# STATISTICAL ANALYSIS IN NURSING NURS 8201

## Sample Answer for STATISTICAL ANALYSIS IN NURSING NURS 8201 Included After Question

“An essential component of nursing education is ensuring students develop the competencies in the use of empirical evidence in their clinical practice. The fundamental goal of statistics courses is to teach healthcare professionals the proper uses of statistical thinking to enable them to effectively evaluate the literature and integrate evidence into their practice” (Baghi & Kornides, 2014).

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How are research methods used in nursing? What particular methods are used in your area of nursing practice? Over the last few weeks, you have been exploring these questions, and you will continue this exploration examining the specific tests and methods that may be used in your particular area of nursing practice. Why might different methods be used based on an area of practice? Why is it important for DNP-prepared nurses to be familiar with various research methods?

For this Discussion, reflect on the tests and methods utilized in research studies, presented over the last eight weeks of the course, to consider the approach, impact, and purpose of these in conducting nursing research. Using a selected article, consider the approach used and reflect on how that approach might fits within your area of nursing practice.

Reference: Baghi, H., & Kornides, M. (2013). Current and future health care professionals attitudes toward and knowledge of statistics: How confidence influences learning. Journal of Nursing Education Practitioners 3(7), 24–29 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4239707/

## To Prepare:

• Review the articles presented in this week’s Learning Resources and analyze each study’s use of statistical and nonparametric tests.
• Select an article to focus on for this Discussion.
• Ask yourself: Which method is most commonly used in research studies that pertain to my area of nursing practice, and why this might be so?

## By Day 3 of Week 8

Post a critical analysis of the article that you selected by addressing the following:

• What are the goals and purpose of the research study described by the article you selected?
• How are nonparametric tests used in the research study? What are the results of their use? Be specific.
• Why are parametric methods (t tests and ANOVA) inappropriate for the statistical analysis of the research study’s data? Be specific and provide examples.
• What are the strengths and weaknesses of the research study (e.g., study design, sampling, and measurement)?
• How could the findings and recommendations of the research study contribute to evidence-based practice for nursing?

## By Day 6 of Week 8

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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.
• 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.

### Week 8 Discussion Rubric

STATISTICAL ANALYSIS IN NURSING NURS 8201

Post by Day 3 of Week 8 and Respond by Day 6 of Week 8

## Title: STATISTICAL ANALYSIS IN NURSING NURS 8201

The article chosen for this discussion is an article by Leigh et al.(2020). The goal and purpose of this article were to explore the predictors of emergency nurses’ protection motivation during the West African Ebola outbreak. This is an example of an article where nonparametric tests were used. For example, the Kruskal-Wallis H test was used in the analysis of the connection between the categorical independent variables like employment, licensure, education level, race, age groups, gender, and other variables related to protection motivation theory. The analysis gave important results. An example is the relationship between gender and psychological variables, which were analyzed.  From the Kruskal-Wallis H test, the self-efficacy χ² value was 11.74, indicating a significance at p<0.005. Male respondents also have a substantially higher self-efficacy as shown from post hoc Dunn-Bonferroni tests.

It is evident that this research did not use parametric methods such as ANOVA and t-test since they were inappropriate for the statistical analysis of the research study’s data. One of the reasons is that parametric tests assume that data usually follow normal distribution; as such, in case the data fails to follow such a trend (Grey & Grove, 2020), then parametric tests can lead to inaccurate results. A typical example from the paper is the case where the Kruskal-Wallis H test was used to explore the distribution of psychological variables in different age groups, as it doesn’t have to make an assumption that the data is normally distributed. ANOVA also assumes homogeneity of variance; hence, it may not be reliable when such an assumption does not hold (Orcan et al.,2020).

This study has various strengths. One of them is the sample size. The sample size was 388, which is sufficient, hence enhancing generalizability. There is also diversity in educational levels and age groups. The use of nonparametric tests such as Spearman rho correlation and Kruskal-Wallis H test in data analysis shows a robust approach (Juang, 2021). One weakness is that the cross-sectional design used limits the ability to explore the causal relationships between variables. It is also vulnerable to response bias as data collection relies on self-reported information. The findings and recommendations of this research study can contribute to EBP for nursing in that stakeholders can formulate tailored preparedness strategies by identifying factors that influence nurses’ perceptions.

## References

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.

Jiang, J. (2021). Nonparametric statistics. In Large Sample Techniques for Statistics (pp. 379-415). Cham: Springer International Publishing. Doi: 10.1007/978-3-030-91695-4_11

Leigh, L., Taylor, C., Glassman, T., Thompson, A., & Sheu, J. J. (2020). A cross-sectional examination of the factors related to emergency nurses’ motivation to protect themselves against an Ebola infection. Journal of Emergency Nursing46(6), 814-826. https://doi.org/10.1016/j.jen.2020.05.002Links to an external site.

