Carroll/Langer: Credulous, scientist-as-hero reporting from a podcaster who should know better
Statistical Modeling, Causal Inference, and Social Science 2024-10-19
tl;dr. To the extent that healing is important, I think it’s important not to overstate evidence for speculative claims about what works. Individual and societal resources are limited. If you want to say something like, “Sure, this is pie-in-the-sky research, but if it works it would be wonderful (‘kind of amazing,’ as Carroll might say), so it deserves our attention, respect, and funding as a high-risk, high-return possibility” . . . go for it. That argument could be made. But then that argument should be made. Don’t fudge it by acting as if there’s evidence that isn’t really there.
Pointing to a podcast of Sean Caroll interviewing psychologist Ellen Langer, commenter Mark writes:
I [Mark] found myself wanting very much to ask her to substantiate the grand claims she was making about how mindfulness (as she defines it, which itself was a bit squirrelly) makes people heal faster, reverse age, and feel perpetually alive and happy.
Sean Carroll is a physicist, so I was hoping for a more rigorous dive into the science and data that Langer asserts is overwhelmingly supportive of her claims, but was notably absent from her explanations. Lots of anecdotes and stories and pithy phrases, though!
“Brash and unscientific” indeed. Also alarmingly overconfident in her views (in direct contra to her description of the “mindlessness” – lack of curiosity and doubt – that she alleges virtually all humans have about their own views). Frustrating to listen for so long with no substantive response by Carroll.
I agree. We’ve written about Langer before (see above link), and more recently Nick Brown and I did a deep dive into a couple of her papers claiming to find evidence of mind-body effects. We concluded that those papers are fatally flawed in the sense of not providing evidence to support their strong claims.
Carroll’s podcast is here, and it conveniently has a transcript, so I could find some of the relevant parts.
Here’s the key bit from Carroll, right at the beginning of the interview:
Ellen came out with a new book at the end of last year called The Mindful Body: Thinking Our Way to Chronic Health, which is about the physiological, the health benefits of mindfulness. And it’s very interesting, she has a lot of studies, right? This is very data-based, and some of the results of these studies are kind of amazing. . . . You can think of it as kind of like the placebo effect. You take some pill that really isn’t anything at all and your mind coaxes your body into getting better. But turning that on its head to make it much more intentional and cognitive and active rather than tricking yourself, just thinking yourself into feeling younger, healing faster, generally being more healthy. So I mean the data are there. . . .
I don’t think the data are there. To be precise, some relevant data exist, but, from the published papers, I don’t see these data providing good evidence for many of the claims being made.
More generally, statements such as “This is very data-based” and “the data are there” are nothing but empty hype if you can’t point to the actual data and their relation to the (justly) controversial scientific claims. Otherwise, you’re just bullshitting. You could just as well interview someone about the Loch Ness Monster or whatever and say “This is very data-based” over and over and hope your listeners don’t go and check.
From the podcast interview, here’s Langer:
All right, we take chambermaids, and we first ask these chambermaids these are people who are cleaning hotel motel rooms, whatever, how much exercise do you get? Well, because the surgeon general describes exercise as what you do after work, and they just too tired, they don’t think they’re getting any exercise. All right, so we take lots of measures, the study is very simple. We divide them into two groups, and one group we teach them that their work is exercise, making a bed is like working at this machine at the gym, and so on. So we have two groups there. One group that knows their work is exercise, the other group that is unaware of it. We want to make sure they’re not eating any differently, they’re not exercising any more, they’re not working any harder, everything is the same except for they change in their mindset. Now that they saw their work as exercise, they lost weight, there was a change in waist to hip ratio, body mass index, and their blood pressure. Which is remarkable, right?
Carroll responds with complete credulity:
Oh, yeah.
That’s a bad response! Nick Brown and I looked into that paper carefully and, no, there’s no evidence that “they’re not eating any differently, they’re not exercising any more, they’re not working any harder, everything is the same except for they change in their mindset.” The most “remarkable” thing about this podcast is that the interviewer just accepts these claims.
And here’s Langer with another example:
So we have people, we have three groups of people. Unbeknownst to them, to all of them. For a third of them, the clock is going twice as fast as real time. For a third of them, the clock is going half as fast as real time. For a third of them, it’s real time. The question we’re asking is, will that wound heal based on perceived time, what the clock tells you, or real time? And the answer is perceived time.
Again, no.
On the plus side, they didn’t mention the so-called “poison ivy” study (see section 3.2 of the above-linked article with Brown).
P.S. The webpage for the podcast has a comment section, and most of the commenters express strong skepticism of Langer’s claims, picking up on the lack of persuasive data and the potential risks of taking these speculative ideas too seriously. It’s an interesting example where the commenters are much more grounded than the main post.
I wonder if Carroll will read those comments and reassess.
My recommendation is that he conduct do a followup interview with Nick Brown, a person who, unlike Langer, has not received her Ph.D. from Yale, is not a professor at Harvard, has not had multiple gallery exhibitions, and has never received a Guggenheim Fellowship or a Genius Award—but who is careful not to exaggerate what can be learned from data.