The Science

The What the Hell Effect

Why a single slip so often ends the whole habit.


The What the Hell Effect describes what happens after a rule gets broken. You draw a hard line, you slip across it once, and instead of correcting course you abandon the entire effort. The name comes from the thought that arrives right after you miss: what the hell, I've already blown it.

Janet Polivy and Peter Herman documented it in dieters. Once dieters made a mistake, they went on to eat more than people who weren't dieting at all.[1] The slip was small. Writing off the day was what did the damage.

The effect has one requirement: an all-or-nothing rule, where anything short of perfect counts as failure. Habit apps ship that rule as a feature. They call it a streak.

What a streak runs on

A streak motivates through loss aversion. Losses feel roughly twice as strong as equivalent gains,[2] so a streak you spent thirty days building becomes something you protect, up until life happens and you inevitably miss.

The worst part is, all your effort was never aimed at the habit. It was aimed at the number. Miss one day and every workout you did still happened, but the number is gone, and the number was the thing you were protecting. With nothing left to protect, the force that kept you maintaining that streak disappears, and you're left with nothing.

That's the what the hell moment, the moment where most "habits" die.

What a miss actually costs

Phillippa Lally's team tracked people building new habits for twelve weeks and measured what a missed day does. Almost nothing. Automaticity dipped by a fraction of a point and recovered with the next repetition.[3] The habit didn't notice. Even in the largest habit study ever run, over 61,000 gym members, single misses weren't the problem.[4] Giving up because that miss broke your streak is the problem.

The streak takes the miss that cost you nothing and declares everything lost.

Why forgiveness doesn't fix it

Streak apps know this, which is why they sell forgiveness. Freezes, repairs, skip days.

Forgiveness has a math problem. The streak only worked because losing it hurt. Every free pass makes losing it hurt less, and a streak that can't be lost doesn't motivate anything. It's just a number going up.

So there's no good setting on that dial. Strict enough to work, and it collapses the first time life interferes. Forgiving enough to survive your life, and it stops being a streak. The best streak based options are somewhere in the middle, but they still suffer from the "What the Hell" effect.

Streaks don't build habits

A streak trains you to maintain a streak. That's not the same as building a habit.

Everything you do starts serving the number. What you show up for, how you show up, when you quit. The number becomes the reason, and a reason that lives in an app disappears with it. Take the streak away and there's often nothing underneath, because nothing else was ever built.

Lasting change isn't a number you defend. It's proof, stacked week after week, that you're someone who shows up. Nobody can reset that to zero.

What we built instead

Try Easier has no streaks.

Every habit has a Floor of once per week, and hitting it means you're on track. Not scraping by. On track. A packed week where you showed up once counts the same as a perfect one, because showing up is the goal.

Miss a few weeks and one session puts you right back, because there was never a streak to rebuild. Above that sits your Ceiling, the goal you're working toward, and it rises when you've earned it.

Most apps are streak based, and when the streak dies so does everything that came with it. Try Easier was designed so that eventually you won't need it. Once your approach to habit formation shifts, the system stops living in the app and starts living in you. But the app keeps all your beautiful statistics, the Horizon screen, and everything else. So don't abandon us out in the cold with the bears and the snakes and all the other spooky scaries.

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Sources

  1. Polivy, J., & Herman, C. P. (1985). Dieting and binging: A causal analysis. American Psychologist, 40(2), 193–201. doi:10.1037/0003-066X.40.2.193
  2. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291. doi:10.2307/1914185
  3. Lally, P., van Jaarsveld, C. H. M., Potts, H. W. W., & Wardle, J. (2010). How are habits formed: Modelling habit formation in the real world. European Journal of Social Psychology, 40(6), 998–1009. doi:10.1002/ejsp.674
  4. Milkman, K. L., et al. (2021). Megastudies improve the impact of applied behavioural science. Nature, 600, 478–483. doi:10.1038/s41586-021-04128-4