NURS 8201 Week 7 Discussion Use of Regression Analysis in Clinical Practice ANSWERS
Sample Answer for NURS 8201 Week 7 Discussion Use of Regression Analysis in Clinical Practice ANSWERS Included After Question
Week 7: Quantitative Analysis and Interpretation: Regression
How might you predict future events in your practice? Why is it important, as a future DNP-prepared nurse, to consider such future events?
For a DNP-prepared nurse, future predictions might lead to better patient outcomes and care. Therefore, analyzing factors to predict or evaluate can assist in transforming nursing practice or healthcare delivery. The “statistical procedure most commonly used for prediction is regression analysis” (Gray & Grove, 2020).
This week, you will examine the application of linear regression. You will analyze the strengths and weaknesses of the findings in a research study determined with linear regression, as well as explore alternatives to strengthen the aims of the study. You will also begin work on an Article Critique Assignment. While this Assignment is not due until Week 10, you are encouraged to begin this Assignment this week.
Reference: Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.
Learning Objectives
Students will:
- Analyze the use of regression analysis to support peer-reviewed research
- Analyze strengths and weaknesses of research studies*
- Recommend alternative quantitative and statistical methods to support research studies
- Analyze impact of research studies on nursing practice*
- Recommend changes to study designs and methodologies to support research studies*
*Assigned in Week 7 of Module 3 and submitted in Week 10 of Module 4
Learning Resources
Required Readings (click to expand/reduce)
Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.
- Chapter 24, “Using Statistics to Predict” (pp. 675–686)
Linear Regression Resources (click to expand/reduce)
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Article Critique Resources (click to expand/reduce)
Discussion: Use of Regression Analysis in Clinical Practice
Regression analysis provides the researcher with an opportunity to predict and explore future outcomes. Whether it is to determine prevention methods, promote opportunities for learning, or propose new treatments, looking towards the future can have a significant impact on patient care and sustained positive patient outcomes.
This week, you explore regression analysis, paying particular attention to linear regression. Linear regression is used to “estimate the value of a dependent variable based on the value of an independent variable” (Gray & Grove, 2020). In your Discussion, you will apply your understanding of this statistical technique as it concerns use in a research study.
Photo Credit: wutzkoh / Adobe Stock
For this Discussion, you will select an article on a study to examine the strengths and weaknesses in the use of linear regression. Consider how you might remedy the weaknesses associated with the application of linear regression and reflect on how the findings of the study that you selected might contribute to various areas of your practice.
Reference: Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.
To Prepare:
- Review the articles in this week’s Learning Resources and evaluate their use of linear regression. Select one article that interests you to examine more closely in this Discussion.
- Critically analyze the article that you selected and consider the strengths and weaknesses described.
- Reflect on potential remedies to address these weaknesses, and how the findings from this study may contribute to evidence-based practice, the field of nursing, or society in general.
By Day 3 of Week 7
Post a brief description of the article that you selected, providing its correct APA citation. Critically analyze the article by addressing the following questions:
- What are the goals and purposes of the research study that the article describes?
- How is linear or logistic regression used in the study? What are the results of its use?
- What other quantitative and statistical methods could be used to address the research issue discussed in the article?
- What are the strengths and weaknesses of the study?
Then, explain potential remedies to address the weaknesses that you identified for the research article that you selected. Analyze the importance of this study to evidence-based practice, the nursing profession, or society. Be specific and provide examples.
By Day 6 of Week 7
Read a selection of your colleagues’ responses and respond to at least two of your colleagues on two different days in one or more of the following ways:
- Ask a probing question, substantiated with additional background information, evidence, or research.
- ·Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives.
- Offer and support an alternative perspective using readings from the classroom or from your own research in the Walden Library.
- Validate an idea with your own experience and additional research.
- Suggest an alternative perspective based on additional evidence drawn from readings or after synthesizing multiple postings.
- Expand on your colleagues’ postings by providing additional insights or contrasting perspectives based on readings and evidence.
