Discussion: Measures of Effect

NURS 8310 Discussion: Measures of Effect

Discussion: Measures of Effect

It is possible to calculate a number of measures of association (measures of effect) between exposure and disease (Friis & Sellers, 2021).The underlying premise is to figure out how much more (or how little) probable the cases are to be exposed than the controls (Friis & Sellers, 2021). Absolute effects, such as risk differences, are evaluated by comparing measures of disease frequency in exposed and non-exposed people (Friis & Sellers, 2021). The difference in illness frequency measures between the exposed segment of the population and the overall population is used to calculate the population risk difference (Friis & Sellers, 2021).

One example of measures of effect includes an environmental study published in 2019 by Jones et al. It investigated N-nitroso compounds (NOC) and disinfection by-products (DBPs), which are generated endogenously following nitrate/nitrite ingestion, are putative colorectal carcinogens, however epidemiologic evidence of these connections was sparse. They calculated average exposures and years of exposure above one-half the US maximum contaminant level using historical nitrate-nitrogen (NO3-N) measurements and estimates of total trihalomethanes (TTHM), the sum of 5 or 6 haloacetic acids (HAAs), and individual DBPs in public water supplies (PWS). The findings imply that drinking water exposure to TTHM is linked to an elevated risk of rectal cancer. Positive results for individual THMs and HAAs in colon and rectal malignancies must be confirmed in additional research. They were not able to find an association with ingested nitrates.

A second example of measure of effect is a meta-analysis that reports on sedentary behavior and its association with colon cancer (Cong et al., 2014). In review of twenty-three studies with 63 reports the authors determined that subgroup analyses suggest a positive association with sedentary behavior and the res of rectal cancer in cohort studies.

It is crucial to investigate measures of effect. Extrapolation of individual study findings to a larger population is crucial (Friis & Sellers, 2021). If effect measures are not used, the ability to enhance population health will be hampered by a lack of risk factor reductions (Friis & Sellers, 2021).


Cong, Y. J., Gan, Y., Sun, H. L., Deng, J., Cao, S. Y., Xu, X., & Lu, Z. X. (2014). Association of sedentary behaviour with colon and rectal cancer: a meta-analysis of observational studies. British Journal of Cancer, 110(3), 817–826.

Friis, R. and Sellers, R. (2021). Epidemiology for public health practice (6th ed.). Jones & Bartlett.

Jones, R. R., DellaValle, C. T., Weyer, P. J., Robien, K., Cantor, K. P., Krasner, S., Beane Freeman, L. E., & Ward, M. H. (2019). Ingested nitrate, disinfection by-products, and risk of colon and rectal cancers in the Iowa Women’s Health Study cohort. Environment International, 126, 242–251.

Examining Measures of Effect in the Nursing Practice

NURS 8310 Week 7 Discussion

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The link between exposure and disease outcomes strengthens the decision-making process in any clinical practice. Risk factors and

Discussion Measures of Effect
Discussion Measures of Effect

outcomes are also important goals in epidemiological and clinical research ( Tripepi et al., 2010). Nurses are also responsible to evaluate the effectiveness of nursing practice on patient health outcomes. Assessing the degree to which exposure affects outcomes can be measured using relative and absolute effects, which can both strengthen nursing practice and reduce patient risk (Friis & Sellers, 2021).

Absolute Risk Measures

The absolute measure is considered an effective examination of risk factors and disease outcomes and is widely used in public health practice (Tripepi et al., 2010).  Through the application of knowledge and evidence-based practice, nurses effectively strengthen practice by modifying the plan of care to direct future nurse-patient interaction to promote positive patient outcomes Krethong et al (2008) suggested that when nurses are called upon to care for patients from different cultures, cultural richness and understanding is an important measure for social support and improved patient outcomes. 

Number Needed for Treatment (NNT)

The number needed for treatment (NNT) is another tool used to determine the clinical significance of effective treatment ( DiCenso, 2001). DiCenso (2001) suggests that NNT is useful in decision making because it helps clinicians and patients avoid bad outcomes such as psychological distress or good outcomes such as the healing of a pressure ulcer.  Knowing the NNT will help nurses determine whether the likely treatment will benefit or harm the patient.


Measures of effects track the association between exposures and health outcomes, and not implementing these measures can cause risk to the individual patient and impact population health ( Friis & Sellers, 2021).  Determining if a nursing intervention is valid can be evaluated using measures of effect such as absolute risk and NNT.


DiCenso, A. (2001) Clinically useful measures of the effects of treatment. Evidence-Based Nursing 4, 36-39. Retrieved from


Friis, R.H., & Sellers, T.A. (2021). Measures of effect. Epidemiology for Public Health Practice

(6th ed., pp.362-380). Jones & Bartlett.


Tripepi, G., Jager, K.J., Dekker, F.W., & Zoccali, C. (2010). Measures of effect in epidemiological research. Nephron Clinical Practice, 115(2), c91-c93. Retrieved from


Week 7, Response 2, Gadon


Thank you for your post. I do enjoy knowing the NNT for reading guideline recommendations. In a commentary article by Kraemer, et al (2019), the authors share the issue avoiding false results from clinical research is to use effect sizes appropriately, but which effect size, when, and how is an unanswered subject. They feel that the p-value, in actuality, represents the quality of research design selections. A solution proposed by the authors is for perhaps the most common problem in clinical research: comparing two populations, such as comparing two treatments in a randomized clinical trial or comparing high risk versus low-risk individuals in an epidemiological study: the success rate difference, or equivalently the number needed to treat/take action (NNT).


Kraemer, H. C., Neri, E., & Spiegel, D. (2020). Wrangling with p‐values versus effect sizes to improve medical decision‐making: A tutorial. International Journal of Eating Disorders, 53(2), 302–308.