A cross-sectional study involves the review of information from a population demographic at a specific point in time. The participants who get involved with this research are selected based on particular variables that researchers want to study. It is often used in developmental psychology, but this method is also useful in several other areas. Social sciences and educational processes benefit from this work.
Researchers who are following cross-sectional study techniques would study select groups of people in different age demographics. Their work would look at one investigatory point at a time. By taking this approach, any differences that exist between the demographics would be attributed to characteristics instead of something that happens.
These studies are observational in nature. They are sometimes described as descriptive research, but not causal or relational. That means researchers are unable to determine the cause of something, such as an illness, when using this method.
Several advantages and disadvantages are worth considering when looking at cross-sectional studies.
List of the Advantages of Cross-Sectional Studies
1. This study takes place during a specific moment in time.
A cross-sectional study has defined characteristics that limit the size and scope of the work. Researchers look at specific relationships that happened during a particular moment in time. That means there are fewer risks to manage if tangents begin to develop in the data. The goal is to look for a meaningful result within an expected boundary.
2. No variable manipulation occurs with a cross-sectional study.
Researchers directly observe the variables under study when using the cross-sectional technique. There is no reason to manipulate the environment because this is not an experimental technique. The data gathering process goes quickly because everything occurs within the scope of the research method. This advantage reduces the risk of having bias creep into the information being gathered.
3. It is an affordable way to conduct research.
A cross-sectional study is much more affordable to complete when compared to the other options that are available to researchers today. No follow up work is necessary when taking this approach because once the information gets collected from the entire participant group, it can be analyzed immediately. This advantage as possible because only a single time reference is under consideration.
This approach allows for usable data to become available without the risk of a significant initial investment. Most of the data points collected using this method come from self-report surveys. Researchers can then collect a significant amount of information from a large pool of participants without a major time investment.
4. This study method provides excellent controls over the measurement process.
Cross-sectional studies are only as good as the measurement processes that researchers used to collect data. Because there aren’t any long-term considerations involved with this specific approach, researchers have more control over the information acquisition process. Everything obtained during this work is quickly and easily measured and applied to the targeted demographics because the controls involved are straightforward to implement.
5. Researchers can look at several useful characteristics at once.
Many researchers prefer the cross-sectional studies method because it allows them to look at numerous characteristics simultaneously. Instead of focusing on income, gender, age, or other separating factors, this method looks at each participant as an entire individual. That makes it possible for the work to include several useful characteristics that can each benefit from changing variables instead of using only one to determine an outcome.
This advantage is the reason why researchers often use cross-sectional studies to look at the prevailing characteristics in a given population. It is a process that lets different variables become the foundation of new correlations.
6. It provides relevant information in real-time updates.
Cross-sectional studies provide us with a snapshot of a specific group of people at a particular point in time. Unlike other methods of research that look at demographics over an extended period, we use this information to look at what is happening in the present. That means the data researchers collect from this process is immediately relevant, giving us an opportunity to create real-time updates within specific population groups.
This process is how we can determine if there are specific risk factors that correlate to particular outcomes wit in that group. A cross-sectional study might look at a person’s past smoking and chewing habits to determine if there is a correlation with a recent lung cancer diagnosis. Although it won’t provide a cause-and-effect explanation, it does offer a fast look at potential correlations.
7. Cross-sectional studies miss fewer data points.
The processes involved with cross-sectional studies reduce the risk of missing critical data points. Researchers have the ability to maximize their examination of the available information at any time because there are no time variables included in this work. That means a lower error rate typically occurs when using this method compared to the other approaches that are available to the scientific community.
8. It allows anyone to look at the data to determine a possible conclusion.
The information that cross-sectional studies obtain is always suitable for secondary analysis. This advantage means that researchers can collect information for one set of purposes, and then use it to explore different variables that might exist in that specific demographic at the same time. That means an investment in this work can provide ongoing usefulness because it always applies to the people involved during that specific time. It is one of the easiest ways to maximize your research investment value.
9. Cross-sectional studies offer information that’s well-suited for descriptive analysis.
If researchers want to develop a general hypothesis, then cross-sectional studies are the best way to generate specific situations that face a particular demographic. Each description of the critical data points creates the possibility of forwarding movement toward a future solution that may not have been considered previously.
Although this benefit doesn’t apply to causal relationships with this research method, the information collected from cross-sectional studies is a useful forward push toward additional research.
10. The focus of a cross-sectional study is to prove or disprove an assumption.
A cross-sectional study is a research tool that is useful across various industries. The reason why it is such a generalized process that anyone can initiate is that the purpose of the work is to prove or disapprove and assumption or theory. Although health-related work tends to be the most popular industry that takes advantage of this approach, retail, education, social science, religion, and government industries can also benefit from this process.
The research that occurs allows each industry to learn more about the various demographics for the purpose of analyzing a target market. It creates data that’s useful when trying to determine what products or services to sell, or when it is necessary to look for specific patient outcomes.