Submission and Grading Information
Grading Criteria
To access your rubric:
Week 7 Discussion Rubric
Post by Day 3 of Week 7 and Respond by Day 6 of Week 7
To Participate in this Discussion:
Week 7 Discussion
Assignment: Article Critique
DNP graduates are expected to apply research findings and integrate nursing science into evidence-based practice. To develop your skills in this high level of nursing practice, you will analyze the strengths and weaknesses of a research study over the next several weeks using the concepts presented throughout the course.
Photo Credit: ismagilov / iStock / Getty Images
- A brief, 1- to 2-paragraph overview of the study that you selected.
- An explanation of two to three strengths of the study and support for your selection (i.e., why is this a strength?). Be specific.
- An explanation of two to three weaknesses of the study and support for your selection (i.e., why is this a weakness?). Be specific.
- Note: The strengths and weaknesses that you identified should be in relation to design, sampling, data collection, statistical analysis, results, and discussion of the study that you selected.
- An explanation of proposed changes that you would recommend to improve the quality of the study, capitalizing on the strengths and improving on the weaknesses that you identified in the study. Be specific and provide examples.
- A final summary of the implications of this study for nursing practice.
The purpose of the analysis is to help you develop a deeper understanding of the research process, to inspire you to think critically and deeply about research on a specific topic, and to strengthen your ability to integrate research findings into evidence-based nursing practice. This Assignment also gives you practice in analyzing the research literature, which will support you when you begin your DNP project. Before you proceed, please review the rubric for this Assignment. Keep in mind that you will be working on your article critique throughout Weeks 8 through 10 with your critique due by Day 7 of Week 10.
The Assignment: (5–7 pages)
- Select a research article from the body of literature that you have reviewed related to the practice gap you have identified and for which you will develop for your DNP Project.
- Review the various quantitative research designs presented in the textbook readings and research articles.
- Consider the research design used in your selected article. Ask yourself the following questions.
- Is the design appropriate for the study? Why or why not?
- Would a different design provide better results? Why or why not?
You are not required to submit this Assignment this week.
Reminder: The College of Nursing requires that all papers submitted include a title page, introduction, summary, and references. The Sample Paper provided at the Walden Writing Center provides an example of those required elements (available at https://academicguides.waldenu.edu/writingcenter/templates/general#s-lg-box-20293632). All papers submitted must use this formatting.
What’s Coming Up in Week 8?
Photo Credit: [BrianAJackson]/[iStock / Getty Images Plus]/Getty Images
Next week, you will continue your exploration of quantitative data. You will analyze and interpret the use of nonparametric methods for quantitative research and consider the appropriateness of applying nonparametric methods to support your research aims.
A Sample Answer For the Assignment: NURS 8201 Week 7 Discussion Use of Regression Analysis in Clinical Practice ANSWERS
Title: NURS 8201 Week 7 Discussion Use of Regression Analysis in Clinical Practice ANSWERS
Logistic Regression in Nursing Practice
The article I chose to examine and analyze this week is “Prediction of influenza vaccination outcome by neural networks and logistic regression.”
Tritica- Majnaric,L., Zekic-Susac, M., Sarlija, N., & Vitale, B. (2010).Prediction of influenza vaccination outcome by neural networks and logistic regression. Journal of Biomedical Informatics, 43(5), 774-781
Post your critical analysis of the article as outlined above
The critical issue with influenza vaccination is to foretell vaccine efficacy. The study presented in this article aimed to create a model to facilitate a credible prediction of the effect on influenza vaccination contingent upon valid medical data. A neural network approach was utilized, and its presentation was compared with using the logistic regression model
The three neural network algorithms that were tested include multilayer perceptron, radial basis, and probabilistic in conjunction with parameter optimization and regularization techniques to create an influenza vaccination model that could be used for prediction purposes in the medical practice of primary health care physicians, where the vaccine is usually dispensed (Tricia- Majnaric, Zekic-Susac, Sarlija, & Vitale, 2010). The variety of input variables was determined from the model of the vaccine strain, which has been altered and which a poor influenza reaction is likely. The action of models was quantified by the standard hit rate of difference in vaccine outcomes. Sensitivity analysis was performed on the best model, and the importance of input variables was discussed (Tricia- Majnaric, Zekic-Susac, Sarlija, & Vitale, 2010).
