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When conducting a study, one may distinguish between two major divisions: observational studies and experimental studies. Observational studies involve studying lives and processes within an area of interest without interfering with the variables or conditions directly linked to the subject under study. Descriptive studies, ecological studies, cohort studies, as well as cross-sectional studies, are all studies based on an observational approach. Conversely, experimental studies involve manipulating variables or conditions to achieve specific results. An example is Randomized Control Trials. A cross-sectional study, also known as a prevalence study, is widely used in studying the prevalence of diseases in populations. It involves collecting data and establishing a correlation between a potential risk factor and an outcome at a particular point in time.1 Cross-sectional study vs. Longitudinal studyCross-sectional studies focus on drawing data from a population at a particular point in time, where in contrast, longitudinal studies draw data of a population multiple times over a specific period in time. This means that it is essential to choose the most suitable type of study for different types of research. In many cases, cross-sectional studies are useful in collecting fundamental data, whereby important links and correlations are evaluated. Thereon, longitudinal studies can be carried out to study these correlations even further. As an example, you may conduct a cross-sectional study on the impact that parents from different income levels have on the grades of their children in elementary school. If you, for instance, evaluate that children with parents from higher income levels, perform better in elementary school, a correlation is concluded. Thereon, you can carry out a longitudinal study to further study the better performance of children in elementary school with parents from a higher income level, as your cross-sectional study has provided this correlation.2 Descriptive vs. Analytical studiesCross-sectional studies may be based on an analytical or a descriptive approach: Analytical cross-sectional study – examines correlations and links between different variables. Example: Suppose a study is being made to determine the number of college students from low-income families and establish whether it has a direct link to alcoholism. The analytical design will have you group the participants as follows:
Using the descriptive approach, the researcher may only look at the exposure or the outcome alone. Cross-sectional study – A guide
The first step toward carrying out research is to have a problem that calls for research. Once a gap has been established, for example, a research question looks to investigate the prevalence of addiction within individuals of a particular age group in the United States. Having this question will steer the research further.
Identify a population, which in the process of taking a sample, accommodates individuals from different races, cultures, ethnicities, religious backgrounds, economic statuses, and genders. It is also vital that the population that is analyzed, is an appropriate size. A large sample may offer variety and ensure that enough data can be collected. In relation to this, the likelihood to identify patterns and correlations may be much higher. In terms of recruiting participants, the most critical factor for a study is that the participation is voluntary and consent has to be given. It is considered an offense if participants are forced to take part.
After you have a group to work with, identify individuals exposed to the risk factor and those not; from this, you can collect information on the outcomes and exposures individually and simultaneously. Methods of data collection in a cross-sectional study:
When is a cross-sectional study suitable?A cross-sectional study is most applicable, when…:
A cross-sectional study is irrelevant to use, when…:
A cross-sectional study is conducted at a specific time, which makes it difficult to determine whether the exposure or the outcome came first and if their occurrences are linked in any way. For example, when studying a disease prevalence in a population, the samples may be grouped as in the following:
This case illustrates that it is difficult to know why one is not exposed and not infected or why one is exposed yet not infected. As there is no underlying evidence, it cannot be assumed that one was infected by exposure…etc. Pros and cons of a cross-sectional studyIn the following, we account for the advantages and disadvantages of cross-sectional studies. Advantages of using a cross-sectional studyA cross-sectional study is one of the most cost-effective forms of research. Therefore, researchers, who seek inexpensive research options may benefit from this type of research. In addition, it is less time-consuming than other studies, as data is collected only once at a defined point in time. It does not only allow you to collect all required variables but also to assess multiple outcomes at the same time. Furthermore, it is very effective, when used in a descriptive approach, as it measures the prevalence of all risk factors and, as a result, provides correlations for further research. Disadvantages of using a cross-sectional studyAs a cross-sectional study is conducted only once, the collected data may be insufficient to analyze behavior and relationships between parameters. It is impossible to determine a link between the outcome and the risk factor. Regarding this, it is also impossible to assess long-term patterns and trends, as the study is conducted over a particular moment. As there is no information prior to and post the study was conducted, the short time frame may make the research inaccurate and not always representative. A cross-sectional study may be subject to report bias. Any form of bias will primarily affect the data collected during a cross-sectional study. Selection bias may occur depending on who answered and who did not. In contrast, information bias is based on the validity and reliability of the collected data and methods used.3 To measure validity in a cross-sectional study, the researcher may ask:
To measure reliability in a cross-sectional study, the data collection method must be verified. The researcher may ask:
To avoid bias, the questionnaire should be able to lead to similar outcomes in similar scenarios. When working with convenience-based samples, another bias may occur. A cross-sectional study has no specific guidelines for sampling. If researchers did not thoroughly analyze and thus, collect non-accommodating samples, the collected data may be in favor of a particular group.1 FAQsWhat are the limitations of cross-sectional studies?As cross-sectional studies focus on studying characteristics of variables at a specific point in time, they are not able to assess behaviors and relationships between variables over an extended period in time. How do you analyze cross-sectional studies?The structure of a cross-sectional analysis includes the following steps:
How is data collected in a crossCross-sectional studies look at a population at a single point in time, like taking a slice or cross-section of a group, and variables are recorded for each participant.
Can crossSuch data can either be analysed cross-sectionally, by looking at one survey year, or combined for analysis over time.
What is a crossThink of a cross-sectional study as a snapshot of a particular group of people at a given point in time. Unlike longitudinal studies, which look at a group of people over an extended period, cross-sectional studies are used to describe what is happening at the present moment.
What is crossCross-sectional study design is a type of observational study design. In a cross-sectional study, the investigator measures the outcome and the exposures in the study participants at the same time.
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