Cross-Sectional Study as Research Design in Medicine Archives of The Medicine and Case Report s

A cross-sectional study is an observational study that analyzes data from a population at one point in time. These studies are often used to measure prevalence in medicine, analyze health studies, and describe health characteristics. Unlike other types of observations, in a cross-sectional study, each research subject was only observed once, the measurement of research variables was carried out at the time of the observation, and no follow-up was carried out on the measurements made. These studies are less expensive and easier to perform and help establish preliminary evidence in planning further studies in the future. This article reviews essential characteristics, describes strengths and weaknesses, discusses methodological issues, and provides design recommendations and statistical analysis for cross-sectional studies.


Introduction
In determining the research design, researchers should understand several essential things.
Researchers must determine whether to intervene or will only make observations without intervention in the research to be carried out. Research that only makes observations without intervention is called an observational study. These observational studies are generally divided into three types: cross-sectional studies, case-control studies, and cohort studies. 1 Observational research is the most frequently conducted research in the medical field. In this study, researchers only observed the phenomena studied systematically and then collected and compiled information, data, and sample materials such as biopsy tissue and blood for later data analysis. This study aims to discuss a cross-sectional study which is part of an observational study.

Archives of The Medicine and Case Reports
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License The characteristic of descriptive cross-sectional studies is the prevalence of one or more health outcomes in a population, so cross-sectional studies are often also referred to as prevalence studies because this study can determine the prevalence of disease in a population at one time. 1,3 In cross-sectional studies analytically, the researcher collects both risk factor data and outcome data at a particular time to compare the differences in outcomes between subjects exposed to risk factors and subjects not exposed to risk factors.
Exposure to risk factors and outcomes are measured simultaneously; therefore, it is difficult to determine whether exposure to risk factors precedes or follows the results in this cross-sectional analysis study a disease that is chronic and is not suitable for assessing acute conditions. 2,4 The advantage of conducting cross-sectional studies is that these studies tend to be faster and cheaper in terms of financing. Research subjects also do not require intervention to get exposure or risk factors, so ethically, research is rarely found to be complicated.
Meanwhile, the weakness of this cross-sectional study is that it cannot be used to assess the incidence or incidence for rare diseases and to assess causal factors, as well as the possibility of sample bias due to the need for a large enough sample.
In an analytical cross-sectional study, essential There are two main categories for sampling methods: probability sampling methods, where the sample is selected using methods based on probability theory and non-probability sampling methods, where samples are selected based on subjective considerations. In general, the probability sampling method is preferred over the non-probability one because the former is considered to be more accurate and thorough. However, there are circumstances in which it is impossible to conduct random sampling in applied clinical research, so nonprobability sampling is an option. 3 When a researcher is going to make a comparison between two study prevalence rates, cross-sectional, the sample size formula used is the same as the formula used in the cohort study design. 1,5 When planning a study with a cross-sectional design, a researcher must identify any bias. Bias is a systematic error in a study that can result in an  After observing and assessing exposure to risk factors and outcomes, the data obtained must be analyzed. In this data analysis, the sample subjects were divided into four groups according to exposure to risk factors and their outcomes, as shown in the 2x2 contingency table below.

Conclusion
A cross-sectional study is a form of observational study that is most often done in medicine. In this crosssectional study, researchers only observed phenomena systematically in a standardized way, collecting and recording information, data or materials that occurred spontaneously at certain times to be continued descriptively or with data analysis. Thus crosssectional studies have great utility in descriptive and analytic studies.