What is a likely explanation for the results from cross sectional studies showing

A cross-sectional study is a type of research design in which you collect data from many different individuals at a single point in time. In cross-sectional research, you observe variables without influencing them.

Researchers in economics, psychology, medicine, epidemiology, and the other social sciences all make use of cross-sectional studies in their work. For example, epidemiologists who are interested in the current prevalence of a disease in a certain subset of the population might use a cross-sectional design to gather and analyze the relevant data.

Cross-sectional vs longitudinal studies

The opposite of a cross-sectional study is a longitudinal study. While cross-sectional studies collect data from many subjects at a single point in time, longitudinal studies collect data repeatedly from the same subjects over time, often focusing on a smaller group of individuals that are connected by a common trait.

Both types are useful for answering different kinds of research questions. A cross-sectional study is a cheap and easy way to gather initial data and identify correlations that can then be investigated further in a longitudinal study.

You then decide to design a longitudinal study to further examine this link in younger patients. Without first conducting the cross-sectional study, you would not have known to focus on younger patients in particular.

When to use a cross-sectional design

When you want to examine the prevalence of some outcome at a certain moment in time, a cross-sectional study is the best choice.

Sometimes a cross-sectional study is the best choice for practical reasons – for instance, if you only have the time or money to collect cross-sectional data, or if the only data you can find to answer your research question was gathered at a single point in time.

As cross-sectional studies are cheaper and less time-consuming than many other types of study, they allow you to easily collect data that can be used as a basis for further research.

Descriptive vs analytical studies

Cross-sectional studies can be used for both analytical and descriptive purposes:

• An analytical study tries to answer how or why a certain outcome might occur.
• A descriptive study only summarizes said outcome using descriptive statistics.

How to perform a cross-sectional study

To implement a cross-sectional study, you can rely on data assembled by another source or collect your own. Governments often make cross-sectional datasets freely available online.

Prominent examples include the censuses of several countries like the US or France, which survey a cross-sectional snapshot of the country’s residents on important measures. International organizations like the World Health Organization or the World Bank also provide access to cross-sectional datasets on their websites.

However, these datasets are often aggregated to a regional level, which may prevent the investigation of certain research questions. You will also be restricted to whichever variables the original researchers decided to study.

If you want to choose the variables in your study and analyze your data on an individual level, you can collect your own data using research methods such as surveys. It’s important to carefully design your questions and choose your sample.

Advantages and disadvantages of cross-sectional studies

Like any research design, cross-sectional studies have various benefits and drawbacks.

Advantages

• Because you only collect data at a single point in time, cross-sectional studies are relatively cheap and less time-consuming than other types of research.
• Cross-sectional studies allow you to collect data from a large pool of subjects and compare differences between groups.
• Cross-sectional studies capture a specific moment in time. National censuses, for instance, provide a snapshot of conditions in that country at that time.

Disadvantages

• It is difficult to establish cause-and-effect relationships using cross-sectional studies, since they only represent a one-time measurement of both the alleged cause and effect.
• Since cross-sectional studies only study a single moment in time, they cannot be used to analyze behavior over a period of time or establish long-term trends.
• The timing of the cross-sectional snapshot may be unrepresentative of behavior of the group as a whole. For instance, imagine you are looking at the impact of psychotherapy on an illness like depression. If the depressed individuals in your sample began therapy shortly before the data collection, then it might appear that therapy causes depression even if it is effective in the long term.

Frequently asked questions about cross-sectional studies

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Thomas, L. (2022, July 21). Cross-Sectional Study | Definition, Uses & Examples. Scribbr. Retrieved November 25, 2022, from https://www.scribbr.com/methodology/cross-sectional-study/