In this series on punishment I have talked about the behavioral research on punishment and long term studies on spanking. In this post we discuss the last of three lines of research on punishment: statistics.
Don’t worry. You won’t have to read eye-glazing percentages about punishment. I don’t mean that there are not really interesting statistics on punishment (there are), but that the science of statistics itself has discovered a phenomenon that can tell us something very important about punishment: regression to the mean.
Stats geeks love regression to the mean because once you really get it, you start seeing it everywhere. Oh, and it has a lot of explanatory power.
Regression to the mean starts with the idea that there is a mean, or average, around which things cluster. It is often represented by a line down the middle of a bell curve, like this:
Things that fall in the middle of the bell curve, near the line, happen more often and things that happen less often are at the tails (where the little guy is writing).
Let’s apply this concept to a specific child behavior. For example, imagine (in a perfect world) that your child remembers to say “please” an average of 5 times a day, so the mean of that behavior is 5.
However, even though the mean is 5, she doesn’t do it exactly five times every day. Usually it is a little higher or a little lower than the mean. Occasionally, at random, it is a lot higher or lower (in the tails of the bell curve). On one day she may say please 10 times and on another day she may completely forget it.
These kinds of variation in behavior happen all the time regardless of what the parent does. And when random variations occur, they usually return to normal (the mean) quickly. That is what “regression to the mean” is: the tendency for exceptionally high or low rates of behavior to go back to normal right away.
So on the day after she remembered to say please 10 times she is likely to go back to 5, and the day after she totally forgot she is likely to go back to 5, at random.
Here is where this can trip you up as a parent. If you are really hyper-focused on a behavior, for example you really want to get your daughter to learn to say “please” every time before your in-laws come for the holidays, then you are going to be very sensitive to every little increase and decrease in pleases, even the random ones. You will try to find reasons why it changed, and more than likely you will find reasons other than “it happened randomly.” In other words, you can attribute the behavior change to something you did, even if it had nothing to do with the change.
And this is where punishment can seem effective even when it is not. Even stranger, rewards can seem ineffective, even if they are working!
Here is how it works. If you punish her on the day when she forgot to say please by giving her a harsh lecture, the very next day the behavior regresses to the mean, which means it increases. You’ll think that the lecturing must have really got through to her.
Conversely, if you reward her on the day she says it many times it will seem ineffective because the next day she is back to the mean again, which is lower.
You’ll start to believe rewards are wishy-washy because she is now doing worse, but harsh lectures are effective because she always does better. This quirk of statistics can mislead parents if they are paying especially close day-by-day attention to behavior.
My advice: focus on behavior change over longer periods of time than day to day. Assess change over weeks, not days. Use rewards frequently, punishments rarely.
Want to learn more? Contact Dr. Ron for a FREE 30 minute consult.
Here is a wonderful video that explains this concept in detail: