Health: Epidemiology
Question 1
Literature and systematic reviews are quite different in terms of method and value. A literature review is generally conducted to explore a research question or a phenomenon, while a systematic review aims to answer the research question as relevant as possible (Griffith University, 2022). For example, it has specific inclusion and exclusion criteria for the selected articles, which are not seen in a general literature review. The reliability of the variables and results is taken into account, while the systematic review adds to the value of the authenticity of the research. This is not the case in the literature review, which only serves to investigate the previous studies related to the current research, irrespective of the research design.
Systematic reviews are considered more reasonable than literature reviews because they are aimed at a specific phenomenon with a specific consideration of scope. The clarity for the researcher is pre-defined by what he is looking for and how he wants the results to be arranged, looking for only a particular research category/design. Various reviews are included to ensure that selection and population bias are avoided so that several opinions from previous researchers give genuineness to the results.
Question 2
Randomization means when the participants in a study/experiment are selected by equal chance or even assigned to a different group with an equal chance of selection (National Cancer Institute, n.d.-a). It is especially carried out in clinical experiments where the treatment of one group is to be compared with non-treatment or dissimilar treatment for true experimental results. This sampling method strengthens experimental studies since the study remains free of selection and accidental bias and the comparison of two groups becomes valid (Suresh, 2011).
When randomization is conducted in research, no previous knowledge of sample participants is known, so each person has an equal chance of being represented. The selection bias is limited, and the tendency to produce inaccurate results that might create risks for the researchs internal and external validity is eliminated.
Question 3
A major difference between descriptive and analytic studies is that descriptive studies tend to describe the relationship between two variables only (Ranganathan & Aggarwal, 2019). It could involve an occasional population for a selected sample. Analytic studies do the same; however, quantification of variables occurs before reaching the outcome or findings related to detecting the relationship between variables (Ranganathan & Aggarwal, 2019).
A descriptive study is less complex, while an analytic study is more complex and comprises a larger study area (Lakna, 2019). The descriptive study involves case reports and case studies, while true experiments and observational studies are part of analytic studies (Lakna, 2019). Further, the descriptive study analyzes the what, when, and where of the diseases under consideration, whereas the epidemiology studies analyze the why and how of the illness (Lakna, 2019).
Question 4
Population-based controls are deemed more appropriate than hospital-based due to minimized risk of selection bias. It is due to the representativeness that population-based control offers more in comparison with hospital-based (Ruano-Ravina et al., 2008). Certain characteristics are presented in the larger population rather than in hospital-based samples such as for a study that aims to explore tobacco use and the prevalence of lung cancer in low socio-economic class in the entire population rather than a specific hospital only (Ruano-Ravina et al. 2008).
Evidence shows that each study design has advantages and disadvantages (Ruano-Ravina et al., 2008). However, a population-based design is deemed more appropriate due to the representativeness factor. The differential characteristic is a serious consideration when using either of them as demographic factors, and the prevalence of diseases in the population has a larger impact (Ruano-Ravina et al., 2008).
Question 5
Non-differential misclassification is when the probability or risk of all study groups is equal for being misclassified (Catalog of Bias, n.d.). Differential misclassification occurs when the same probability differs in all study groups (Catalog of Bias, n.d.). The misclassification can cause great bias in the results since the group that should belong to a certain category or classification is done incorrectly, creating errors in outcomes of interests. The effect of non-differential misclassification is when certain ratios, like the risk ratio, the odd ratio, etc., move toward the null hypothesis (Alexander et al., n.d.). Also, the effect of...
…the one who has similar symptoms but not the exact condition, the control group (National Cancer Institute, n.d.-b). To see what effect a certain variable has on one group while the same variable has an effect on the other with relevance to particular demographic features, for instance, would be a suitable research design for a case-control study.The advantages of a case-control study are the evaluation of diseases in one group to make comparisons with the other, less investment of time and costs, and measuring the effects of variables for a dynamic population whose follow-up might be difficult afterward (LaMorte, 2016c). Disadvantages include their vulnerability to selection bias, no calculation of incidence that contributes to absolute bias, and inefficiency in making calculations for rare exposures (LaMorte, 2016c).
uestion 13
The ecologic fallacy occurs when an inference about an individual or group under study is made based on the wholesome characteristics or outcomes based on the aggregated data for the group (Hsieh, 2017). The reasoning seems short of a rational explanation of population health outcomes as risk-modifying factors are weak. The correlations show different results on a group level, which are matched with those of an individual, making the reasoning doubtful.
For example, research has been conducted that African people are more prone to have a diet not usually found in neighboring countries, which might not be true. Factors like changing demographic aspects and foreign people entering or exiting the country could have their influences. Inter-cultural marriages and their diet combination could be another element under scrutiny that could only be inferred for one African person.
