Which research method involves collecting data repeatedly on the same person as he or she ages?

Study design depends greatly on the nature of the research question. In other words, knowing what kind of information the study should collect is a first step in determining how the study will be carried out (also known as the methodology).

Let’s say we want to investigate the relationship between daily walking and cholesterol levels in the body. One of the first things we’d have to determine is the type of study that will tell us the most about that relationship. Do we want to compare cholesterol levels among different populations of walkers and non-walkers at the same point in time? Or, do we want to measure cholesterol levels in a single population of daily walkers over an extended period of time?

The first approach is typical of a cross-sectional study. The second requires a longitudinal study. To make our choice, we need to know more about the benefits and purpose of each study type.

Cross-sectional study

Both the cross-sectional and the longitudinal studies are observational studies. This means that researchers record information about their subjects without manipulating the study environment. In our study, we would simply measure the cholesterol levels of daily walkers and non-walkers along with any other characteristics that might be of interest to us. We would not influence non-walkers to take up that activity, or advise daily walkers to modify their behaviour. In short, we’d try not to interfere.

The defining feature of a cross-sectional study is that it can compare different population groups at a single point in time. Think of it in terms of taking a snapshot. Findings are drawn from whatever fits into the frame.

To return to our example, we might choose to measure cholesterol levels in daily walkers across two age groups, over 40 and under 40, and compare these to cholesterol levels among non-walkers in the same age groups. We might even create subgroups for gender. However, we would not consider past or future cholesterol levels, for these would fall outside the frame. We would look only at cholesterol levels at one point in time.

The benefit of a cross-sectional study design is that it allows researchers to compare many different variables at the same time. We could, for example, look at age, gender, income and educational level in relation to walking and cholesterol levels, with little or no additional cost.

However, cross-sectional studies may not provide definite information about cause-and-effect relationships. This is because such studies offer a snapshot of a single moment in time; they do not consider what happens before or after the snapshot is taken. Therefore, we can’t know for sure if our daily walkers had low cholesterol levels before taking up their exercise regimes, or if the behaviour of daily walking helped to reduce cholesterol levels that previously were high.

Longitudinal study

A longitudinal study, like a cross-sectional one, is observational. So, once again, researchers do not interfere with their subjects. However, in a longitudinal study, researchers conduct several observations of the same subjects over a period of time, sometimes lasting many years.

The benefit of a longitudinal study is that researchers are able to detect developments or changes in the characteristics of the target population at both the group and the individual level. The key here is that longitudinal studies extend beyond a single moment in time. As a result, they can establish sequences of events.

To return to our example, we might choose to look at the change in cholesterol levels among women over 40 who walk daily for a period of 20 years. The longitudinal study design would account for cholesterol levels at the onset of a walking regime and as the walking behaviour continued over time. Therefore, a longitudinal study is more likely to suggest cause-and-effect relationships than a cross-sectional study by virtue of its scope.

In general, the research should drive the design. But sometimes, the progression of the research helps determine which design is most appropriate. Cross-sectional studies can be done more quickly than longitudinal studies. That’s why researchers might start with a cross-sectional study to first establish whether there are links or associations between certain variables. Then they would set up a longitudinal study to study cause and effect.

Source: At Work, Issue 81, Summer 2015: Institute for Work & Health, Toronto

This column updates a previous column describing the same term, originally published in 2009.

A longitudinal study is a type of correlational research study that involves looking at variables over an extended period of time. This research can take place over a period of weeks, months, or even years. In some cases, longitudinal studies can last several decades.

Longitudinal design is used to discover relationships between variables that are not related to various background variables. This observational research technique involves studying the same group of individuals over an extended period.

Data is first collected at the outset of the study, and may then be repeatedly gathered throughout the length of the study. Doing this allows researchers to observe how variables change over time.

For example, imagine that a group of researchers is interested in studying how exercise during middle age could affect cognitive health as people age. The researchers hypothesize that people who are more physically fit in their 40s and 50s will be less likely to experience cognitive declines in their 70s and 80s.

To test this hypothesis, the researchers recruit a group of participants who are in their mid-40s to early 50s. They collect data related to how physically fit the participants are, how often they work out, and how well they do on cognitive performance tests. Periodically over the course of the study, the researchers collect the same types of data from the participants to track activity levels and mental performance.