List of the Disadvantages of Cross-Sectional Studies
1. It requires the entire population to be studied to create useful data.
A correctly structured cross-sectional study must be representative of an entire demographic for it to provide useful information. If this representation is not possible, then the data collected from the participating individuals will have a built-in error rate that must come under consideration.
That’s why a complete generalization is not possible when using this approach. Environmental conditions, a person’s education, and several other factors can all change an individual’s perspective.
2. A researcher’s personal bias can influence the data from cross-sectional studies.
Everyone has particular biases that influence their personality and general perspective on life. Many of these circumstances come from the conditioning that happens over the course of time. Even people who work hard to avoid showing bias in any situation can come under the influence of this disadvantage of cross-sectional studies.
Some demographics might include prison populations, the homeless, or people who are unable to leave their homes. If a researcher feels uncomfortable contacting individuals in these groups, then the final data points will not have as much relevance as they could.
3. The questions asked during cross-sectional studies may lead to specific results.
If researchers want to achieve a specific result when performing a cross-sectional study, then they can ask questions in such a way that it leads participants to the desired answer. When there are surveys or questionnaires about specific aspects of a person’s life, then the answers received may not always result in an accurate report. Shared experiences can result in different perspectives.
We have seen this disadvantage play out numerous times throughout several generations. The people who were alive during the Vietnam war, the attack on Pearl Harbor, or the terrorist event in New York City on 9/11 have shared experiences that make them different from other age groups. The people who survived these events are another subgroup that can impact the quality of information gathered.
4. Large sample sizes are often necessary to generate usable information.
A significant sample size is often necessary for a cross-sectional study to provide useful information. This disadvantage occurs because the entire population demographic must go through the research at once to prevent errors in the data. When a smaller sample size is the focus of the work, then the risk of errors entering into the information increases dramatically. There are more opportunities for coincidence or a chance to influence the results with a smaller research sample.
Although cross-sectional studies are often very affordable, the inclusion of an entire demographic pushes the cost of this work higher than it would be for other approaches.
5. Cross-sectional studies don’t offer any control over purpose or choice.
When the data from a cross-sectional study is found useful for secondary data analysis, the bias of the researchers can influence the information without any future realization. The secondary approach has no control over how this work gets completed initially. That’s why an overview of the methods used and the purpose for collecting information in the first place are often included as part of the results of this work.
If these additional facts are not part of the final experience, and the usefulness of the information for future needs becomes questionable.
6. No information about causal relationships is possible with this approach.
This research method does not provide information about causal relationships. The goal of this approach is to offer correlated data that is useful when drawing conclusions about a specific demographic. It can only let researchers see that a causal relationship exists without letting them know the reason behind its existence.
That’s why individualization is a disadvantage to this type of study. Researchers are wanting to see a generalized overview of a specific population sample instead of understanding why some people make particular choices.
7. Demographic definitions must be available to create a. successful result.
The information collected during a cross-sectional study is not reliable unless there are specific definitions in place for a population sample that is large enough for generalization. If researchers want to look at a rare outcome or a unique event, then inappropriate conclusions could get gleaned from the collected data. Trying to force a specific question or result could encourage responses that are unnecessary within the study population.
The only way to avoid this disadvantage of a cross-sectional study is to create definitions that work specifically with the intended results.
8. Cross-sectional studies have no way to measure incidence.
The goal of a cross-sectional study is to review the data that researchers collect as they study-specific variables. It does not take a look at the reason why the specific information points occur within the population demographics. This disadvantage limits the availability of an outcome for researchers in many situations because there is no determination available as to why the variables are present initially.
It only measures the existence and relationships that are present in that environment, not what triggers the variables.
9. It can be challenging to duplicate the results.
Even though a large population sample is necessary to create an accurate dataset from a cross-sectional study, it is challenging to duplicate results from multiple efforts. This disadvantage occurs because work happens in real-time situations. What happens right now can create a very different result then what could happen in the future.
That’s why many institutions face some challenges when they attempt to put together a sampling pool. The variables that should be studied are available in complex ways that may be difficult to manage. This issue is so detrimental that the timing of a specific snapshot is never a 100% guarantee that it’s representative of the entire population group.
A cross-sectional study is a useful research tool in most areas of health and wellness. When we can learn more about what is happening within a specific population demographic, then researchers can better understand the relationships that could exist between particular variables. The information that comes out of this process allows us to develop further studies that can explore the results in greater depth.
Several other research study options are available when there is a need to collect information from a specific demographic. It is essential to compare the critical points from each approach to determine what the best possible solution will be for each situation.
These cross-sectional advantages and disadvantages show us that a massive undertaking of simultaneous data collection can provide unique results that can benefit an entire population group. Although there are some challenges to manage when taking this approach, it is one that most researchers find to be beneficial.
Blog Post Author Credentials
Louise Gaille is the author of this post. She received her B.A. in Economics from the University of Washington. In addition to being a seasoned writer, Louise has almost a decade of experience in Banking and Finance. If you have any suggestions on how to make this post better, then go here to contact our team.