Question 14
If the null hypothesis states that myocardial infarction (heart attack) is not caused by feeling depressed, the alternate hypothesis is that heart attack is caused by feeling depressed. A 95% confidence interval shows that the null hypothesis does not fall within the remaining 5%, meaning that the alternate hypothesis stands true (Flechner & Tseng, 2011). The results should indicate that a statistically significant relationship exists between heart attacks and feelings of depression.
A wider confidence interval range shows that the results could be faulty and that a statistically significant relationship might be estimated…
References
Alexander, L.K., Lopes, B., Ricchetti-Masterson, K. & Yeatts, K.B. (n.d.). Sources of systematic error or bias: Information bias. Gillings School of Global Public Health. https://sph.unc.edu/wp-content/uploads/sites/112/2015/07/nciph_ERIC14.pdf
Catalog of Bias. (n.d.). Misclassification bias. https://catalogofbias.org/biases/misclassification-bias/#:~:text=Non%2Ddifferential%20misclassification%20occurs%20when,2014).
Flechner, L., & Tseng, T. Y. (2011). Understanding results: P-values, confidence intervals, and number need to treat. Indian journal of urology: IJU: Journal of the Urological Society of India, 27(4), 532–535. https://doi.org/10.4103/0970-1591.91447
Griffith University. (2022, November 1). Systematic style literature reviews for education and social sciences. https://libraryguides.griffith.edu.au/systematic-literature-reviews-for-education#:~:text=Systematic%20literature%20reviews%20aim%20to,producing%20varied%20and%20reliable%20results.
Health Knowledge. (n.d.). Introduction to study designs- case-control studies. https://www.healthknowledge.org.uk/e-learning/epidemiology/practitioners/introduction-study-design-ccs#:~:text=A%20major%20characteristic%20of%20case,and%20conduct%20of%20the%20study.
Hsieh, J.J. (2017, September 4). Ecological fallacy. Britannica. https://www.britannica.com/science/ecological-fallacy
Lakna. (2019, July 5). What is the difference between descriptive and analytic epidemiology. Pediaa. https://pediaa.com/what-is-the-difference-between-descriptive-and-analytic-epidemiology/
LaMorte, W.W. (2016-a, September 21). Follow-up in cohort studies. https://sphweb.bumc.bu.edu/otlt/mph-modules/ep/ep713_cohortstudies/EP713_CohortStudies4.html
LaMorte, W.W. (2016-b, September 21). Advantages and disadvantages of cohort studies. https://sphweb.bumc.bu.edu/otlt/mph-modules/ep/ep713_cohortstudies/EP713_CohortStudies5.html
LaMorte, W.W. (2016-c, June 7). Advantages and disadvantages of case-control studies. https://sphweb.bumc.bu.edu/otlt/mph-modules/ep/ep713_case-control/EP713_Case-Control8.html
LaMorte, W.W. (2021, November 11). Three methods for minimizing confounding in the study design phase. https://sphweb.bumc.bu.edu/otlt/MPH-Modules/PH717-QuantCore/PH717-Module11-Confounding-EMM/PH717-Module11-Confounding-EMM4.html
National Cancer Institute. (n.d.-a). NCI Dictionaries: Randomization. https://www.cancer.gov/publications/dictionaries/cancer-terms/def/randomization
National Cancer Institute. (n.d.-b). Case-control study. https://www.cancer.gov/publications/dictionaries/cancer-terms/def/case-control-study
Pandis, N. (2014). Case-control studies: Part 2. American Journal of Orthodontics and Dentofacial Orthopedics, 146, 402-403. http://dx.doi.org/10.1016/j.ajodo.2014.06.005
Ranganathan, P., & Aggarwal, R. (2019). Study designs: Part 3 - Analytical observational studies. Perspectives in Clinical Research, 10(2), 91–94. https://doi.org/10.4103/picr.PICR_35_19
Ruano-Ravina, A., Perez-Rios, M. & Barros-Dios, J.M. (2008). Population-based versus hospital;-based controls: Are they comparable? Gaceta Sanitaria, 22(6), 609-613. https://doi.org/10.1016/S0213-9111(08)75363-9
Setia M. S. (2016). Methodology series module 1: Cohort studies. Indian Journal of Dermatology, 61(1), 21–25. https://doi.org/10.4103/0019-5154.174011
Skelly, A. C., Dettori, J. R., & Brodt, E. D. (2012). Assessing bias: The importance of considering confounding. Evidence-Based Spine-Care Journal, 3(1), 9–12. https://doi.org/10.1055/s-0031-1298595
Suresh K. (2011). An overview of randomization techniques: An unbiased assessment of outcome in clinical research. Journal of Human Reproductive Sciences, 4(1), 8–11. https://doi.org/10.4103/0974-1208.82352
Tsai, S.P., Cowles, S.R. & Ross, C.E. (1990). Smoking and morbidity frequency in a working population. Journal of Occupational Medicine, 32(3), 245-249. https://www.jstor.org/stable/45006955
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