Longitudinal studies are usually observational in nature, and are a type of correlational research. Longitudinal research is often contrasted with cross-sectional research. While longitudinal research involves collecting data over an extended period of time, cross-sectional research involves collecting data at a single point in time.

One of the earliest examples of a longitudinal analysis occurred during the 17th century in what is now Canada, when King Louis XIV gathered information from his population—including age, marital status, occupation, as well as livestock and land owned. He collected this information periodically to understand the health and economic viability of his colonies.

The oldest recorded longitudinal study on growth was conducted in the 18th century by Count Philibert Gueneau de Montbeillard. He measured his son every six months and published the information in the encyclopedia "Histoire Naturelle."

The Genetic Studies of Genius (also known as the Terman Study of the Gifted), which began in 1921, is known as one of the first studies to begin during the childhood of the participants and continue into their adulthood. Psychologist Lewis Terman's goal was to examine the similarities among gifted children and disprove the common assumption at the time, which was that gifted children were "socially inept."

There are three major types of longitudinal studies:

• Panel study: Sampling of a cross-section of individuals
• Cohort study: Selecting a group based on a specific event, such as birth, geographic location, or historical experience
• Retrospective study: Reviewing historical information such as medical records

A longitudinal study can provide unique insight that might not be possible any other way. This method allows researchers to look at changes over time.

Because of this, longitudinal methods are particularly useful when studying development and lifespan issues. Researchers can look at how certain things may change at different points in life and explore some of the reasons why these developmental shifts take place.

For example, consider longitudinal studies that looked at how identical twins reared together versus those reared apart differ on a variety of variables. In these types of studies, researchers tracked participants from childhood into adulthood to look at how growing up in a different environment influences personality, achievement, and other areas.

Since the participants share the same genetics, it is assumed that any differences are due to environmental factors. Researchers can then look at what the participants have in common and where they differ to see which characteristics are more strongly influenced by either genetics or experience. Note that adoption agencies no longer separate twins, so such studies are unlikely today. Longitudinal studies on twins have shifted to those within the same household.

Some longitudinal studies take place over a period of years (or even decades). Researchers can use their data to establish a sequence of events when looking at the aging process.

As with other types of psychology research, longitudinal studies have strengths and weaknesses. There are some important advantages to conducting longitudinal research, but there are also a number of challenges that need to be considered.

Longitudinal studies require enormous amounts of time and are often quite expensive. Because of this, these studies often have only a small group of subjects, which makes it difficult to apply the results to a larger population.

Another problem is that participants sometimes drop out of the study, shrinking the sample size and decreasing the amount of data collected. This tendency is known as selective attrition. Participants might drop out for a number of reasons, like moving away from the area, illness, or simply losing the motivation to participate.

In some cases, this can influence the results of the longitudinal study. If the final group no longer reflects the original representative sample, attrition can threaten the validity of the experiment.

Validity refers to whether or not a test or experiment accurately measures what it claims to measure. If the final group of participants is not a representative sample, it is difficult to generalize the results to the rest of the population.

Even before the Terman Study ended, psychologists criticized Terman for his work. Terman, a proponent of eugenics, is seen today as letting his own sexism, racism, and economic prejudice influence his study. He is also viewed as drawing major conclusions from weak evidence.

However, Terman's study continues to be influential in longitudinal studies. For instance, a recent study found new information on the original Terman sample, which was that men who had skipped a grade as children, on average, went on to have higher incomes than those who didn't skip a grade.

A longitudinal study can provide a wealth of information on a topic. While such studies can be expensive and difficult to carry out, the information obtained from such research can be very valuable. Longitudinal studies from the past continue to influence and inspire researchers and students of psychology today.

Frequently Asked Questions

• What is the difference between a longitudinal study and a cross-sectional study?

  A longitudinal study follows up with the same sample (i.e., group of people) over time, whereas a cross-sectional study examines one sample at one point in time.

• How long is a longitudinal study?

  There is no set time for how long a longitudinal study should be. It can range from a few weeks to a few decades or even longer.

• How many participants do you need for a longitudinal study?

  There is no set number of participants needed for a longitudinal study. However, a researcher needs at least one participant, of course, to be able to measure data over time. But a larger group provides more information.