Hi, I'm Michael Corayer and this is Psych Exam Review.
In this video I'd like to talk about operation definitions and construct validity.
I'm going to start with a property.
So what is a property? A property is a general sort of concept that we want to investigate.
So researchers might want to know about the property of
happiness
or they might want to know about
depression
or intelligence.
And an important thing about properties is that we can't directly detect them
so I don't have a happiness detector that's going to tell me exactly how happy you are
Instead I need to have a way of defining it and this is my operational definition.
So an operation definition is the particular way that I'm going to measure the property.
It's important to remember that
it's not actually the property, it's just a representation of the property
It gives us a way to talk about
so for instance if I wanted to know about the length of a desk
you could tell me that the desk is 80 centimeters
and now this is not saying that 80 centimeters on a tape measure is the desk
but it's a useful representation
to help you determine whether the desk is going to fit in a particular space
and there's other operational definitions that you could use to talk about the length of the desk
you could tell me that it's 0.000497097 miles
and that might be just as accurate as telling me it's 80 cm but
in this particular situation it's not that useful. So different operational definitions are going to be more appropriate in certain situations.
In contrast, if I wanted to know the distance between
Austin and Houston
I'd probably prefer that you tell me in miles, because I'm not used to thinking about how many centimeters per hour my car can travel.
so if I want to figure out how long this trip is gonna take, centimeters isn't very useful.
Now we have experience using certain operational definitions like for length were used to using cm or inches or miles
so we have a pretty good idea what that means but when it comes to psychological variables
it can be little bit more complicated. So let's say we want to know about happiness.
How am I going to define happiness? I can't detect it directly so I need to come up with an operational definition, something that I can
actually measure and that's going to represent it's. So you might say "well, ok I could ask people on a survey I could say
how happy are you from -5 to +5", that would give me a measurement.
But it might be kinda hard to determine
what that means. What is +3?
That's not as comfortable to me as using cm or miles. I don't really know what +3 happiness means.
Ok, well I might measure smiling behavior. People smile when they're happy, people are happy they tend to smile, so I'm going to say
that, I'm going to count how much people smile and use that to determine how happy they are.
That might be a way of defining happiness. Or I might say smiling is too easy to fake, I want to use laughing
so I'm going to show people a video, count how many times they laugh, use that to determine how happy the video made them.
You might say, well there might be some brain activity associated with happiness. I'm going to measure people's brain activity in a scanner
and show this certain pattern of activity and use that to represent happiness
What we're hoping for with any of these operational definitions, we want to have construct validity
and what construct validity refers to
is the idea that we have the property
and we want to see a clear relationship between the property
and the operational definition we chose.
So I'm going to look at happiness and smiling, is there a clear relationship between these two? And we hope that there is.
We hope that the property is actually related to the thing that we're measuring.
So let's use that example, let's say OK I want to know about happiness
and I'm going to measure smiling behavior
and we're going to ask, is there a clear relationship between these two things?
Ok, people smile when they're happy, if people are unhappy they tend not to smile so much, so OK this seems like it has construct validity.
There seems to be a clear relationship between this property and this definition.
It's not perfect. Certainly people can be happy and not smile and people can be smiling even
though they're not actually happy. So it's not perfect but we can say
it has construct validity, it seems to have a clear relationship between these two things.
In contrast, I might say I wanna know about happiness
and let's see, I was really happy when I got a car
so I think cars make people happy so I'm going to count how many cars people have
and I'm going to use that to determine how happy they are.
If you have more cars then you're happier, if you have fewer cars, not so happy.
In this case you might look at this relationship and say "I'm not so convinced here. I don't think there's
a clear relationship between happiness and the number of cars that somebody owns".
There might be some relationship but it's not a very clear one. And I can certainly imageine lots of people who don't have any cars
who bike everywhere and they seem perfectly happy and I can imagine somebody who has dozens of cars but isn't actually happy.
So in this case, I'm going to say I'm not convinced, I don't think we have construct validity here. Our operational definition is not a
good representation of our property. Now this is where we see that operational definitions and construct validity are extremely important
because if this relationship isn't clear then my conclusions don't really matter.
if I told you my study was on happiness and I found some conclusion about happiness and then you looked at my paper
and said "wait a minute, you defined happiness as the number of cars that people had?" you would immediately disregard
my results, they wouldn't matter because you'd say "they're not really about happiness".
So this is why it's so important, a faulty operational definition
with low construct validity causes us to basically disregard any of the results from that study.
This is why this should be the first thing that you look at whenever you see a study or you see some results.
You say, "wait a minute, what's the property and how are they measuring it?". If that relationship isn't clear then I don't really care what the
results were. I hope you found this helpful, if so please like the video and subscribe to the channel for more. Thanks for watching!