Merits of Random Control Trials

Merits of Random Control Trials
Random Control Trial (RCT) is one of the effective study designs commonly used by health science researchers. RCT is a prospective study that determines the effectiveness of new treatments and interventions (Hariton & Locascio, 2018). In RCT, participants are assigned to control and experimental groups; however, the main projected difference is the outcome variable. Randomization is used to reduce bias and ensure a valid relationship between outcome and intervention. The design balances the participants' characteristics in the experimental and control groups, which is not evident in most study designs. Health researchers should be accurate and cautious when using RCT, especially during population selection. For instance, it is advisable to conduct a power calculation after determining the exact number required. After the calculation, the researcher should recruit the participants and assign them to either a comparator or intervention group. Besides, it is also necessary to ensure that the clients are unfamiliar with their assigned groups to enhance validity and reliability. RCT comprises specific merits and shortcomings in four major areas: external validity, feasibility, cofounding, and internal validity, which the paper addresses.
Merits of RCT
Internal Validity
Internal validity is essential in determining RCT's strengths. It refers to the extent to which the data represents the truth with minimal or no methodological errors. Internal validity is essential in health research since it reduces methodological errors that may jeopardize healthcare delivery quality. The key merit of RCT is that it maximizes internal validity by ensuring that differences within and between groups are not systematized (Deaton & Cartwright, 2018). Therefore, any recorded differences in the groups can be used for treatment and high-quality procedures. RCT provides valid data that can streamline high-quality procedures, which is critical in health science. The other merit of RCT about internal validity is that it addresses the 'identical' aspect of the treatment and the control group. The ultimate goal of a researcher is to make the treatment and control groups identical during formation; therefore, the approach is easily achieved through RCT, which maximizes internal validity.
Additionally, RCT guarantees equivalency or matching of the groups (Deaton & Cartwright, 2018). There is a possibility that the groups may have preexisting and matching attributes which are necessary for the research. Lastly, it allows the researchers to identify causal attribution, which is the ultimate goal of health-related researchers. Internal validity determines the accuracy of the cause and effect inferences. Therefore, whenever the researchers achieve the ultimate goal of causal attribution, then internal validity is achieved. Despite the identified differences, RCT is an accurate design for health science research due to its uniqueness and applicability. Therefore, it is recommended due to optimization of internal validity.
Confounding
The merits of the RCT as a design can also be explained through the cofounding aspect. Cofounding is the distortion of the relationship between dependent and independent variables...