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Understanding the Time Dimension in Research

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  • 0:07 Time
  • 1:25 Cross-Sectional Design
  • 3:25 Longitudinal Studies
  • 5:09 Case Study
  • 7:09 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.

Something few researchers consider is how the passage of time may affect some research studies. This lesson explores a few different types of studies and how a researcher has to take the dimension of time into consideration when planning the whole experiment.

Time

Nothing is constant. It would be really nice to freeze everything following a major event and then deal with each change one at a time. There is even a phrase in Latin, ceteris paribus, which means 'all things held constant.'

Unfortunately, you can't really hold everything at a standstill while you focus on one thing. Real life and real experiments have to happen in real time. Sorry for the repetition, but it is kind of what this lesson is all about. What does this mean specifically when you're doing research? It means that time is not standing still. It means that all the distractions and issues that happen in the real world are happening to your participants.

For instance, if you need to look at how some participants change over time, you need to be aware that some of your participants may die. It's not pretty, but it's possible. Other times huge events can occur, like terrorist attacks or national tragedies, that can distract people so much your results will be skewed.

In this lesson, we will discuss how time affects three particular types of research designs: cross-sectional, longitudinal and case studies.

Cross-Sectional Design

Before we get into the nitty-gritty, cross-sectional designs use sampled groups along a developmental path in an experiment to determine how development influences a dependent variable. This is where you're interested in how something changes as it develops, and typically this means taking children and adolescents of different ages and testing to see how they're different.

Maybe you think age has something to do with increased anger control, or maybe you think age is irrelevant in mathematical abilities. You could use a cross-sectional study to address these questions.

Time comes into play here in how it affects your participants over the course of their lives. Since cross-sectional studies examine samples along a continuum, the individual's experience up until that point can be very different.

For example, if you look at the life events of people who are:

  • 100 years old: World War II and the Great Depression may play a strong part in their lives
  • 75 years old: May be impacted by Sputnik and the Space Race
  • 50 years old: May have been shaped by the end of the USSR
  • 25 years old: Have computers which will likely factor into their development

While the oldest have experienced all of these events, the youngest didn't experience the earlier ones. Equally important, the older individuals did not experience the more recent events in the same way as the younger generations. There are kids now who have never known the world without computers! The passage of time has brought about many new events and each generation experiences these events differently.

So how do you account for this? Typically, age difference is an understood phenomenon and a limitation of the cross-sectional design. Generations of people aren't the same.

Longitudinal Studies

A quick definition of a longitudinal design is a research study where a sample of the population is studied at intervals to examine the effects of development. This means you have a sample of the population and you study them periodically throughout their lives. After your tests, you release them back into their natural habitat and then a few weeks, months or years later, you call them up and test them again to see if there are any differences. Sometimes you can call them back two, three or more times.

As time passes, people develop and change, and your entire study is based on those changes. Without the time aspect in this study, you wouldn't really have a longitudinal design; you would just have a regular experiment.

In a longitudinal design, you are focusing on the development as time passes. You need to report and focus on how much time has elapsed between specific experiments because this can become an important area later in your discussion. For example, if you checked every five years on developing children, then a lot can happen between each check-in. With adults, while a lot happens in five years, you don't see the dramatic developments you do with kids. So, to account for time in your longitudinal design, you want to:

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