Contributions of Randomised Controlled Trial - Essay Example

?Introduction In some 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. 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. 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 features of RCT that characterise it and could lead us to the particular benefits and disadvantages involved in this research design which clinical practitioners commonly employed in clinical research. Implication to professional application is included. RCT potentially prevents bias and reduces confounding Dauphin et al. (1999) 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, they were able 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. There was inclusion of randomisation from samples prior to investigating the actual point of the study. the same process was initiated during the first and second trials. This means that the actual general data were assumed to represent the entire information obtained from the entire samples. 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. Thus, the study of Dauphin et al reflects the actual framework involved in RCT research design. The RCT in general is trying to create an inference of a particular intervention by randomly employing samples from the entire study sample from a population that should therefore be randomly identified as the treatment or intervention groups and control groups respectively (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). One important strength in employing RCT as found in the study of Dauphin et al. (1999) is the presence of consistent result, as depicted by the presence of invariability when it comes to the precision of measurement of change over time. This specifically implies that the study samples where randomly chosen and given equal chance or opportunity to be chosen, allowing the same results to manifest from the first until the second trial of the study. In fact, Dauphin et al. were able to employ two-level randomisation in a six by two factorial design stratified by age and sex. This means that they were able to randomise the sample to generate a comprehensive result for knowing the probable bias or precision when using VAS under varying orientation. The second was for understanding the probable results of VAS under different scales. In other words, the actual data, prior to analysis by employing VAS could be assumed to be free from any hint of bias. This is a 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. This is a very important concept to be considered because Dauphin et al are trying to prove the significant difference that may be probably incurred upon implementing VAS under varying scales and orientations. If there was no consistent result when it comes to the consistency of the generated samples, the associated differences in the results of VAS could at some point be questionable. The differences of result would substantially imply that there might be a strong influence of the different samples employed into the first and second trials respectively, and so bringing us away from the potential claim that there might be probable existing bias in using VAS under diversified scale or orientation. Thus, the study eventually was able to assert that the choice of a type of VAS may potentially affect result, implying that researchers should come in consensus when it comes to deciding what sort of VAS to use particularly in experiments employing RCT. The RCT could be used for varying purposes. 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). For this reason, there is a need to have high level of control when it comes to variability. 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). Thus, 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. 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. A significant weakness or limitation of the study of Dauphin et al is the involvement of lower levels of control for interindividual variability. This could mean that they might have failed to completely execute initial selection of sample, but based on their finding there was no difference of the precision of measurement of change over time. This at some point might be contradictory, allowing us on the other hand to question the actual result of their findings. Concerning this, Dauphin et al must have presented us the statistical difference of the number of samples generated from the first and second trial. RCT is conclusive to tell the effectiveness of treatment in general 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. In the same way, Dauphin et al are trying to show us the result of their findings based on the effectiveness of certain prevention trial on average basis. Thus, allowing them to compare VAS of varying orientation and skills based on the average result from the generated data. This however, has important implication because there was no actual comparison of response of an individual employing different VAS. It would have been another interesting point to consider individual response for the purpose of finding whether there is actual bias issue associated with using VAS of different orientation and scale. However, the point of the study is to generalise the result, allowing all random samples to respond to the study, without taking into account the individual cases. The employment of RCT in the study of Dauphin et al therefore potentially reflects both the adavantage and limitation of RCT when it comes to its being conclusive to tell the effectiveness of treatment on average. Thus, one can also employ RCT in a study involving heterogeneous population, which implies that it substantially could give extensive basis for the generalisation 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. However, Dauphin et al. have lower level of control for interindividual variability implying that employing RCT was just an appropriate approach in order to consider extensive basis for the generalisation of findings. 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. 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