A cross-sectional study is a type of observational research that analyzes data of variables collected at one given point in time across a sample population or a pre-defined subset. This study type is also known as cross-sectional analysis, transverse study, or prevalence study. Although cross-sectional research does not involve conducting experiments, it is often used to understand outcomes in the physical and social sciences, as well as many business industries.
Now that you know the definition of cross-sectional research, you’re ready to perform your own study, right? No, this non-experimental type of study can be quite complex, but we’ve got you covered.
In this article, we discuss what a cross-sectional study is and is not. We’ll review cross-sectional study examples, explain the types of cross-sectional research you might perform, and take a closer look at the benefits that make this research useful for the work you do.
Defining characteristics of cross-sectional studies
Some of the key attributes of a cross-sectional study are:
- The cross-sectional study is conducted with the same set of variables over a set period of time.
- Similar research may look at the same variable of interest, but each study observes a new set of subjects.
- Cross-sectional research assesses subjects during a single instance with a defined start and stopping point, unlike longitudinal studies, where variables can change during extensive research.
- Cross-sectional studies provide the researcher with the flexibility to look at one independent variable as the focus of the cross-sectional study and one or more dependent variables.
Want a fitting metaphor for a cross-sectional study? Think of a snapshot of a group of people at one event, say a family reunion. The people in that extended family are used to determine what is happening in real–time, at the moment. All of the people have at least one variable in common – being related – and multiple variables that they do not share. From that starting point, you could make all kinds of observations and analyses. Hence, this research type “takes the pulse” of population data at any given point in time.
You can also use this type of research to map prevailing variables that exist at a particular point. For example, cross-sectional data on past drinking habits and a current diagnosis of liver failure.
Cross-sectional study examples
The data collected in a cross-sectional study involves subjects or participants who are similar in all variables – except the one which is under study. This variable remains constant throughout the cross-sectional study. This is unlike a longitudinal study, where variables can change throughout the research. Consider these examples for more clarity:
- Retail: In retail, cross-sectional research can be conducted on men and women in a specific age range to reveal similarities and differences in spending trends related to gender.
- Business: In business, a cross-sectional study can be conducted to understand how people of different socio-economic status from one geographic segment respond to one change in an offering.
- Healthcare: Scientists in healthcare may use cross-sectional research to understand how children ages 2-12 across the United States are prone to calcium deficiency.
- Education: A cross-sectional study in education is particularly helpful in understanding how students who scored within a particular grade range in the same preliminary courses perform with a new curriculum.
- Psychology: The cross-sectional study definition in psychology is research that involves different groups of people who do not share the same variable of interest (like the variable you’re focusing on), but who do share other relevant variables. These could include age range, gender identity, socio-economic status, and so on.
Cross-sectional research allows scholars and strategists to quickly collect actionable data that helps in decision–making and offering products or services.
Types of cross-sectional studies
When you conduct a cross-sectional research study, you will engage in one or both types of research: descriptive or analytical. Read their descriptions to see how they might apply to your work.
A cross-sectional study may be entirely descriptive. A descriptive cross-sectional study assesses how frequently, widely, or severely the variable of interest occurs throughout a specific demographic. Think of the retail example we mentioned above. In that cross-sectional study example, researchers make focused observations to identify spending trends. They might use those findings for developing products and services and marketing existing offerings. They aren’t necessarily looking at why these gendered trends occur in the first place.
Analytical cross-sectional research investigates the association between two related or unrelated parameters. This methodology isn’t entirely foolproof, though, because the presence of outside variables and outcomes are simultaneous, and their studies are, too. For example, to validate whether coal miners could develop bronchitis looks only at the variables in a mine. What it doesn’t account for is that a predisposition to bronchitis could be hereditary or this health condition could be present in the coal workers before their employment in the mine. Yes, other medical research has shown that coal mining is detrimental to lungs, but you don’t want those assumptions to bias your current study.
In a real-life cross-sectional study, researchers usually use both descriptive and analytical research methods.
More cross-sectional study examples
Now that you have a better understanding of what cross-sectional research is and the methods you can use to perform your own studies, let’s take a look at two examples in more detail:
Cross-sectional study example 1: Gender and phone sales
Phone companies rely on advanced and innovative features to drive sales. Research by a phone manufacturer throughout the target demographic market validates the expected adoption rate and potential sales of the phone. In a cross-sectional study, men and women across regions and age ranges are enrolled for this research. If the study results show that Asian women would not buy the phone because it is bulky, the mobile phone company can tweak the design before its launch or develop and market a smaller phone to appeal to a more inclusive group of women.
Cross-sectional study example 2: Men and cancer
Another example of a cross-sectional study would be a medical study looking at the prevalence of cancer amongst a defined population. The researcher can evaluate people of different ages, ethnicities, geographical locations, and social backgrounds. If a significant number of men from a particular age group are more prone to have the disease, the researcher can conduct further studies to understand the reasons behind it – like a longitudinal study, which would study the same participants over time.
Learn more about various kinds of social research to plan similar studies.
Cross-sectional studies advantages and disadvantages
Are you curious about whether cross-sectional research is the right approach for your next study? Surveys are an efficient and revealing way to gather data. Check out some of the key advantages and disadvantages of conducting online research using a cross-sectional study and see if it’s a good fit for your needs.
Advantages of cross-sectional studies
- Relatively quick to conduct.
- All variables are collected at one time.
- Multiple outcomes can be researched at once.
- Prevalence for all factors can be measured.
- Suitable for descriptive analysis.
- Can be used as a springboard for further research.
Disadvantages of cross-sectional studies
- Cannot be used to get timeline-based research.
- Tough to find people that fall under the same variables.
- Associations can be difficult to interpret.
- Is open to bias.
- Does not help to determine cause.
If you are looking for an approach that studies subjects and variables over time, you might prefer a longitudinal study. Additionally, you could follow your cross-sectional research with a longitudinal study. It is easy to confuse the two research methods, so we’ve broken it down here:
Cross-sectional vs. longitudinal studies
Even though they are both quantitative research methods, there are a few differences when we compare and contrast cross-sectional studies vs. longitudinal studies.
In cross-sectional studies, the variables are collected at a particular point in time. Longitudinal studies span multiple sessions, and the variables could change.
Cross-sectional studies are preferred to find common points between variables. Still, longitudinal studies, due to their nature, are used to dissect the research from the cross-sectional study even further.
Learn more about cross-sectional vs. longitudinal studies.
Create and analyze a cross-sectional study survey
It’s your turn! Whether you’re building a marketing strategy or performing a cutting edge medical study, you can get started by creating an intuitive survey from QuestionPro. Choose from one of our 350+ survey templates, or build your own and leverage our reporting tools to discover deep insights to apply to your best work.