Logistic regression was widely used for dissecting the multivariate data, including dichotomous reactions with this research study. Logistic regression is identified as an analysis relationship between multiple independent variables and a single dependent variable which yields a predictive equation (Polit, 2010). The three neural network algorithms along with the logistic regression model were implemented to deliver the influenza vaccination probability model and apply it for prediction purposes within practice outcomes. Another statistical method that could address the research problem discussed in this article is the analysis of variance (ANOVA) statistical technique. ANOVA entails analyzing and arranging differences among three or more groups being compared to draw inferences. From this research study, the three NN algorithms, multilayer perceptron (MLP), radial-basis function network (RBFN), and probabilistic network (PNN), were tested and analyzed to draw an inferential conclusion.
Propose potential remedies to address the weaknesses of each study.
A strength of this study was the degree of the sensitivity and specificity analysis that was appropriately expressed. The generalization ability of the models used by a 10-fold cross-validation procedure showed that the model attained by multilayer perception produced the highest average hit rate among neural network algorithms and also outperformed the logistic regression model about sensitivity and specificity discussed (Tricia- Majnaric, Zekic-Susac, Sarlija, & Vitale, 2010). The sensitivity analysis was also implemented on the best models, and the vitality of the input variables was evaluated. A weakness of this study was the small sample size. The study consisted of 90 patients out of 150 people who required the influenza vaccine between 2003-2004 in Croatia. A more significant sample number would have been beneficial in this dataset and incorporating other methods to discover a more successful model.
Analyze the importance of this study to evidence-based practice, the nursing profession, or society.
The importance of prevention and control of the influence epidemic is imperative to the nursing profession and health care society. Based on the results of this research study, it is indicated that both types of data, those related to previous influenza viruses exposure and those describing the health status of examinees, influence outcome values of performed predictive models and could be used as efficient predictors of the influenza vaccine efficacy discussed (Tricia- Majnaric, Zekic-Susac, Sarlija, & Vitale, 2010). This is important, especially in the elderly, as this population has been more affected by the influenza virus. The available vaccines are less
effective in this age group. With new vaccine preparations and approaches, the effectiveness of influenza vaccines can be implemented through evidence-based practice.
References
Polit, D. F. (2010). Statistics and data analysis for nursing research (2nd ed.). Upper Saddle River, NJ: Pearson Education.
Tritica- Majnaric,L., Zekic-Susac, M., Sarlija, N., & Vitale, B. (2010).Prediction of influenza vaccination outcome by neural networks and logistic regression. Journal of Biomedical Informatics, 43(5), 774-781
A Sample Answer 2 For the Assignment: NURS 8201 Week 7 Discussion Use of Regression Analysis in Clinical Practice ANSWERS
Title: NURS 8201 Week 7 Discussion Use of Regression Analysis in Clinical Practice ANSWERS
Linear regression is one of the most commonly used type of predictive analysis in which estimates are used to explain the relationship between two things. The overall idea of linear regression is to examine if a set of predictor variables do a good job in predicting an outcome (dependent variable) or which variables in particular are significant predictors of the outcome variables and what they do (Statistic solution, 2020). This form of analysis estimates coefficients of the linear equation, involving one or more independent variable that best predicts the value of the dependent variable. As a result, they fit into a straight line or surface that minimizes the discrepancies between predicted and output values (Sathwick, 2020). Also, linear regressions help healthcare organizations collect massive data and use these data manage information. It would also provide better insights on patterns and relationships that would help understand its analytical connection. Since there is a new surge of Covid-19 almost every year for the past three years now, a study that I found interesting in conjunction with the Covid-19 is the associated stress that comes with this ongoing pandemic.
Being a nurse in the ICU during the outbreak, I can clearly remember the days where not only were there many patients being admitted during the outbreak, but also the frontline healthcare teams were increasingly also catching the virus. This pandemic has prompted many nurses to retire and the unit short staffed every day. Accompanied with the staff shortage is the constant PPE and infection disease management policy changes. Dealing with the unknown, often puts people in a vulnerable risk for infection and psychological effects that should be monitored and understood. This would then assist in protecting the frontline workers and research ways to increase resilience amidst the pandemic outbreak.
