Imagine your friend — we’ll call him James — starts up about this new woman he’s been dating. “She’s so great,” he says. “And on top of that, the sex is amazing!”
You’re happy for James, of course. But at the same time, you know your friend isn’t always the most careful.
“You’re using protection, right?” you ask.
“Well, sometimes we use a condom. But you know how things can get,” James says with a wide smile. “Besides, I haven’t had a pregnancy scare yet. No need to change something that works! Am I right?”
James is not right. Rather, your friend is the victim of the hot hand fallacy, which creeps up frequently in contraception.
The hot hand fallacy refers to someone being lucky and expecting that luck to continue. In reality, the risk of failure is continuous and independent of any previous luck. This mistaken idea is common with gambling or with success in sports like basketball.
Here, your friend James doesn’t have a “hot hand” when it comes to avoiding pregnancy. He’s just been lucky. He’s been using a condom, though highly inconsistently. We know from our previous blogpost that the latest numbers for typical-use annual pregnancy rates for the condom went down to 13%.
If we’re taking the same advice from that blog post to estimate pregnancy risk, then we start at the 13% typical-use base pregnancy rate. Then we ask ourselves if a contraceptive user is worse or better than average at using the method. (We also ask about other factors like frequency of intercourse.)
We’ll say James is significantly worse than average as a condom user and has a 35% annual risk of causing a pregnancy. Given this, what are the chances that James is able to keep up his luck in future years?
His luck looks something like this:
His risk of avoiding a pregnancy next year is still 65% (35% chance of causing pregnancy), but his “luck” in future years drops over time. Still, his chances of avoiding a pregnancy is never zero. This idea means that there’s always some person like James out there who thinks they’re lucky and what they’re doing is going to keep working. But — assuming they weren’t tested as being infertile — that doesn’t change that person’s real risk or anyone else’s.
When doing this type of analysis, it’s nice to have a control reference. Below is what the luck looks like for both a perfect and typical condom user.
As you can see, the more time that elapses, the more these differences make an impact. For instance, after ten years, a typical condom user is 25 times more likely to have avoided an unplanned pregnancy than James is as a poor condom user. And a perfect user is over 3 times more likely to have avoided an unplanned pregnancy than a typical user during this ten-year time frame.
The takeaway is that James shouldn’t rely on his prior luck because that same luck will tend to thin out over time. And perhaps even typical users should recognize that they’re relying more on luck than they realize. This surprising risk is a good case for doubling up methods.
This risk of causing a pregnancy — whether understood by users or not — is why our work is important. We want to make sure we have more options available that are both effective and can combine well with other contraceptives. As you can see, having good options that users can adhere to in the real world makes a big difference.
In the meantime, don’t rely on luck like James. Because it’s likely to run out sooner than you think.