Key Takeaways
- A cross-sectional study collects data from a single point in time without changing any variables.
- This type of study is useful in identifying correlations but cannot prove cause and effect.
- Cross-sectional studies are quicker and cheaper than longitudinal studies, but provide only a snapshot of a given time.
A cross-sectional study looks at data at a single point in time. The participants in this type of study are selected based on particular variables. Cross-sectional studies are typically used in developmental psychology, but they are useful in many other areas as well, including social science and education.
Cross-sectional studies are observational and are known as descriptive research, not causal or relational—meaning you can’t use them to determine the cause of something, such as a disease. Researchers record the information that is present in a population, but they do not manipulate variables.
This type of research can be used to describe characteristics that exist in a community, but not to determine cause-and-effect relationships between different variables. This method is often used to make inferences about possible relationships or to gather preliminary data to support further research and experimentation.
Example: Researchers studying developmental psychology might select groups of people who are different ages but investigate them at one point in time. By doing this, any differences among the age groups can be attributed to age differences rather than something that happened over time.
Defining Characteristics of Cross-Sectional Studies
Some of the key characteristics of a cross-sectional study include:
- The study takes place at a single point in time
- It does not involve manipulating variables
- It allows researchers to look at numerous characteristics at once (age, income, gender, etc.)
- It’s often used to look at the prevailing characteristics in a given population
- It can provide information about what is happening in a current population
Verywell / Jessica Olah
Think of a cross-sectional study as a snapshot of a particular group of people at a given point in time. Unlike longitudinal studies, which look at a group of people over an extended period, cross-sectional studies are used to describe what is happening at the present moment.This type of research is frequently used to determine the prevailing characteristics in a population at a certain point in time. For example, a cross-sectional study might be used to determine if exposure to specific risk factors might correlate with particular outcomes.
A researcher might collect cross-sectional data on past smoking habits and current diagnoses of lung cancer, for example. While this type of study cannot demonstrate cause and effect, it can provide a quick look at correlations that may exist at a particular point.
For example, researchers may find that people who reported engaging in certain health behaviors were also more likely to be diagnosed with specific ailments. While a cross-sectional study cannot prove for certain that these behaviors caused the condition, such studies can point to a relationship worth investigating further.
Advantages of Cross-Sectional Studies
Cross-sectional studies are popular because they offer many benefits for researchers.
Inexpensive and Fast
Cross-sectional studies typically allow researchers to collect a great deal of information quickly. Data is often obtained inexpensively using self-report surveys. Researchers are then able to amass large amounts of information from a large pool of participants.
For example, a university might post a short online survey about library usage habits among biology majors, and the responses would be recorded in a database automatically for later analysis. This is a simple, inexpensive way to encourage participation and gather data across a wide swath of individuals who fit certain criteria.
Can Assess Multiple Variables
Researchers can collect data on a few different variables to see how they affect a certain condition. For example, differences in sex, age, educational status, and income might correlate with voting tendencies or give market researchers clues about purchasing habits.
Might Prompt Further Study
Although researchers can’t use cross-sectional studies to determine causal relationships, these studies can provide useful springboards to further research. For example, when looking at a public health issue, such as whether a particular behavior might be linked to a particular illness, researchers might utilize a cross-sectional study to look for clues that can spur further experimental studies.
For example, researchers might be interested in learning how exercise influences cognitive health as people age. They might collect data from different age groups on how much exercise they get and how well they perform on cognitive tests. Conducting such a study can give researchers clues about the types of exercise that might be most beneficial to the elderly and inspire further experimental research on the subject.
Challenges of Cross-Sectional Studies
No method of research is perfect. Cross-sectional studies also have potential drawbacks.
Difficulties in Determining Causal Effects
Researchers can’t always be sure that the conditions a cross-sectional study measures are the result of a particular factor’s influence. In many cases, the differences among individuals could be attributed to variation among the study subjects. In this way, cause-and-effect relationships are more difficult to determine in a cross-sectional study than they are in a longitudinal study. This type of research simply doesn’t allow for conclusions about causation.
For example, a study conducted some 20 years ago queried thousands of women about their consumption of diet soft drinks. The results of the study, published in the medical journal Stroke, associated diet soft drink intake with stroke risk that was greater than that of those who did not consume such beverages. In other words, those who drank lots of diet soda were more prone to strokes. However, correlation does not equal causation. The increased stroke risk might arise from any number of factors that tend to occur among those who drink diet beverages. For example, people who consume sugar-free drinks might be more likely to be overweight or diabetic than those who drink the regular versions. Therefore, they might be at greater risk of stroke—regardless of what they drink.
Cohort Differences
Groups can be affected by cohort differences that arise from the particular experiences of a group of people. For example, individuals born during the same period might witness the same important historical events, but their geographic regions, religious affiliations, political beliefs, and other factors might affect how they perceive such events.
Report Biases
Surveys and questionnaires about certain aspects of people’s lives might not always result in accurate reporting. For example, respondents might not disclose certain behaviors or beliefs out of embarrassment, fear, or other limiting perception. Typically, no mechanism for verifying this information exists.
Cross-Sectional vs. Longitudinal Studies
Cross-sectional research differs from longitudinal studies in several important ways. The key difference is that a cross-sectional study is designed to look at a variable at a particular point in time. A longitudinal study evaluates multiple measures over an extended period to detect trends and changes.
Cross-Sectional Study
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Evaluates variable at single point in time
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Participants less likely to drop out
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Uses new participant(s) with each study
Longitudinal Study
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Measures variable over time
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Requires more resources
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More expensive
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Subject to selective attrition
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Follows same participants over time
Longitudinal studies tend to require more resources; these are often more expensive than those used by cross-sectional studies. They are also more likely to be influenced by what is known as selective attrition, which means that some individuals are more likely to drop out of a study than others. Because a longitudinal study occurs over a span of time, researchers can lose track of subjects. Individuals might lose interest, move to another city, change their minds about participating, etc. This can influence the validity of the study.
One of the advantages of cross-sectional studies is that data is collected all at once, so participants are less likely to quit the study before data is fully collected.
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