Study Design: Randomized Controlled Trial

A study design is an organized system or approach to carrying out a study. Different forms of studies are carried out appropriately by using different research designs. Initially, the design used in a study was largely determined by whether the study in question was a quantitative one or a qualitative one (Chassang & Miquel, 2010). However, with advancements in technology, more specialized methods of conducting studies have been established, and with them, new designs of studies have been discovered (Walters, Lareau & Ranis, 2009).

One such specialized design of conducting studies is the Randomized Controlled Trial (RCT). RCT is a form of Ecological Study Design that uses aggregated secondary data on, for instance, the risk factors of a disease and the prevalence of that disease in different population groups, to be able to establish the association between the two factors (Chassang & Miquel, 2010). However, Randomized Controlled Trial, as a study design, entails a random assignment of subjects in to a treatment or control groups. It is, therefore, used to conduct studies in to the effects of treatment as a method of disease control in different populations (Chassang & Miquel, 2010). In this form of study, the control group is accorded a usual treatment or a placebo, and the treatment group given the interventional or treatment drug or medication. This process serves to establish a similarity or difference between the two groups, and, as such, establish the possible confounders that help to eliminate the effect of the control group. The result is that the researcher can isolate the effects of intervention or treatment and consider them as an independent entity. In so doing, any observations made, which portrays the difference between the intervention and the control groups, can be solely attributed to the intervention group, making it easier to establish the difference between the two. Because of these capabilities, randomized Controlled Trials, as a study design, is used as the gold standard for health and disease surveillance studies. Indeed, if properly executed, this design has the capacity to offer the strongest evidence of the relationship between exposure to a certain disease condition and its outcome.  


The establishment of an association between exposure and outcome of a disease is a very important aspect of an epidemiological study. However, this association may be due to a third factor that has not been identified yet (Walters et al., 2009). This third factor may be associated to exposure to a disease but independently affect the amount of risk involved in developing the disease. This situation of dependent and independent association to the disease occurrence factors is termed as confounding. The third factor that is dependently or independently associated to the disease process is, therefore, termed as the confounder (Walters et al., 2009).

Most observational studies, just like Randomized Controlled Trial, have the problem of Confounding as their main weakness. In the case of health science studies, this weakness is widely so because healthy and unhealthy behaviors are often congregated in the same individual (Walters et al., 2009).  An example of this congregation is seen in people who exercise, who have bee observed to eat healthier foods. As such, to consider the association of exercise and health outcomes alone, without taking the effects of diet in to consideration, would be to commit a fallacy in research. This is because the effects of exercise will falsely be portrayed to be large, since the effects of diet would be unaccounted for. Confounding, therefore, brings in to perspective the need to consider the third factors that may be of immense significance to a study. It marks the first weakness to which Randomized Controlled Trial is prone. 


This can be defined as the ability of a certain study design or instrument to measure and provide the same trend of results each time it is used under the same conditions, and using the same objects (Chassang & Miquel, 2010). In simpler terms, it is the ability of a study design or instrument to repeat the measurements consistently. On the other hand, a measure can only be considered reliable if the same person scores the same score in the same test given twice. Because of this logic, Randomized Controlled Trial often performs the study surveys in duplicates, using control groups in both cases. This has a general effect of improving the accuracy of the studies, and accounting for every factor that is involved.


Internal Validity: This is simply defined as the truth within a study. A study is considered effective and valid as such, only if the results and conclusions of the study define the truth about the subject of study as depicted by the individuals being studied (Chassang & Miquel, 2010). There is, therefore, a belief or assumption that the results obtained by these studies were not likely a product of bias, chance, or confounding and that the study design had been accurately executed, and the results correctly analyzed. Considering that Randomized Controlled Trial randomly places individuals in different groups for studies, thereby minimizing congregation of certain traits or behaviors within a certain study group, it is expected that it will achieve a higher internal validity because it has effectively eliminated bias (Chassang & Miquel, 2010). It is pointless to conduct a statistical assessment of the effects of a given factor if it has already been invalidated by its bias. However, all study designs are flawed to some extent. The important question to address here, therefore, is whether or not these problems or errors were great enough to influence the outcome of the study to a large extent.

External Validity: This is simply defined as the truth beyond a study. A study design is often considered externally valid if its results and conclusions are consistent with the truth about a certain population, regarding the subject of study. Additionally, the results of the study should be able to establish similarity in important characteristics, between the study population and the reader’s population, regarding the subject of study.

The random allocation of study groups in the case of Randomized Controlled Trial study design ensures that errors are eliminated and that the study population is widely represented (Chassang & Miquel, 2010). This effective representation of the study population, in a random manner, will help the study to achieve results that are almost similar to textbook outcomes for the same subject of study.

However, just like in most ecological study designs, the aggregation of data at the group level makes the inference of the relations at the individual level a daunting task. Randomized Controlled Trial as a study design, therefore, comes up with weak empirical evidence to support the facts of the study subject.

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