While being a healthcare worker as well as a being a frontline employee, stress becomes an inevitable part of our job. In a linear regression study done by Tayyib & Alsolami (2020), the role of RNs have potentially exposed them infection and its associated consequences. This study was done to assess the physiological effects of fear, stress, and level of resilience in response to Covid-19 outbreaks. In this study, questionnaires were conducted during the outbreak including sociodemographic details, job related stress, and fear of infection; the data analyzed used descriptive correlation studies and linear regression studies. In the study result, about 314 nurses (87%) who responded to survey showed that the higher the outbreaks the higher the level of anxiety and stress during the outbreaks (mean 7.61, SD + 2.72); reporting high risk of being infected (mean 7.6, SD+ 2.72), causing stress at work (mean 6.92, SD + 2.91), and falling ill (mean 6.72, SD + 2.98). The predictive factors included social media (0.76, p= 0.03), exposure to trauma prior to outbreak (-0.95, p=0.003), and readiness of care (-0.21, p=0.001). these factors have significant impact on an RN’s psychological status which may affect the quality of patient care.
The strength of this article is that it takes into account the important aspects that should be considered regarding RNs’ perceived high level of fears and stress are the coping measures that should be taken during and after this time to help alleviate post-traumatic stress and increase their emotional resilience. The weakness of this article includes the need for further longitudinal prospective studies to capture the large population and different time series recommended to validate this study further and provide a more thorough understanding of this issue. Furthermore, it would be more beneficial to research on factors that affect their level of stress and fears during such times. Supportive interventions need to be introduced to ensure resilience among staff and ensure quality patient care.
Reference(s)
Sathwick, S. (2020). What is a linear regression? Data Science. Retrieved from
https://towardsdatascience.com/the-concepts-behind-linear-regression-and-its-implementation-ffbab5a4d65e
Statistic Solution (2020). What is linear regression? Stat Solution Dissertation. Retrieved from
Tayyib, N. & Alsolami, F. (2020). Measuring the extent of stress and fear among registered
nurses in KSA during the Covid-19 outbreak. Journal of Taibah University Medical Sciences. 15(5). 410-416. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7462892/
A Sample Answer 3 For the Assignment: NURS 8201 Week 7 Discussion Use of Regression Analysis in Clinical Practice ANSWERS
Title: NURS 8201 Week 7 Discussion Use of Regression Analysis in Clinical Practice ANSWERS
Regression analysis is one of the statistical models used in estimating the relationship between variables. The researcher has the ability to determine the effect that an independent variable has on the dependent variable (Willis & Riley, 2017). For example, an increase in one or more values on the independent variable would have an effect on the dependent variable. This paper examines regression analysis was used by an author including its weaknesses and strengths.
Article Summary
The article authored by Hatakeyama et al., (2019) aimed at finding the relationship between quality of clinical practice guideline (CPGs) and overall assessment scores. This study considered the previous studies that had been done and published between 2011 and 2015. These selected studies were subjected through an independent valuation using AGREE II. The author analyzed the results using a regression analysis. For instance, the analysis included the effect that the six domains and 23 items has on the overall assessment. The study collected a total of 206 CPGs and correlated all the domains to the items on the overall assessment to determine the strength of the relationship before taking the regression analysis on the proposed items.
Use of Regression on the Article
The author decided to subject domain 3, domain 4, domain 5, and domain 6 of the regression analysis. Domain three represented rigor of development, domain four was for clarity of presentation, domain five was for applicability and finally domain 6 was for editorial independence. The analysis was majoring on how these domains influence the overall assessment (Hatakeyama et al., 2019). The analysis showed that all the domains had a significant relationship with the overall assessment. The author also found that four different items on AGREE II, which were item 8, 15, 19 and 22 had an effect on overall assessment. The regression analysis showed that the change in one unit of the items above had a significant change on the overall assessment which in this case acted as the dependent variable (Hatakeyama et al., 2019). Therefore, the improvement of overall assessment dependent on the increase and decrease of the items that acted as independent variables in this case.
