With any psychological question, what we are really trying to establish is better understanding of a property. We want to know about properties like happiness, depression, aggression, intelligence, etc. The problem with wanting to know about psychological properties is that they can be especially difficult to measure.
In other sciences, it can often seem easy to determine how to define a particular measurement. For example, the general property of length can be defined in terms of centimeters. It’s important to remember, however, that centimeters themselves are really just one way of talking about length, they are not the property itself. In other words, measures do not detect properties, they simply provide more convenient representations for us to talk about.
It’s simply been agreed upon that centimeters are a good way to talk about length and ideally your centimeter is the same as my centimeter (if not, the measure would become useless). When I decide to measure in centimeters, this is my operational definition for the property of length. We may say that the property of length has been operationalized as number of centimeters. Someone else may choose miles, nanometers, or furloughs, which would just be different operational definitions for the same property (length). Depending on the situation, some operational definitions may be more appropriate than others. So if we’re at IKEA it’s easier for me to tell you that a desk is 80 centimeters in length rather than tell you that the desk is 0.000497097 miles. Even though both of these may be accurate, one is better for helping you decide if the desk will fit in your bedroom.
The same concept is true in psychological research. We may refer to particular measures like depression scales, personality inventories, or satisfaction-with-life assessments, and these are ways of attempting to agree on measurements of psychological properties. As you might guess, however, agreeing on how to define a property like happiness is far more difficult than agreeing to define length in centimeters. I may choose to measure happiness by counting smiles, recording laugh time, completing a survey from -5 to +5, or by looking at patterns of brain activity.
No matter which approach I use to measure happiness, I’m hoping to have construct validity. Construct validity means that the operational definition that I’ve chosen has a clear relationship with the property in question. For example, we might say that using smiles as a measure of happiness has construct validity because we know that there is a relationship between being happy and smiling. In fact, this is an operational definition we probably use quite often when assessing happiness in daily life. We see someone smiling and immediately assume he is happy. Or we try to make someone happy and gauge how successful we are based on whether or not they smile. This doesn’t mean that smiling always represents happiness (as there are fake smiles and happy non-smilers) but in general the relationship seems clear.
If instead of counting smiles I chose to count cars as my measure of happiness, the relationship may not seem as clear. While I may argue that owning cars makes some people happy and therefore more cars equal more happiness, chances are that many people would disagree with me, citing happy bikers or depressed millionaires with garages full of vehicles. Or they may even cite the car dealer who is happiest each time a car leaves his possession. In this case, my operational definition (measuring happiness as # of cars owned) would be criticized as having low construct validity, meaning that it does not represent the property I’m hoping to study.
This post is an excerpt from Master Introductory Psychology: Complete Edition
