Study Design
Cross sectional study design
Definition
A cross-sectional study is an observational descriptive study represents a snapshot about a particular status in a specific community, at a specific point in time without intervening in any way with the subjects.
Types of Cross-sectional Studies
Descriptive:
A cross-sectional study may be purely descriptive and used to assess the frequency and distribution of a particular disease in a defined population.
End point:
Inform about single/multiple variables
Prevalence
Disease and suspected risk factor
Analytic
Used to investigate the association between a putative risk factor and a health outcome.
However, this type of study is limited in its ability to draw valid conclusions about any association or possible causality because the presence of risk factors and outcomes are measured simultaneously.
End point:Present + strength of the association between disease and risk factor
Testing hypothesis.
Choosing a Representative Sample:
Sampling Methods:
Probability Sampling: This is also known as random sampling.
Non-Probability Sampling: where the samples are gathered in a process that does not give all the individuals in the population equal chances of being selected
Sampling Methods - Probability Sampling:
Simple random sampling: size n is produced by a scheme which ensures that each subgroup of the population of size n has an equal probability of being chosen as the sample.
Stratified random sampling: Divide the population into "strata". There can be any number of these. Then choose a simple random sample from each stratum.
Systemic random sampling
Cluster random sampling: divide the population into groups, obtain a simple random sample of so many clusters from all possible clusters, and obtain data on every sampling unit in each of the randomly selected clusters.
Sampling Methods – non-Probability Sampling
Snowball Sampling: usually done when there is a very small population size.
Judgmental Sampling: subjects are chosen to be part of the sample with a specific purpose in mind.
Convenience Sampling: the samples are selected because they are accessible to the researcher.
Strengths and Weaknesses
Strengths:
Relatively easy to conduct.
It is a study that could be done over short periods of time.
Data on all variables (exposure, outcome, and confounders) are only collected once.
Possibility of assessing prevalence for all factors being studied.
Multiple exposures and outcomes can be studied.
The prevalence of disease or other health related characteristics are important in public health for assessing the burden of disease in a specified population and in planning and allocating health resources.
Good for providing descriptive results and for generating hypotheses.
Weakness:
Time sequence of exposure and outcome is not implicated in this design.
Not suitable for studying rare diseases.
The incidence of a disease cannot be calculated through this study design.
Susceptible to selection bias.
Susceptible to information bias.
Susceptible to confounding bias.