Other statistical analysis that could have been used in the study is ANOVA analysis because it shows the strength of the relationship between the items selected. Besides, it allows the researcher to determine the effect that each dependent variables have on each other and how the relationship between the dependent variables can influence the study (Fontaine et al., 2019). Use of ANOVA tests in this study could have strengthened and relayed more information on the collection of items that could have a great impact on the overall assessment.
The strength of the regression analysis is on the ability of the author to examine more than one dependent variable. According to the study the author was interested in 22 items and their effect on overall assessment. The study is able to report on the influence of 22 items more easily as compared to other methods that could have been complex (Hatakeyama et al., 2019). Despite the strength that regression analysis has on the study, the method also has its weakness it lacks the ability to examine the relationship between the independent variables considered in the study.
Conclusion
Regression analysis is a powerful tool in assessing the relationship between dependent and independent variables. The author in the selected the study has the ability to evaluate which of the 22 items have a high or low effect on the overall assessment.
References
Fontaine, G., Cossette, S., Maheu-Cadotte, M. A., Deschênes, M. F., Rouleau, G., Lavallée, A., … & Mailhot, T. (2019). Effect of implementation interventions on nurses’ behaviour in clinical practice: a systematic review, meta-analysis and meta-regression protocol. Systematic reviews, 8(1), 1-10. https://doi.org/10.1186/s13643-019-1227-x
Hatakeyama, Y., Seto, K., Amin, R., Kitazawa, T., Fujita, S., Matsumoto, K., & Hasegawa, T. (2019). The structure of the quality of clinical practice guidelines with the items and overall assessment in AGREE II: a regression analysis. BMC health services research, 19(1), 1-8. https://doi.org/10.1186/s12913-019-4532-0
Willis, B. H., & Riley, R. D. (2017). Measuring the statistical validity of summary meta‐analysis and meta‐regression results for use in clinical practice. Statistics in medicine, 36(21), 3283-3301. https://doi.org/10.1002/sim.7372
NURS 8201 Week 7 Discussion Use of Regression Analysis in Clinical Practice ANSWERS Grading Rubric Guidelines
| Performance Category | 10 | 9 | 8 | 4 | 0 |
| Scholarliness
Demonstrates achievement of scholarly inquiry for professional and academic decisions. |
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| Performance Category | 10 | 9 | 8 | 4 | 0 |
| Application of Course Knowledge –
Demonstrate the ability to analyze, synthesize, and/or apply principles and concepts learned in the course lesson and outside readings and relate them to real-life professional situations |
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| Performance Category | 5 | 4 | 3 | 2 | 0 |
| Interactive Dialogue
Replies to each graded thread topic posted by the course instructor, by Wednesday, 11:59 p.m. MT, of each week, and posts a minimum of two times in each graded thread, on separate days. (5 points possible per graded thread) |
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Summarizes what was learned from the lesson, readings, and other student posts for the week. |
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| Minus 1 Point | Minus 2 Point | Minus 3 Point | Minus 4 Point | Minus 5 Point | |
| Grammar, Syntax, APA
Note: if there are only a few errors in these criteria, please note this for the student in as an area for improvement. If the student does not make the needed corrections in upcoming weeks, then points should be deducted. Points deducted for improper grammar, syntax and APA style of writing. The source of information is the APA Manual 6th Edition |
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| 0 points lost | -5 points lost | ||||
| Total Participation Requirements
per discussion thread |
The student answers the threaded discussion question or topic on one day and posts a second response on another day. | The student does not meet the minimum requirement of two postings on two different days | |||
| Early Participation Requirement
per discussion thread |
The student must provide a substantive answer to the graded discussion question(s) or topic(s), posted by the course instructor (not a response to a peer), by Wednesday, 11:59 p.m. MT of each week. | The student does not meet the requirement of a substantive response to the stated question or topic by Wednesday at 11:59 pm MT. |
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