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POPH8552 Introduction To Clinical Epidemiology

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POPH8552 Introduction To Clinical Epidemiology Question: Write a report on the Global Burden of Disease Cancer Collaboration’s article. Answer: Introduction The main objective of this paper is to provide an extensive assessment of the Global Burden of Disease Cancer Collaboration’s article. The article assesses the burden of cancer on 29 groups over a specified period of time with a view to provide a platform for policy discussion, research focus and resource allocation based on the findings of the study on the research topic. This paper mainly focuses on the particular aspects of the above collaboration’s health article with a view to identify the value of the article in terms of the employed study design, validity and reliability, comprehensiveness and representativeness, association, cause and effect. Research Design The study design used in the article is retrospective. This is a type of design that draws conclusion and similarity from past trends on an event (Kratochwill, 2015). This is because in the study, the development, outcome and burden of cancer on the 29 identified groups is watched. During the period of the study, other factors such as risk and protection factors are put into consideration. The study is retrospective in nature since it also involves cohort of the 29 groups which are the subjects of the research and watching them over a period of time. The outcome of interest in the study is common which makes it a retrospective study which is aimed at reducing cases of bias (Klebanoff & Snowden, 2018). Validity And Reliability In any study, the term validity is used to imply that the sample data meets the expectations of the study in the sense that it measures the intended variables (Heale & Twycross, 2015). In the study, the researcher ensures that the validity of the data is secured by employing already tested data from previous related studies. In addition to this, the article’s data validity is ensured since the researchers use data that has been released by previous related GBD studies. The data collection instruments that are used in the study are valid and are implemented as they should be hence yielding low errors in data collection. Consequently, the data represented on the articles is deemed reliable. Comprehensiveness And Representativeness Of Data It is imperative for a researcher to ensure that the sample data in a study denotes the specific characteristics of the sample and target population. Data comprehensiveness on the other hand simply implies that the meaning of the sample data is clear and comprehensive in nature (Hruby et al., 2016). There are a number of examples that can be drawn from the article that evidence that the sample data is comprehensive and representative in nature. In 2016, there were 17.2 million (95% UI, 16.7-17.8 million) incident cancer cases worldwide and 8.9 million (95% UI, 8.8- 9.1 million) cancer deaths (Fitzmaurice, 2018). This is an example from the article that shows representativeness and comprehensiveness of the data. The researcher also takes meanings into account which also makes the sample data representative and comprehensive. Association, Cause And Effect Cause and effect in studies is used to show the decisive role of a phenomenon in the occurrence of another phenomenon (Taris & Kompier, 2014). Any research that presents data from a sample population fails to reflect cause-and-effect. However, in the article, the researcher aims at ascertaining the different burden that cancer has on patients. As a result, the article clearly differentiates between association, cause and effect. The researcher achieves this  through the groups of 29 related to cancer that are classified into specific considerations that bring new developments to the causes and effects, something that clearly states that this study has a critical presentation of differences between the cause-and-effects and association. Similarly, the data that is used in the study clearly presents a clear difference in the association and cause-and-effect since it develops a clear category of the disease threat and their specific analysis that have been seen in the global platform and the issues that surround cancer and its development over the years. Specifically, the researcher presents an improvement of the differences that have been made under prior studies in which the changes made present a reliable case that is also used to analyze and categorize the many changes that are seen in the estimation methods and also the differences seen in the global cancer control. From the epidemiological and the demographic transition, the study also presents a specific contribution to the differences and to the cause and effects that are seen in the global war against cancer and other differences. Conclusion In conclusion, the different aspects used in the evaluation criteria of the article verify the value of the article as a research piece. The credibility of the article is also ascertained and evidenced by the lack of weaknesses and failures that have been scrutinized in the article.   References Fitzmaurice, C., 2018. Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2016; A Systematic Analysis for the Global Burden of Disease Study. JAMA oncology, pp.E1-E16 Heale, R. and Twycross, A., 2015. Validity and reliability in quantitative studies. Evidence-based nursing, pp.ebnurs-2015. Hruby, G.W., Hoxha, J., Ravichandran, P.C., Mendonça, E.A., Hanauer, D.A. and Weng, C., 2016. A data-driven concept schema for defining clinical research data needs. International journal of medical informatics, 91, pp.1-9. Klebanoff, M.A. and Snowden, J.M., 2018. Historical (retrospective) cohort studies and other epidemiologic study designs in perinatal research. American journal of obstetrics and gynecology.   Kratochwill, T.R., 2015. Single-case research design and analysis: An overview. In Single-Case Research Design and Analysis (Psychology Revivals) (pp. 13-26). Routledge. Taris, T.W. and Kompier, M.A., 2014. Cause and effect: Optimizing the designs of longitudinal studies in occupational health psychology.

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