Psychology 101: Intro to Psychology

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How do validity and reliability contribute to study design in psychology? In this lesson, you'll look at how experiments can fail reliability and validity requirements to get an idea of the challenges behind conducting significant psychological research.

Designing a psychological study isn't really that hard. If you've ever written a survey or taken a poll among your friends, you've conducted some crude psychological research. But designing a study that produces valuable and scientific results is really challenging. If you gave your friends a survey about their political leanings, they might be influenced by the way you phrased the questions or by knowing your own political opinions; your survey might not accurately measure what you think it does. Two key concepts for designing scientific psychological studies are reliability and validity. We'll look at some examples of both to better understand the importance of careful research design.

Do you have a friend or family member who will always help you out if you ask? You'd probably describe this friend as reliable. Reliability in psychological research isn't really that different - it means that your tools for measuring a given variable measure it accurately and consistently. If you use a rigid ruler to measure the length of your foot, you should always get the same length; this is a measurement that has test-retest reliability. But if instead you measure your foot by holding your fingers about an inch apart and then moving them down the length of your foot and counting as you go, you'd probably come up with different measurements each time. Your fingers are not a particularly reliable measurement tool for the length of your foot.

Important to designing and interpreting psychological research is the idea of validity. In general, validity refers to the legitimacy of the research and its conclusions: has the researcher actually produced results that support or refute the hypothesis? It can be easier to understand validity by looking at some of the ways that research can be not valid.

A study fails construct validity if what it chooses to measure doesn't actually correspond to the question it's asking. Let's say you were doing research that required you to know how intelligent your subjects were. To measure intelligence, you decide to administer a really difficult physics exam. If you did this, your experiment would lack construct validity because a score on a physics exam doesn't really measure intelligence; it just measures whether you've taken physics or not.

Internal validity has to do with confirming that a causal relationship you've found between your variables is actually real. Even if you think you've found a definite relationship between changing one variable and observing change in another, you could be inadvertently changing something else that is actually causing the effect. As an example, let's say you wanted to test whether certain colors of fonts help people remember information better than others. You give your subjects two texts, one in green and one in red. The red text is about celebrity gossip; the green text is about chemistry. You find that your subjects remember the red text much better and conclude that red font helps memory. But by having two different texts, one much more easily memorable than the other, you introduced a confound into your experiment. You don't know whether your effect is caused by the red font or by the more interesting content.

A third type of research validity is external validity, which has to do with your conclusions applying to more people than just the ones you tested. Though psychologists might like to test everyone, doing so would be absurdly expensive and time-consuming. So instead, psychologists take a sample of the population they want to study. This sample group is usually selected at random, based on who volunteers to participate. Psychologists try to get bigger groups to control for random variations. Usually the results found in the sample are assumed to generalize, unless there are compelling reasons to question it: for example, if a study on attitudes toward aging had only college students for subjects, it might fail external validity.

In general, reliability and validity are principles related to making sure that your study is actually testing what you think it is. Reliability makes sure that your test measures its variables accurately. Validity ensures that your measures and variables are telling you what you think they should; that your questions assess the right variables, that your experimental results have no confounds and that your results generalize like you think they will.