- Just to jump right to the chase, this is my own example.
When I eat chocolate, I lay down my own reward hierarchy.
And it goes broccoli at the bottom,
milk chocolate very low down.
60%, 70%. Now you're talking.
75%. Add in some sea salt, maybe a little cayenne pepper.
And now it's rewarding.
So how does it actually work?
For those of you that are mathematically inclined
or just like to know that there is math behind this,
there was a model developed by Rescorla
and Wagner back in the '70s.
This is something that we can actually embed
right into these tools to measure
the change in reward value.
Just in the interest of time I'm not gonna go
through all the details.
We're gonna focus on one particular aspect,
which is called an error term.
And what this means is, you know,
basically current reward values
based on the previous reward value.
If we don't pay attention, this is zero
and we just keep doing the same thing.
If we pay attention, we can get a positive
or a negative prediction error.
That's the error term.
Positive prediction means let's use an example.
If somebody, let's say I like chocolate cake
and I go to a bakery.
And it's a new bakery.
I see some chocolate cake. It looks good.
I eat that chocolate cake. And it is amazing.
It's the best chocolate cake I've ever had.
I get a positive prediction error,
meaning my brain expected it to be so rewarding
but it was better.
My brain lays down this behavior that says
or this reward value that says,
"Hey, go back to this bakery and eat this cake again."
If I eat the cake and it's not that good,
my brain's like eh, I get a negative prediction error.
It's not as good as expected and so I'm less likely
to go back and less motivated to go back to that bakery.
So long story short, we can actually embed this
right into our Eat Right Now app where we first
have people imagine eating, so either a type
or an amount of food.
And what that does is it, you know,
it's projecting the future based on past experience.
It brings back the reward value from whatever
we've laid down previously.
And then we ask people, "How much are you craving it?"
If they crave it more, it suggests that it's got
a pretty high reward value.
If they bring it up and they go eh,
they may not have that high of a reward value.
And then we have them pay attention as they eat.
So they go through a mindful eating exercise.
And we can take all of this together to measure how quickly
they change behavior based on this change in reward value.
I'll show you a couple of studies that we just finished.
These are actually in press now.
These were just accepted for publication.
It was a study that we did with 38 individuals.
And we found that within 10 times
of somebody paying attention as they mindfully ate,
that reward value dropped below zero,
as in below not eating.
You can see the probability that they would shift
their behavior from overeating or eating the junk food
to not doing that.
There's another study of 1,000 people
in a community sample where we actually found again,
you know, five, 10 craving tool uses,
not very long before it drops below zero
and we get a shift in behavior.
So that's pretty remarkable in terms
of seeing this mathematically.
What are people reporting? Here are some examples.
This person said, "The food is distracting.
"It also can create a pleasant shift for a moment inside
"but then you need more food, more distraction."
So this person was starting to see
how the brain was functioning.
The gig was up basically.
Or as this person put it, "Dear sneaky habit loop
"that says eating junk food is fun.
"I am on to you."
I think I have one more example.
This is from smoking, same idea,
somebody said, "Today all the cigarettes
"I smoked were disgusting."
So there we are I hope that gives you a good sense
for this second step, which is really to focus
on how rewarding a behavior is.