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Presentation/PPT
27/08/2022
Measures of Effect
One important application of epidemiology is to identify factors that could increase the likelihood of a certain health problem occurring within a specific population. Epidemiologists use measures of effect to examine the association or linkage in the relationship between risk factors and emergence of disease or ill health. For instance, they may use measures of effect to better understand the relationships between poverty and lead poisoning in children, smoking and heart disease, or low birth weight and future motor skills.
What is the significance of measures of effect for nursing practice? In this Discussion, you will consider this pivotal question.
To prepare:
By tomorrow 04/11/2018 3pm, write a minimum of 550 words in APA format with at least 3 scholarly references from the list of required readings below. Include the level one headings as numbered below”
Post a cohesive scholarly response that addresses the following:
Required Readings
Friis, R. H., & Sellers, T. A. (2014). Epidemiology for public health practice (5th ed.). Sudbury, MA: Jones &smp; Bartlett.
Review Chapter 3, “Measures of Morbidity and Mortality Used in Epidemiology”
Chapter 9, “Measures of Effect”
Chapter 9 extends the discussion that began with Chapter 6 (which looked at ecologic, cross-sectional, and case-control study designs) by introducing additional measures that are useful in evaluating the potential implications of an exposure-disease association.
Tripepi, G. Jager, K. J., Dekker, F. W. & Zoccali, C. (2010). Measures of effect in epidemiological research. Nephron Clinical Practice, 115(2), c91–c93.
As noted by the authors of this article (2010), “Measuring the strength of observed associations between a given risk factor (e.g., blood pressure) and a given outcome (e.g., stroke) is an important goal in epidemiological and clinical research” (p. c91). This article provides an accessible overview of the terminology and various methods used to measure associations in research.
Optional Resources
Krethong, P., Jirapaet, V., Jitpanya, C., & Sloan, R. (2008). A causal model of health-related quality of life in Thai patients with heart-failure. Journal of Nursing Scholarship, 40(3), 254–260.
Ibrahim, M., Alexander, L., Shy, C., & Deming, S. (2001). Common measures and statistics in epidemiological literature. ERIC Notebook, 17, 1–6. Retrieved from http://cphp.sph.unc.edu/trainingpackages/ERIC/eric_notebook_17.pdf
Schmidt, C. O., & Kohlmann, T. (2008). When to use the odd ratio or the relative risk? International Journal of Public Health, 53(3), 165–167.
Vineis, P., & Kriebel, D. (2006). Causal models in epidemiology: Past inheritance and genetic future. Environmental Health: A Global Access Science Source, 5, p. 21.
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