What is a Cross-Sectional Study – Definition with Examples
A cross-sectional study is defined as an observational research type that analyzes data of variables collected at one given point of time across a sample population. population or a pre-defined subset. This study type is also known as cross-sectional analysis, transverse study or prevalence study.
The data collected in a cross-sectional study is from people who are similar in all variables except the one variable which is under study. This variable remains constant throughout the cross-sectional study. This is unlike a longitudinal study, where variables in the study can change over the course of research.
Cross-sectional studies are conducted across multiple industries like:
- Retail – In retail, a cross-sectional study can be conducted on males and females between the ages 24-35 to check for spending or purchase trend differences between the sexes.
- Business – In business, a cross-sectional study can be conducted to understand how people of different socio-economic status from one geographical segment respond to one change in an offering.
- Healthcare – A cross-sectional study in healthcare is used to understand how prone kids between the age of 2-12 across different boroughs in the US are prone to a low calcium deficiency.
- Education – A cross-sectional study in education is particularly helpful to understand how either males or females from a similar age bracket but different ethnicities react to their grasp of a certain object.
Cross-sectional research helps garner a lot of quick actionable data that helps in decision making and offering products or services.
Types of cross-sectional studies
A cross-sectional study may be entirely descriptive and it used to assess the frequency and distribution of the study topic in a certain demographic. For example, how a random sample of Universities across a state is assessed to check for obesity amongst women and women.
This type of cross-sectional study is used to investigate the association between two related or unrelated parameters. This methodology isn’t entirely full proof though because the presence of risk factors and outcomes are simultaneous and their studies are simultaneous too. For example, to validate if coal workers in the mine could develop bronchitis only looks at the factors in the mine. What it doesn’t account for is that bronchitis could be inherent or may have existed from before.
In a real-life cross-sectional study, attributes from both types are used.
Defining variables of Cross-Sectional Studies
Some of the key variables of a cross-sectional study are:
- The cross-sectional study is conducted with the same set of variables over a certain period of time. The study is conducted in a single instance, unlike longitudinal studies, where variables can change over the period of extensive research.
- Cross-sectional studies give the flexibility to the researcher to look at multiple variables together as a constant, with only one variable being the focus of the cross-sectional study.
The easiest way to encapsulate a cross-sectional study is that it is a snapshot of a group of people at that point in time. They are used to determine what is happening in real time, at the moment. Hence, this research type is used to draw the pulse of the population data at any given point in time.
You can also use it 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
You’ve now understood what parameters encompass the cross-sectional research method. To better illustrate this, below are 2 examples:
- Phone companies rely on advanced and innovative features to drive sales. Research amongst the target demographic market by a phone manufacturer validates the expected adoption rate and potential sales of the phone. In a cross-sectional study, males and females across geographies and ages 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 for women.
- Another example of a cross-sectional study would be a medical study looking at the prevalence of cancer amongst a certain population. The researcher can evaluate people from different ages, ethnicities, geographical location and social backgrounds. If a significant amount of men from a particular age are found to be more prone to have the disease, the researcher can conduct further studies to understand the reason behind it – like a longitudinal study.
Learn more: Social Research
Analysis of cross-sectional studies
In a cross-sectional study, to calculate prevalence, multiple parameters are measured simultaneously – questions, observations, and answers.
Prevalence = No of cases at a given time / No of people at the same given time
For continuous variables, they fall along a continuum within a given range. To calculate prevalence, the values have to be below or above a predetermined level or else median levels may be calculated.
Cross-Sectional Studies Advantages and Disadvantages
Here are some of the key advantages and disadvantages of conducting online research using cross-sectional study.
Advantages of cross-sectional studies
- Relatively quick to conduct
- All variables are collected at one go
- Multiple outcomes can be researched at once
- Prevalence for all factors can be measured
- Good 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 exact same variables
- Associations are tough to interpret
- When strong feelings are involved, there could be the case of a bias
- Does not help to determine cause
Cross-Sectional vs. Longitudinal Studies
Even though they are both quantitative research methods, there are a few differences between cross-sectional studies vs longitudinal studies.
In cross-sectional studies, the variables are collected at a certain given point of time but longitudinal studies span across multiple sessions and the variables could change.
Cross-sectional studies are preferred to find common points between variables but longitudinal studies, due to their nature are then used to dissect the research from the cross-sectional study even further.
Create & Analyze Cross-sectional study Survey
The other factor is that due to the longevity of the research, there could be attrition in the longitudinal study which skews the results finding and the corresponding research whereas, in cross-sectional research, there’s no chance of that happening because the study is done with the same variables and sometimes at the same time of collection of variables.
Learn more: Cross-Sectional vs Longitudinal Studies