What (Exactly) Is A Cross-Sectional Study?
A Plain-Language Explanation & Definition (With Examples)
By: Derek Jansen (MBA) | June 2020
If you’ve just started out on your dissertation, thesis or research project and it’s your first time carrying out formal research, you’ve probably encountered the terms “cross-sectional study” and “cross-sectional research” and are wondering what exactly they mean. In this post, we’ll explain exactly:
What (exactly) is a cross-sectional study?
A cross-sectional study (also referred to as cross-sectional research) is simply a study in which data are collected at one point in time. In other words, data are collected on a snapshot basis, as opposed to collecting data at multiple points in time (for example, once a week, once a month, etc) and assessing how it changes over time.
The opposite of a cross-sectional study is a longitudinal study. In a longitudinal study, data are collected at multiple points in time and the objective is to assess how the data change over that time period.
Here’s an example of what this looks like in practice:
Cross-sectional study: a study which assesses a group of people’s attitudes and feelings towards a newly elected president, directly after the election happened.
Longitudinal study: a study which assesses how people’s attitudes towards the president changed over a period of 3 years after the president is elected, assessing sentiment every 6 months.
As you can probably see, while both these studies are analysing the same topic (people’s sentiment towards the president), they each have a different focus. The cross-sectional study is interested in what people are feeling and thinking “right now”, whereas the longitudinal study is interested in not just what people are feeling and thinking, but how those thoughts and feelings change over time.
What are the advantages of a cross-sectional study?
There are many advantages to taking a cross-sectional approach, which makes it the more popular option for dissertations and theses. Some main advantages are:
- Speed – given the nature of a cross-sectional study, you can complete your research relatively quickly, as information only needs to be gathered once.
- Cost – because information only needs to be collected once, the cost is lower than a longitudinal approach.
- Control – because the data are only collected at one point in time, you have a lot more control over the measurement process (i.e. you don’t need to worry about measurement instruments changing over a period of years).
- Flexibility – using a cross-sectional approach, you can measure multiple factors at once. Your study can be descriptive (assessing the prevalence of something), analytical (assessing the relationship between two or more things) or both.
What are the disadvantages of
a cross-sectional study?
While the cross-sectional approach to research has many advantages, it (naturally) has its limitations and disadvantages too. Some of the main disadvantages are:
- Static – cross-sectional studies cannot establish any sequence of events, as they only assess data with a snapshot view.
- Causality – because cross-sectional studies look at data at a single point in time (no sequence of events), it’s sometimes difficult to understand which way causality flows – for example, does A cause B, or does B cause A? Without knowing whether A or B came first, it’s not always easy to tell which causes which.
- Sensitivity to timing – the exact time at which data are collected can have a large impact on the results, and therefore the findings of the study may not be representative.
Should I use a cross-sectional study
or longitudinal study design?
It depends… Your decision to use a cross-sectional or longitudinal approach needs to be informed by your overall research aims, objectives and research questions. As with most research design choices, the research aims will heavily influence your approach.
For example, if your research objective is to get a snapshot view of something, then a cross-sectional approach should work well for you. However, if your research aim is to understand how something has changed over time, a longitudinal approach might be more appropriate.
If you’re trying to make this decision for a dissertation or thesis, you also need to consider the practical limitations such as time and access to data. Chances are, you won’t have the luxury of conducting your research over a period of a few years, so you might be “forced” into a cross-sectional approach due to time restrictions.