Randomised Controlled Trial - Coursework Example

Introduction In clinical studies, researchers may be looking forward to a specific treatment response of some certain illnesses to a given drug. In this reason, they may be able to compare treatment groups with control groups not receiving the medication. In employing a particular clinical study, the reliability of a certain drug may be proven effective or not because of the associated empirical evidence that one could generate thru the employed research design. Furthermore, there are some studies that would require precise measurement of the actual empirical evidence, so minimising the allocation of bias and other predictive factors has become necessary. Combining all these requirements results to achieving elemental characteristics found in using a Randomised Controlled Trial (RCT) which one could specifically apply into a clinical study and other related fields. As a research design, the RCT tries to generate more meaningful results that could mirror the reality, allowing it to capture the actual prevailing conditions. In this paper, the proponent tries to talk about the RCT by referring to a specific study as an example. Thus, the proponent highlighted the potential benefits and disadvantages involved in RCT as a research design commonly employed in clinical research. Implication to professional application is included. Randomised controlled trial Suppose a clinical study would want to use simple but powerful tools of research design, the RCT would remarkably qualify for this purpose. Based on the most commonly used actual research design for this concern, the RCT has considerably proven its worth on how it would help the researchers to come up with relevant data and information. The RCT as a research design would try to employ respondents by randomly choosing them to receive some designed clinical interventions. Some interventions are in form of treatments that are aimed at finding relevant information associated with prevention strategies, screening programs, diagnostic tests, interventional procedures, setting of providing health care, and educational models (Stolberg et al., 2004). One of the most important drawbacks in some studies is the inclusion of probable bias especially in generating data prior to the actual analysis and presentation of results. There are many statistical methods that could try to prevent this from influencing the reliability of the study. However, one common logical approach in statistics is to initiate random trials in response to selecting or acquiring of data. The RCT, as a research design and as the name implies, would try to randomise in choosing actual samples in order to give equal chance for each member of the population to be randomly chosen. This is such a very effective method because one could probably deter bias along the way resulting to generation of a more reliable information. In randomisation effort, the implication for this treatment would pave the way for considering the entire generated samples to represent the entire population. For example, by investigating the probable impact of certain chemicals or drugs on the human health, a common study is to employ animals like rats and monkeys. These animals may be randomly subdivided into different groups, in which some of them receive the treatments at varying dosage or by considering other relevant factors and related concerns. On the other hand, the control group will receive no treatment at all, as a reference point in order to find out the necessary information needed from the actual investigation process. Randomisation of selecting samples is in reality a most feasible approach because in the actual setting it would be impossible to use the entire population. Aside from it is going to be costly, not everyone in the first place would be willing to participate in the actual studies. In other words, the RCT in general is trying to create an inference of a particular intervention by randomly employing samples from the entire population that should therefore be randomly identified as the treatment or intervention groups and control groups (Bonita et al., 2006, p.50). Below is the actual diagram or framework showcasing the general flow involved in the RCT research design (Evidenced-Based Dentistry, 2013). So far, we now have a concrete and general idea on RCT as a research design and what it is all about, but we still need to know some important advantages and disadvantages associated with it. The good thing about RCT is the comparability of the control and treatment groups at the start of the investigation provided that the execution of initial selection or randomisation process is appropriate (Bonita et al., 2006, p.50). The comparability of generated samples out from randomised allocation from the study sample is therefore dependent on the execution of initial selection. Therefore, if the initial selection process is not properly executed, the actual outcome between the control and test group would remarkably vary and at some point could not be conclusive enough. The RCT research design is therefore a method that requires extra skills in order to generate the appropriate result. Another good thing about RCT is its ability to be conclusive to exactly tell that on the average a certain treatment may be effective for the entire population of samples (Fletcher and Fletcher, 2005, p.139). This means that the RCT could specifically help generalise the results or outcomes of certain treatments. On the other hand, a treatment that is effective on average may not be that effectual when applied to individual cases (Fletcher and Fletcher, 2005, p.139). This however is a remarkable drawback in employing RCT because it always seeks to find the results based on average outcomes. It seeks to generalise the outcome in order to generate a general conclusive information concerning a certain intervention. One can also employ RCT in a study involving heterogeneous population, which implies that it substantially could give extensive basis for the generalization of findings (Monsen and Van Horn, 2007, p.96). On the other hand, this would give us another idea that RCT cannot necessarily provide a generalized findings in line with individual cases. Probable reduction of confounding is a significant result that could be generated out of using RCT compared with other observational research designs (Agabegi and Agabegi, 2008, p.486). This is due to the fact that as stated earlier, if proper randomisation is initiated incurring findings that are bias are way far from being possible. However, if there is probable failure when it comes to concealment of allocation, blinding, and completeness of follow up and intent-to-treat analysis, a particular study may turn out bias (Agabegi and Agabegi, 2008, p.486). Thus, one essential point of ensuring a fair RCT is to consider constant assessment of the actual steps involved in performing it. This remarkably requires more