The Power of Quackery

The psychology class keeps chugging along, and I keep finding new and interesting things to think about. (Which makes me think if I’d taken an intro to psychology class during my undergraduate career, I might have ended up a psychology major instead of a linguistics major. Maybe I’m just a sucker for interesting things . . .) For our next class, we read up on the proper use of case studies and the way they inevitably get abused.

I’m (fairly) sure you all know what a case study is: an in-depth analysis of a single person’s experiences with something. In an ideal world, case studies suggest areas for further investigation. Simply knowing that one person had a certain experience is no reason to conclude that single experience is properly understood, and that the conclusions it raises should be applied to everyone.

However, that’s often what people end up doing, day after day, when they look at their own experiences and decide they can reach all sorts of conclusions about How Life Is. A simple example: there was a local restaurant in town that I’d heard good things about from many different people. I hadn’t had a chance to make it there, but one Chester Greenwood Day they were offering free samples of soup. I tried one, and it was one of the worst soups I’ve ever had. So despite the fact that many other people had gone and enjoyed the restaurant, I never went back. That one experience was all I needed to know it was bad.

I fall into the same hole when I’m looking at online reviews of something I’m thinking about buying. I can see that 10,000 people gave something 5 stars, but I also see that 50 people gave it one star, and that they wrote long reviews about how awful it was. A lot of the time, those few in-depth bad reviews are enough to keep me from pulling the trigger, despite the fact that the vast majority of people disagree. (Well, that and the knowledge that sometimes those reviews are falsified . . .)

People fall for this trap when looking at science, as well. The vast majority of scientific data will say one thing, but a few outliers will say something else, and some end up giving that small slice much more credence than the rest, just because it agrees with what they want to believe anyway.

When these small outliers are deliberate, the text defines them as quackery, and it makes a point of showing just how easy it is to fall for it, especially when it’s somehow connected to a trusted source. (The example it uses is one where Oprah Winfrey used one of her shows to highlight an “alternative medicine” approach to treating cancer. After the show aired, a fan wrote to her, gushing about how wonderful it was, and how she’d decided to stop her doctor’s suggested cancer treatment to follow this new approach instead. Winfrey tried to convince her otherwise, but too late. She stopped treatment, and then she died soon after.

The fact is, it’s not that difficult to fine “case studies” that prove just about anything you want to prove, and many have started to criticize science, saying “they always end up contradicting themselves anyway, so why should I listen?” But in the end, I believe informed decisions are the best decisions, and that relies on the information being correct. When science ends up being wrong about something, it says so. Publicly. And just because it was wrong doesn’t mean it was deceitful. It was using the best data available to make the best conclusions possible. Sometimes that pans out; sometimes it doesn’t.

But friends don’t let friends fall victim to quackery.

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