Cross-sectional, Longitudinal & Sequential Designs: Advantages & Disadvantages

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  • 0:03 Definitions
  • 2:38 Advantages
  • 4:02 Disadvantages
  • 5:03 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 examines the three main ways of conducting research on adults and older individuals. Specifically, we will examine the three types, some of their advantages, and some of their disadvantages.

Types of Research Design

Maturation and growth don't stop at 15. We continue to grow and develop throughout our lives and into old age. There are a handful of ways to conduct research on adults and older persons, which will provide you with exceptional information about the process of aging and maturation.

When you want to see how people change over a lifetime, like comparing people who are 20, 40, 60, and 80 years old, you really only have two good options. Longitudinal design is a research study where a sample of the population is studied at intervals to examine the effects of development. To conduct a longitudinal design, we start with 20-year-olds and then check in with them every 20 years to see how they've changed. We'll get more into the advantages and the disadvantages in a little bit.

This seems like a lot of work, although it would give really good information. Another option is cross-sectional design, defined as sampled groups along a developmental path in an experiment to determine how development influences a research variable. Instead of taking one group of people and following them for 60 years, we take 4 groups of people and study them now. Our first group is all 20-year-olds, the second group is 40-year-olds, and so on. This saves us time because we can do all the research now instead of over 60 years.

And because almost every science has someone who cleverly combines things, we have a sequential design, also sometimes referred to as a cross-sequential design, which is defined as a combination of longitudinal and cross-sectional designs, by following several differently aged cohorts over time. With longitudinal, we look at one group over a long time. With cross-sectional, we look at a whole bunch of groups right now. With sequential, we look at a whole bunch of groups over time.

Most importantly of all, we need to have ecological validity, which is defined as the level to which we can apply findings to real-world situations. Meaning, if I say people will always do better on their tests and pay attention to their lessons, but I have to wrap a live electrode around their thumb to keep their attention, then this would be said to have low ecological validity. On the other hand, if I say that more people will watch this lesson if it was read in a British accent, then that would be said to have high ecological validity.


There are some distinct advantages to each type of research, some of which we have already discussed.

With longitudinal designs, we have one main advantage; that is, individual differences are recorded, which means that we can go back later and see if something peculiar is happening in the data. For example, if after our 10-year-long study on aging we found that people with darker skin appeared to age better, then we can go back and examine the exact amounts of melanin in their skin.

Looking at cross-sectional designs, we already discussed the situation with time. That is, instead of doing a study over many years, we can complete a research study in a short amount of time. This means the study resolves faster and can get published faster. In addition to this, there's no follow up. Once the study is complete, the subjects go off on their merry way and never have to come back later. Lastly, the subjects can be picked to be more representative of the population. This allows you to maintain high ecological validity, because your study looks a lot like the population you're interested in studying.

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