Cross-sectional study

A cross-sectional study is a type of research that looks at a sampling of subjects from a particular group to see how many exhibit a particular trait. The study is observational, which means the researchers only look for the trait in which they have an interest and do nothing to alter or change the behavior of the study subjects. Cross-sectional studies are limited to a particular moment in time and do not look backward or forward in gathering information; they do not consider subjects who had the trait in question in the past or who will have it in the future. These studies are useful for studying more than one trait at a time and their results can be applied to a larger group of subjects, which makes them more cost-effective than some other types of studies. However, they only provide a snapshot of the subjects at the time studied and provide no information on causes of the traits in question.

Background

Research studies are undertaken to answer a particular question: someone wants to know something, such as how many people in a town have children younger than twelve, how many people in a state have high blood pressure, or whether more dogs or cats are kept as pets. To do this, researchers establish a hypothesis, or a theory, about what they think is the answer to the question. They then design a study to determine if their hypothesis is correct.

A number of different considerations are involved in designing research studies. The researcher decides what information is needed, then plans a study that will help find that information. The study must be free of bias, meaning it must be designed so that the study does not influence the results. For instance, if the subject of the study is how many healthy honeybees are in North America, it would bias the test to intentionally choose to study only an area where it is known many bees have been killed by insecticides. On the other hand, it would be appropriate to include the bee population in that area in a study of factors that affect the lifespan of bees.

Researchers also need to determine the kind of study that will best provide the information they seek. Some studies use only previously gathered information, such as printed surveys or case studies. Others rely on experimental-type studies done in a laboratory. Others involve human subjects. In some cases, these can be studies known as randomized controlled trials, in which groups of people are given medications or treatments or instructed to make a lifestyle change (such as exercising more or eating certain foods). The groups that make these changes are compared to other groups called control groups that do not make the changes. This helps researchers to see the effects of the changes.

In many instances, the ethics issues involved in conducting tests on living humans makes it necessary to conduct tests that are strictly observational. In these tests, the researchers do not intervene with the behavior or habits of the test subjects in any way. They simply observe what happens.

The two main forms of these types of test are longitudinal studies and cross-sectional studies. In a longitudinal study, researchers observe the test subjects at several intervals to see how things change. For instance, if researchers want to study depression in a group of people who experienced a trauma, the researchers might observe them a month after the event and again at one year, two years, five years, ten years, and fifteen years to evaluate the effect the event had on their lives. Cross-sectional studies, on the other hand, capture just a moment in time; the researchers might observe a group of people six months after a trauma to see how many people were depressed.

Overview

Each type of test has its advantages. One of the main advantages of a cross-sectional study is that the results can easily be applied to a broader group. For instance, if researchers examine one hundred plants and find that ten of them grow red flowers instead of pink, they can estimate that in a group of one thousand plants, one hundred plants will have red flowers.

Cross-sectional studies can also be readily adapted to studying more than one trait at a time, such as how many of those same plants grow taller than one foot. Once researchers choose a group of test subjects, they can simultaneously study many things about the same group. For example, in a study that involves subjects who are childless couples living in a particular city, researchers can simultaneously determine how many use public transportation, recycle, purchase organic foods, and many other specific traits in one study. This makes cross-sectional studies very economical and cost-effective to conduct. They can also provide a great deal of information about the test subjects that can help researchers form a picture of the combined traits of certain subgroups of the test subjects. For instance, they may discover many of the couples who use public transportation also are more likely to purchase organic foods.

Cross-sectional studies provide a snapshot of how the subjects are when studied. While this is not a problem in many circumstances, it does not allow researchers to make any observations related to causality, or whether certain traits that are observed cause other traits. This is because no information is gathered from before the moment of the study and no follow-up is conducted. For instance, in the example of the childless city dwellers, the researchers do not know if some of the people who use public transportation owned vehicles shortly before the study or if some bought cars the next week.

In many types of studies this is not an issue. However, in studies involving health questions, researchers are often helped by having more context and follow-up on the test subjects. For example, a cross-sectional study on a population of people who work out at a gym might reveal that a small percentage has high cholesterol. A longitudinal study on the same group might show that a number had high cholesterol before they started working out regularly, and that some saw a return of high cholesterol when they stopped working out. This allows the researchers to theorize that exercise helps lower cholesterol levels, something the cross-sectional study cannot do.

Bibliography

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"Quantitative Study Designs: Cross-Sectional Study." Deakin University, 14 Oct. 2024, deakin.libguides.com/quantitative-study-designs/cross-sectional. Accessed 6 Jan. 2025.

Sedgwick, Philip. "Cross Sectional Studies: Advantages and Disadvantages." British Medical Journal, 26 Mar. 2014, www.bmj.com/content/348/bmj.g2276. Accessed 28 Apr. 2017.

"Types of Study Designs." Georgia State University, research.library.gsu.edu/c.php?g=115595&p=755213. Accessed 28 Apr. 2017.

"What Researchers Mean by Cross Sectional vs. Longitudinal Studies." Institute for Work and Health, www.iwh.on.ca/wrmb/cross-sectional-vs-longitudinal-studies. Accessed 28 Apr. 2017.