Validity Issues in Adult Development & Aging Research: Explanation & Examples

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  • 0:02 Definitions
  • 2:02 Validity
  • 4:01 Meta-Analysis
  • 4:39 Issues
  • 6:24 Lesson Summary
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Lesson Transcript
Instructor: Devin Kowalczyk

Devin has taught psychology and has a master's degree in clinical forensic psychology. He is working on his PhD.

This lesson goes into some depth about what validity is and its different types. The lesson is finished with an examination of the main causes of skewed validity and a possible way to compensate for it.

Defining Validity

You sit down to take a test. You studied all semester. You read the book, and you know exactly what is going to be covered during your abnormal psychology course. The professor hands out the test, and you take a look at the first question.

It reads, 'What is the sum of a fractal series?' The look on your face could be described as somewhere between perplexed and dumbfounded. You would think, 'This isn't ab-psych,' and you're right.

Validity is a description of how well a test measures what it is intended to measure. Our example of you taking your abnormal psychology test demonstrates that the test lacks validity. In other words, it does not appear to be measuring what it is supposed to be measuring.

Validity is kind of a big thing throughout psychological research. Many pseudo-sciences will make claims, like how crystals will form under happy music or plants will die if you yell at them, yet lack the ability to demonstrate their validity. That is, these pseudo-sciences lack the ability to demonstrate what they are doing actually measures what they're intended to.

Let's look at a different example. What if we wanted to test the idea that the more water a person drinks, the better they age. We collect a whole lot of people of different ages and ask them how much water they drink on average. With our results, we have to ask ourselves how ecologically valid our results are.

Ecological validity is defined as the level to which we can apply findings to real world situations. With our drinking water example, we can say that most of the first world countries the results apply towards. However, if we examine some third world countries, we would have to question the results because water is not the only issue or the main issue when it comes to how one ages. We will examine different types of validity here in a moment and then an alternative way of looking at how results work together.


Validity is the idea of how well the test we are using actually measures what we want it to. There are a handful of types of validity we need to look at. These are different ways something can be valid since there are multiple ways to justify a test's measurements. A goal of a researcher is to have as many of these types of validity as they can.

A test is said to have face validity when the test appears to measure what it is intended. This is the simplest and easiest form of validity to obtain. Basically, does your test ask questions or focus on a single area? Our example of water and aging would have questions about how much water people drink and the effects of aging.

When we examine the test itself, we can say that a test has construct validity when the test has been approved by experts and, by their opinion, appears to measure what it intends. Here, the validity is based on people who know what they're talking about. The expert we might use could be on aging, maybe an expert on cellular biology and possibly someone who knows how to construct surveys.

After collecting and analyzing the results, we can say a test has criterion validity when the test results correlate with other tests that measure what we're interested in. With this type of validity, we need two things: the results of our test and the results of other tests proven to measure what we're interested in. If our water and aging tests were very similar to water and health measures, we could say that we have criterion validity.

Lastly, we have sampling validity when the test includes questions covering a large range of areas dealing with the intended measurement. This is where the test samples different questions to get a bigger picture. Our water aging study would have questions about water dealing with soda, water and tea, while our aging may have areas of general health, skin and heart conditions.


A meta-analysis is a method of combining results from multiple research articles to say something the individual articles could not. A meta-analysis can be used to confirm the validity of multiple articles by combing their results. If we had ten different water and aging studies and we combined their results, then we have a much larger picture than if we only had one article.

A meta-analysis allows a researcher to describe larger patterns and interactions. With multiple findings, it's sort of like having more pieces to a puzzle. We may not have everything, but we can start to describe something that we may not have seen before.

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