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Discussion 2: Logistic Regression in Nursing Practice

NURS 8200 Discussion 2: Logistic Regression in Nursing Practice

Discussion 2: Logistic Regression in Nursing Practice

Introduction

According to Polit (2010), the definition of logistic regression is “it analyzes the relationship between multiple independent variables and a single dependent variable, and yields a predictive equation (Pg. 306).” What make logistic regression useful are the biological systems and issues with which the health care field is concerned. We use logistic regression in healthcare to diagnose, predict, and forecast what could happen to patients.

Article Selection of Interest

“Prediction of influenza vaccination outcome by neural networks and logistic regression.”

Tritica-Majnaric, L., Zekic-Susac, M., Sarlija, N., and Vitale, B. (2010). Prediction of influenza  vaccination outcome by neural networks and logistic regression. Journal of biomedical Informatics, 43(5), 774-781. Doi:10.1016/j.jbi.2010.04.011

Critical Analysis of Article

What are the goals and purposes of the research study the article describes? The purpose of the study was to design a computer-based neural network model that will enable successful prediction of the outcome of influenza vaccine efficacy based on data related to influenza viruses and influenza vaccination, in combination with historical medical data (Tritica-Majnaric at al, 2010). The aim of the study was to design an intelligent computer-based neural network model that will enable successful prediction of the outcome of influenza vaccine efficacy (Tritica-Majnaric at al, 2010).

How is logistic regression used in the study? What are the results of its use? Logistic regression modeling is widely used for analyzing

Discussion 2 Logistic Regression in Nursing Practice
Discussion 2 Logistic Regression in Nursing Practice

multivariate data providing a powerful technique analogous to multiple regression and ANOVA for continuous responses (Tritica-Majnaric at al, 2010). The likelihood function of mutually independent variables Y1,…,Yn with outcomes measured on a binary scale is a member of the exponential family with (log(π11-π1),…,log(πn1-πn)) as a canonical parameter (πj is a probability that Yj becomes 1), the assumption of the logistic regression model is a linear relationship between a canonical parameter and the vector of explanatory variables x(Tritica-Majnaric at al, 2010).  Three algorithms and logistic regression were used in order to provide the influenza vaccination probability model that could be used for prediction purposes in the practice of primary health care physicians, where the vaccine is usually dispensed (Tritica-Majnaric at al, 2010).

What other quantitative and statistical methods could be used to address the research issue discussed in the article? Cross-validation was used in this paper because it produces no statistical bias of the result since each tested sample is not a member of the training set (Tritica-Majnaric at al, 2010). Others used are neural network methodology, logistic regression methodology, and evaluating model performance (Tritica-Majnaric at al, 2010).

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What are the strengths and weaknesses of the study? The main challenge is to predict which individual will most likely adequately respond to conventional influenza vaccines and which individual will not (Tritica-Majnaric at al, 2010). The artificial neural networks (ANN) have been shown to be a suitable computer-based method which can incorporate non-linear effects and interactions between multiple variables in a valid probability model (Tritica-Majnaric at al, 2010). The model is based on the results of vaccination by the influenza vaccine strain, the content of which was recently changed and on which, therefore, a poor antibody response was expected (Tritica-Majnaric at al, 2010). The results were compared with a standard logistic regression approach (Tritica-Majnaric at al, 2010). The major challenge in influenza vaccination is to predict vaccine efficacy (Tritica-Majnaric at al, 2010).

How could the weaknesses of the study be remedied? One way of remediating the weakness of the study is to use a larger sample size. Another way is to continue testing the influenza vaccine until the most accurate one becomes available.

How could findings from this study contribute to evidence-based practice, the nursing profession, or society? It gives a prediction of the outcome of influenza vaccination based on real historical medical data.

Conclusion

The influenza vaccination is fascinating to me in that hopefully one day, there will be a universal vaccination that covers all strains and maybe a person only has to get it once every five years or so. The importance of the study is that it continues to be researched to find that one vaccine to cover everyone.

References

Gray, J.R., Grove, S.K., and Sutherland, S. (2017). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Saunders Elsevier.

Polit, D.F. (2010). Statistics and Data Analysis for Nursing Research (2nd Ed.). Pearson Education Inc., Upper Saddle River, New Jersey.

Tritica-Majnaric, L., Zekic-Susac, M., Sarlija, N., and Vitale, B. (2010). Prediction of influenza vaccination outcome by neural networks and logistic regression. Journal of biomedical

Informatics, 43(5), 774-781. Doi:10.1016/j.jbi.2010.04.011