to find a foolproof, silver bullet for recovery.
She also takes on fitness trackers and related apps. To be clear, I think there are definite benefits to using those sorts of tools. They can provide good motivation, prompt you towards making better health decisions, and the social aspects can help you stay accountable. But Aschwanden also points out the negatives. If we’re not careful, we can get too tied up in the numbers even if, ultimately, they may only have a loose connection to our overall health.
Her final conclusion on recovery? Ultimately the only thing we can say definitively helps with recovery is sleep (not a surprise if you’ve read Why We Sleep). Other than that, it’s mostly about the placebo effect. If you find something that feels like it’s making a difference for you, then stick with it.
If I’ve learned anything about recovery, it’s that the subjective sense of how it feels is the most important part.
A few highlights:
The bottom line is that science is hard, and sports science especially so.
My college anthropology professor taught me a name for narratives people develop to explain their data—"just-so" stories. The name comes from Rudyard Kipling's fanciful animal tales for children, which explain, for example, that the camel got its hump as punishment for being lazy. Just-so stories are appealing because they so perfectly explain the data you've found. That's not because they're true, but because they were explicitly created to fit the data.
Lab tests can advance scientific knowledge, but they can also direct our attention to the things easily measured, rather than the things that really count.
I once had a coach tell me, "Any fool can go train more. It takes courage to rest."
Nothing else comes close to sleep's recovery-enhancing powers. You could add together every other recovery aid ever discovered, and they wouldn't stack up.
If you're forced to pick between some extra shut-eye or an extra workout, it's wiser to pick the sleep, Singh says. Sacrificing an hour of sleep to make a morning workout is totally self-defeating.
In a perfect world, science is supposed to seek truth and go wherever the evidence leads. But in practice, studies may be used as marketing tools by designing them to back claims that a company wants to make about its product.
But the culture of "go hard or go home" and the advent of social media apps like Strava and MapMyRun that allow people to view data on other athletes' workouts means that "everybody is constantly comparing themselves," Dieffenbach says. "It becomes a competition for training, but in those apps you don't log everything else you did in the day. You don't know what anybody else's budget is or what genetic lottery she won or trust fund she was born with. Maybe she needs more sleep than you do. Those comparisons won't tell you that.