Cross Sectional Research Design Advantages And Disadvantages PdfBy Hollie N. In and pdf 18.05.2021 at 23:44 5 min read
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- Cross-Sectional Study
- 15 Cross Sectional Study Advantages and Disadvantages
- Quantitative Study Designs: Cross-Sectional Studies
- How Does the Cross-Sectional Research Method Work?
The column covered over 35 common research terms used in the health and social sciences.
This short article gives a brief guide to the different study types and a comparison of the advantages and disadvantages. Figure 1 shows the tree of possible designs, branching into subgroups of study designs by whether the studies are descriptive or analytic and by whether the analytic studies are experimental or observational. The list is not completely exhaustive but covers most basics designs. Figure: Tree of different types of studies Q1, 2, and 3 refer to the three questions below. Our first distinction is whether the study is analytic or non-analytic. Descriptive studies include case reports, case-series, qualitative studies and surveys cross-sectional studies, which measure the frequency of several factors, and hence the size of the problem.
Cross-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. Unlike in case—control studies participants selected based on the outcome status or cohort studies participants selected based on the exposure status , the participants in a cross-sectional study are just selected based on the inclusion and exclusion criteria set for the study. Once the participants have been selected for the study, the investigator follows the study to assess the exposure and the outcomes. Cross-sectional designs are used for population-based surveys and to assess the prevalence of diseases in clinic-based samples. These studies can usually be conducted relatively faster and are inexpensive. They may be conducted either before planning a cohort study or a baseline in a cohort study.
A cross-sectional study involves looking at data from a population at one specific point in time. The participants in this type of study are selected based on particular variables of interest. Cross-sectional studies are often used in developmental psychology , but this method is also used in many other areas, including social science and education. Cross-sectional studies are observational in nature and are known as descriptive research, not causal or relational, meaning that you can't use them to determine the cause of something, such as a disease. Researchers record the information that is present in a population, but they do not manipulate variables. This type of research can be used to describe characteristics that exist in a community, but not to determine cause-and-effect relationships between different variables.
15 Cross Sectional Study Advantages and Disadvantages
Published on May 8, by Lauren Thomas. Revised on June 5, 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.
The prodominant study designs can be categorised into observational and interventional studies. Observational studies, such as cross-sectional, case control and cohort studies, do not actively allocate participants to receive a particular exposure, whilt interventional studies do. Each of the above study designs are described here in turn. In a cross-sectional study, data are collected on the whole study population at a single point in time to examine the relationship between disease or other health-related outcomes and other variables of interest exposures. Cross-sectional studies therefore provide a snapshot of the frequency of a disease or other health-related characteristics in a population at a given point in time. This methodology can be used to assess the burden of disease or health needs of a population, for example, and is therefore particularly useful in informing the planning and allocation of health resources. Non-response is a particular problem affecting cross-sectional studies and can result in bias of the measures of outcome.
PDF | A cross sectional study design was used to investigate the extent of chronic fatigue and the associated psychosocial exposures in a.
Quantitative Study Designs: Cross-Sectional Studies
Cross-sectional designs are used by empirical researchers at one point in time to describe a [Page ] population of interest universe. In cross-sectional designs, researchers record information but do not manipulate variables. A common example of cross-sectional design is a census study in which a population is surveyed at one point in time in order to describe characteristics of that population including age, sex, and geographic location, among other characteristics. This entry defines the characteristics of cross-sectional design, identifies examples of different types of cross-sectional designs, and describes common strengths and weaknesses of such designs.
In medical research , social science , and biology , a cross-sectional study also known as a cross-sectional analysis , transverse study , prevalence study is a type of observational study that analyzes data from a population, or a representative subset, at a specific point in time —that is, cross-sectional data. In economics , cross-sectional studies typically involve the use of cross-sectional regression , in order to sort out the existence and magnitude of causal effects of one independent variable upon a dependent variable of interest at a given point in time. They differ from time series analysis , in which the behavior of one or more economic aggregates is traced through time. In medical research, cross-sectional studies differ from case-control studies in that they aim to provide data on the entire population under study, whereas case-control studies typically include only individuals who have developed a specific condition and compare them with a matched sample, often a tiny minority, of the rest of the population. Cross-sectional studies are descriptive studies neither longitudinal nor experimental.
The Australian Census run by the Australian Bureau of Statistics, is an example of a whole of population cross-sectional study. Data on a number of aspects of the Australian population is gathered through completion of a survey within every Australian household on the same night.
How Does the Cross-Sectional Research Method Work?
Within the context of a cross-sectional study, information is collected on the entire study population at a single point of time. The goal of collecting this data is to examine the relationship of a specific target point, such as a disease, and other variables of interest within the population group. That allows this type of study to provide an overall snapshot of the characteristics, frequency, or occurrence of the targeted data point, at any given time, within the population group being studied. Using this methodology, it becomes possible to assess the burden of the population when they encounter the targeted data point being studied. That makes it a useful option when determining the allocation of resources to the population should the incident occur. There are two types of cross-sectional studies: descriptive and analytical. Descriptive studies are used to assess distribution and frequency.
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