effort by ensuring additional assesment of the initiated research design aside from giving primary focus on the objective of the study. In other words, RCT is such a sophisticated research design but in reality it requires more effort on the part of the researchers in order to obtain findings that would make sense. General findings are integrated with RCT and based on the above discussion, if individual cases are to be involved, RCT may not be the appropriate idea. However, as presented so far, RCT is a remarkable research design that could be relevant especially in clinical studies aiming to find the associated impact of a certain intervention. In other words, RCT is a robust method of raising definitive evidence for the effectiveness of a certain intervention or its superiority over other treatments (Bhugra, 2007, p.291). Even though there are wonderful opportunities and promised involved in RCT, there are also some weaknesses linked up with this research design. This research design is susceptible to incur bias provided that everything in the process is not set under favourable condition. However, in reality it is difficult to organise RCT under the most favourable conditions (Bhugra, 2007, p.291). This means that this research design although effective in obtaining definitive evidence would also require expertise in setting up the flow of the whole process involved in the whole period of the study. Evaluation Let us now move to our specific evaluation on the effectiveness of RCT when applied to an actual study. Based on the investigation that Dauphin et al. (1999) initiated, they were able to come up a significant result concering the bias and precision in visual analogue series (VAS) while successfully employing the RCT. In this study, the proponents tried to investigate the characteristics of VAS especially in the measurement of symptoms’ intensity or frequency. Prior to finding this, the research investigation included study samples under a prevention trial involving supplementation by antioxidant vitamins and minerals of respondents who were 35-61 years gathered from the general population in France. The actual data used in the study were generated by allowing respondents who were randomly chosen to put a scale on their response during the prevention trial. This is a specific case in which there was successful integration of the RCT with the actual study. Here are the following major observations that we could probably depict from the stated study using the RCT research design. There was inclusion of randomisation in gathering the entire samples in France. This means that the actual general data were assumed to represent the entire population. This is a remarkable strength of the study because this will eventually reflect on the kind of data that will be used for the VAS. The randomisation also applied when each subject was assigned a unique type and orientation of VAS. This means that the actual data prior to analysis by employing VAS could be assumed to be free from any hint of bias. This is another remarkable strength of the study because from its results, it seeks to show us that there was a guaranteed inclusion of proper execution of the initial selection. The entire study was able to test the variables based on the presence or absence of certain characteristics of the scale in VAS. Thus, the proponents were able to create comparison of data and results using a statistical tool that could be able to generate the mean difference. In finding these differences, the proponents have remarkable basis of telling whether there was involved bias or precision in VAS. This is another remarkable strength of the study because the entire findings could directly be associated with the actual research design. Since there was randomisation and inclusion of prevention trial during the generation of data, it is then implied that the proponents have substantially gathered the essentials that could lead them to obtain their research objectives. However, there was no clear methodology that could illustrate on how the prevention trial was initiated and how many numbers of samples were obtained from the entire population. This is a remarkable weakness of the study because in reality, researchers could not generate a conclusive result based on the data gathered and used if the samples could not be sufficient enough to represent the entire population. After all, one could use RCT to create a definitive evidence for the effectiveness of certain intervention. In the case of the study of Dauphin et al. (1999), the VAS is just a remarkable measure in order to maximise the efficiency of RCT in generating conclusive findings. The study of Dauphin et al. (1999) therefore has special implication on how to come up with intelligent approach in designing research that could guarantee giving the appropriate results and addressing the main objectives. Conclusion This paper tries to weigh the notable contributions of RCT especially in the field of clinical studies and how one could maximise its advantage when integrated with other relevant tools for analysis in generating highly defined conclusive results. The RCT has relevant advantages and weaknesses, but the bottom line boils down to the skills of the users on how they should properly initiate the research design including its associated process. The RCT is so powerful research design for as long as it tries to represent a general idea about the impact of a certain prevention or treatments applied in a certain population. As a result, it could help determine a generalise conclusion of the general case. Although individual cases cannot be entirely determined, the RCT still proves to be an efficient research design that could be freely integrated within the clinical studies especially in ensuring precision of results and warding off probable bias. References Agabegi, S. S., and Agabegi, E. D. (2008). Step-up to medicine. Philadelphia, PA: Lippincott Williams & Wilkins. Bhugra, D. (2007). Homelessness and mental health. New York, NY: Cambridge University Press. Bonita, R., Beaglehole, R., and Kiellstrom, T. (2006). Basic epidemiology. 2nd ed. Geneva: World Health Organization. Dauphin, A. P., Guillemin , F., Virion, J. M., and Briancon, S. (1999). Bias and precision in visual analogue scales: A randomized controlled trial. American Journal of Epidemiology. 150(10): 1117-1127. Evidenced-Based Dentistry (2013). Randomised-controlled trials. [Online]. Retrieved from: http://www.nature.com/ebd/journal/v8/n1/fig_tab/6400473f1.html [Accessed: 27 January 2013]. Fletcher, R. H., and Fletcher, S. W. (2005). Clinical epidemiology: The essentials. 4th ed. Baltimore, MD: Lippincott Williams & Wilkins. Monsen, E. R., and Van Horn, L. (2007). Research: successful approaches. 3rd ed. Washington, DC: American Dietetic Association. Stolberg, H. O., Norman, G., and Trop, I. (2004). Randomized controlled trials. American Journal of Roentgenology. 183(6): 1539-1544. Read More