The meaning, types and examples of a cross-sectional study

By Indeed Editorial Team

Published 15 June 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Business owners and marketing professionals use cross-sectional studies to understand customers' preferences. Companies use this research to help them market their products to the right consumers. Understanding what a cross-sectional study is can help you gain useful market insight and save time and money. In this article, we explain what a cross-sectional study is, explore its characteristics, types and benefits, compare it with other research methods and share some examples.

What is a cross-sectional study?

A cross-sectional study is an observational research tool you can use to gather data from a group of people during a particular period and analyse it. The participants of this research method usually have varying characteristics and demographics, known as variables. Examples of variables include age, location, gender, ethnicity and school. The types you use depend on the research and the results you hope to achieve. This method also goes by the names of prevalence study, cross-sectional analysis or transverse study.

Related: 10 common types of variables in research and statistics

Characteristics of a transverse study

The following are characteristics of a cross-sectional analysis:

The study is a single event

This research tool involves gathering data in a single period and associating information with that point in time . Therefore, the results provide information about one specific timeframe. For instance, if a restaurant owner conducts a customer poll on Thursday and another on Saturday, they might identify that food preferences vary on the two days because of how the data aligns with each event.

It provides information on population patterns

This research method accesses the qualities and traits of a group at that time. You can gather multiple pieces of data, which provide useful information about your target market. It also informs you about rare occurrences. For instance, an ice cream shop owner could conduct regular surveys to understand flavour preferences and how they change.

It's observational

Cross-sectional studies are different from experimental research methods, which involves creating a specific environment and adjusting factors to determine an outcome. With a transverse study, you're able to avoid manipulating variables, which can happen when assigning different cohorts to different study groups. Here, using observation to gain current information about one group is the primary goal.

There is no manipulation of variables

As a researcher, you handle the designing and construction tools that you use for data collection. When doing this for a cross-sectional analysis, you avoid manipulating variables or the study environment. For instance, when studying the difference in debit card privacy concerns between people who shop in malls and those that shop online, you can avoid interfering with either group and changing their patterns. This results in more authentic data.

Related: What is a biased sample? (Examples and tips to avoid it)

It allows researchers to observe multiple variables simultaneously

You can assess variables like age, location, gender and income at the same time. This characteristic is important if you wish to examine the relationship between multiple variables. This research method provides information on each variable you choose to study, which you can then compare.

Types of cross-sectional studies

When you perform this type of study, you can use descriptive or analytical research. Below are the definitions of these different types of transverse study:

Analytical research

This research method examines the relationship between two related or unrelated parameters. A challenge with this method is that it doesn't consider external variables. For instance, when researching if working in mines increases mining engineers' chances of developing cancer, this approach doesn't consider that some engineers might have already had a pre-existing lung condition. Some medical reports have established that working in mines could affect your lungs, but it's better to avoid letting this information create bias.

Related: How to analyse data: definition, steps, benefits and skills

Descriptive research

This type of research investigates how frequently, severely or widely, a variable occurs throughout a specific set. For example, you can observe the spending trends of people in an age range. You could also use this type of study to develop products and services for people.

Related: What are the different types of research methodology?

When can you use a transverse study?

It's important to understand when it's best to use a certain research method. You could use the cross-sectional study method to assess the prevalence of outcomes at a particular time. For instance, you could ascertain how many families in a city are on a low income so that you can estimate the cost of running a free lunch programme in schools. A cross-sectional analysis could provide you with all the data you need in this situation.

Benefits of this study method

These are some of the benefits of using the cross-sectional method to conduct research:

  • quick to plan and conduct

  • helpful for creating new theories

  • allows access to all variables at once

  • suitable for descriptive analysis

  • provides valid data for various types of research

  • enables researchers to assess multiple outcomes at once

  • proves or or disproves assumptions

  • cheap and time effective

  • generates time-specific data

Differences between cross-sectional and longitudinal studies

Below are a few differences between these two research methods:

  • The cross-sectional analysis uses variables at a specific point in time. In longitudinal studies, you can measure variables over an extended period.

  • In transverse studies, you can examine multiple variables simultaneously, while longitudinal studies only examine one at a time.

  • Transverse studies cannot explain cause-and-effect relationships, while longitudinal studies can justify this relationship.

  • Transverse studies are cheaper and less time-consuming than longitudinal studies.

Longitudinal studies are prone to selective attrition. Also, some individuals may leave a study earlier than others. This can affect the validity of the study, as a longitudinal study could last a number of years and require researchers to revisit the variables at regular intervals.

Examples of when to use transverse study

A transverse study is the best option to help provide practical solutions in some situations. Here are some examples of effective uses of transverse studies:

Medical research

This is an example of how to effectively apply transverse studies in the medical sector. You could conduct a medical study to examine the prevalence of cancer in a particular group of people. You can evaluate people of different social backgrounds, ethnicities, ages and geographical locations. If a significant number of people in that age group are more prone to contracting cancer, you may then conduct further research to discover the reasons behind it.

Technology research

Manufacturers regularly produce innovative phones and rely on advanced features to increase sales. Researchers can conduct studies to discover the potential adoption rate and sales numbers of a new piece of technology. They may study the phone use of younger people of different genders and age ranges. If the results show that many young people avoid buying heavy phones, the designers could adjust the design of their next phone to ensure it's lightweight. They could also produce sleeker phones so their customers remain loyal to their brand.

Educational research

Many factors can contribute to how well a student performs in school. The income level of a student's parents is one example of a variable that may influence their academic outcomes. Researchers could conduct a study to determine the academic performance of various students whose parents have different levels of income. In this study, the researcher can collect data from the parents and correlate it with their children's performance. The results may show that parents' incomes influence their children's results at school. If this is the case, the school can use this information to tailor its approaches to student performance and behaviour management.

Hospital research

You could study the rate at which hospital facilities manage blood pressure conditions. Conducting a medical study can collect the data for this research. You might compare the number of patients with blood pressure to the total number of patients that the hospital treats over a specific period. If the study reveals that most of the ailments the hospital treats are blood pressure conditions, you can further analyse what causes the high prevalence of blood pressure issues. This information can then be useful in advising patients on how to avoid potential risk factors.

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