The final module is dedicated to randomised controlled trials, which is often considered the optimal study design, especially in clinical research. You will also develop the skills to identify strengths and limitations of the various study designs.
By the end of this course, you will be able to choose the most suitable study design considering the research question, the available time, and resources. The range of different study designs can be quite confusing. However, to help you navigate the maze of study designs, we can split them into groups which share common characteristics.
In this module, you will be introduced to these common characteristics, and you will learn the main principles of ecological and cross-sectional studies, as well as when it is appropriate to use them. By the end of the module, you will be able to identify and critically consider the advantages and disadvantages of these study designs. Study Designs in Epidemiology. Course 1 of 3 in the Epidemiology for Public Health Specialization. Enroll for Free.
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This Course Video Transcript Choosing an appropriate study design is a critical decision that can largely determine whether your study will successfully answer your research question. From the lesson. Different fictional data from different studies were used to calculate the incidence rate, relative risk, mortality rate, odds ratio and prevalence of diseases. The odds ratio and relative risk are called measures of association simply because they quantify the relationship between exposure and outcome.
Incidence rate, relative risk, and mortality rate were calculated in cohort studies; the odds ratio was determined in a case-control study while prevalence was calculated in a cross-sectional study. The appropriate measure to be used depends on the type of the research. Polio is also one of the diseases suffered by children in some developing countries. A lot of health-related problems have been bedeviling people all over the world.
Measures of frequency and association are very useful for that purpose and they are regarded as the fundamental of descriptive epidemiology. Epidemiology is very important field that is uses by government, health organizations, among others, in determining the important aspects of human conditions in a particular population. Such aspects include nationality, morbidity and mortality and they are described by rates, ratios and proportions.
The main concern of epidemiology is to measure health, discover what bring about the disease and intervene to cure the disease and overcome its causes . The role of epidemiology is beyond just a disease but the improvement of health, the control of the disease and devising structure for the health-related problems analysis. Epidemiology is made up of two study designs. Experimental study design and observational study design are the two basic study designs in epidemiology. In experimental studies, intervention is made by a researcher to modify reality and then observe what will happen, while in observational studies, a researcher notices what occurs but does not make any modification .
Randomized controlled trials and Quasi-experimental design are the types of experimental study designs while cohort study, case-control study as well as cross-sectional study are the three most common types of observational study designs.
Epidemiology – Knowledge for medical students and physicians
Data analysis is very crucial in epidemiological research as it assists in forming and structuring the findings from different sources of data collection and it also helps to keep human bias away from conclusion with the aid of appropriate statistical treatment . This article focuses on some measures of frequency and association calculated for cohort study, case-control study and cross-sectional study.
Fictive data will be used to calculate some measures of frequency and association. Those measures include incidence rate, relative risk, mortality rates, odds ratio and prevalence. Incidence rate, relative risk, and mortality rate will be used in a cohort study to calculate the different rates. Odds ratio will be determined in a case-control study while for cross-sectional study, prevalence will be calculated. Fictional data from the study of cholera cases among Yobe state civilian will be used to calculate the incidence rate while cases for lung cancer fictive data in Jigawa state will be used to analyze the relative risk as well as the odds ratio.
For mortality rate, Fictional data of maternal deaths of Kano state will be used to calculate the rate. The fictive data for the survey of patients at a sexually transmitted disease clinic in Kano state will be used to calculate the prevalence of condom used during the specified period. In this type of studies , a researcher observes and systematically gathers relevant information, but does not attempt to modify the subjects being observed.
Unlike experimental studies where a researcher intervenes to alter something e.
Examples of observational studies include a survey of smoking habits among adolescents, the study of breast cancer among women aged between 25 and 60, and a study of maladaptive behaviors among high school students. Observational studies are carried-out when a researcher cannot perform an experiment, when the experiment is not accepted or when the study is not experimental in nature.
It is also carried-out when the primary aim of the researcher is to get descriptive information. Cohort study, case-control study, and cross-sectional study are the three most common observational studies Figure 1. The ratios, proportions, and rates are used in epidemiology to describe the birth, disease and death.
Introduction: Value of epidemiological research for clinical practice.
The birth rate, mortality rate and the prevalence or incidence rate of a disease can be calculated using the data derived from the observational studies. Confidence interval will be calculated to assess or evaluate the possible impact of this sampling error. If both ends of the confidence interval are less than 1.
However, if the CI includes the null value, i. Mortality rate is regarded as a descriptive frequency measure while incidence rate and relative risk as measures of comparative effect . Cohort study analysis used the ratio of the rate of disease in the exposed group compared with the rate in the unexposed group. In epidemiology, incidence simply means the occurrence of new cases of disease, for example, new cases of Ebola disease, Lassa fever, or injury in a population during a specified period.
The incidence of a particular disease measures how quickly or frequently the disease of interest is been developed by people.
Unlike prevalence, incidence considers only new cases, and it has a unit. In order to measure the incidenceof a disease, a cohort study should be conducted. The study will include participants who are at risk of developing the disease of interest. Then they should be followed to determine those that truly developed the disease. Incidence rate is one of the approaches of measuring the frequency of disease in a population. Therefore, the incidence rate of a disease measures the frequency of the disease occurrence in a population over a specified period.
Incidence rates are subject to change over time, from disease to health, therefore the period of the cohort need to be specified. Example The cholera new cases among the Yobe state of Nigerian civilians population is while the Nigerian civilian population was estimated to be , The cholera incidence rate for the Nigerian civilian population will be calculated using these data. The above example shows that represent the new cases of diseases which were diagnosed during the specified period of the study while , is the population at risk.
This implies that persons who are involved in the , should be able to develop the disease, which is been described during the period covered. Relative risk also called risk ratio, is a measure of relationship which compares the rates of disease in two groups. The rate for the group of primary interest, for example, treatment group, is divided by the rate for a comparison group, for instance, control group.
Relative measures are used to detect the frequency of the likelihood of experiencing a particular health outcome for a person who is exposed to something than a person who is not exposed. The measures give a clue about the strengthof relationship between the exposure and the outcome, but do not express anything about the definite number of occurrence of disease in either group.