Orcan, F. (2020). Parametric or nonparametric: Skewness to test normality for mean comparison. International Journal of Assessment Tools in Education7(2), 255-265. https://doi.org/10.21449/ijate.656077

## Title: STATISTICAL ANALYSIS IN NURSING NURS 8201

Thanks for participating in this week’s discussion. Your post is fascinating and I learned a lot from your in-depth discussion.  According to Polit and Beck (2017), data-collecting plans aid in producing reliable, valid, and significant data. The results of this study should be supported by evidence for future nursing practice and interventions. I feel that, in attempting to gauge patient satisfaction with my existing organization, it would be more advantageous to gather data quantitatively utilizing this approach. A cross-sectional study is the topic of the article you have chosen to discuss today. Investigation of the Elements Associated with Emergency Nurses’ Willingness to Defense Against an Ebola Contagion using a Cross-Sectional Approach (Leigh, 2020). Examining the factors that influence emergency nurses’ motivation for protection is the aim of this research. This study aims to determine what and how emergencies, like the Ebola outbreak in West African countries, inspire nurses to take protective measures for themselves. The two types of tests used to test research are parametric and non-parametric tests (changingminds.org, 2016). According to changingminds.org (2016), non-parametric designs do not fit the usual bell curve, however, parametric designs may be statistically defined as bell-shaped and have standard dissemination that allows for more inferences. In contrast to non-parametric testing, which uses ordinals or nominals and measures the median to allow for simplicity and be less impacted by variables, parametric testing examines data that is ratio or interval and measures the mean to make more conclusions, according to Changingminds.org (2016).

Stepwise multiple linear regression, Spearman rho correlation, post hoc Dunn-Bonferroni test (which produces t values), and nonparametric Kruskal-Wallis H test (which produces χ2 values) were all carried out with SPSS version 26. We chose this approach because it produced accurate data devoid of conjecture. The information provided by all of the ER nurses’ participants strongly predicts the protective motivation of emergency nurses.

For statistical analyses of research studies, parametric tests like the t-test and ANOVA are inappropriate because they require that the populations under study have the same type of variance, that the variables being tested and measured have been measured at the same scale of intervals, and that the populations are not still valid on small data sets. The mean and its deviation are two examples of the data used in a parametric correlation.

Utilizing a cross-sectional research design and having it authorized by the institutional review board of the University of Toledo and the head of the Institute for Emergency Nursing Research was a strength of the study. The random selection of emergency nurses, which includes ENA members, is one of the weaknesses. The findings’ external validity could be jeopardized by the possibility that ENA members do not accurately reflect all emergency nurses in the US geographically. The current findings represent a generous assessment of the nurses’ incentive to protect themselves when providing care to potential patients with Ebola virus, however, it may be expected that ENA members might be experienced and professionally dedicated. The nurses’ incentive to follow precautionary measures when tending to patients who may be infected with the disease may also have been impacted by the timing of the Ebola outbreak. Since the study’s goal was to provide intervention to increase emergency nurses’ knowledge, self-efficacy, and response efficacy while also lowering their perceived vulnerability and response cost, its conclusions and recommendations may help advance evidence-based practice in nursing. When nurses are caring for patients in emergencies, as the coronavirus pandemic the globe is currently experiencing, it would be expected that such interventions will proactively inspire them to protect themselves..

## References

Bailey, J., McVey, L., & Pevreal, A. (2005). Surveying patients as a start to quality improvement in the surgical suites holding area. Journal of Nursing Care Quality, 20(4), 319-326

Leigh, L., Taylor, C., Glassman, T., Thompson, A., & Sheu, J-. J. (2020). A cross-sectional examination of the factors relating to emergency nurses’ motivation to protect themselves against Ebola infection. Journal of Emergency Nursing, 46(6) 814-826.

Polit, D. F., & Beck, C. T. (2017). Nursing research: Generating and assessing evidence for nursing practice (10th ed.). Philadelphia, PA: Wolters Kluwer

## Title: STATISTICAL ANALYSIS IN NURSING NURS 8201

### Introduction

The selected article outlines a research study with the stated goal of determining what drives American emergency nurses to adopt protective measures against working with Ebola patients. A modified version of the Protection Motivation Theory (PMT) was employed in this study to examine the associations and predictors of the nurses’ motivation to adopt Ebola precautions based on multiple psychological traits (Leigh et al., 2020). The purpose of this study is to investigate the relationship between emergency nurses’ anxiety of treating Ebola patients and the psychological elements that encourage them to adopt preventative measures during outbreaks.

## Utilizing statistics

The group uses nonparametric testing in their statistical analysis. Because the data in this study do not meet the normalcy assumptions of parametric testing, nonparametric tests are used. Whereas Fisher’s exact and chi-square tests are used to compare categorical variables, the Wilcoxon rank-sum test is used to compare continuous variables between groups. Empirical research indicates a strong correlation between emergency nurses’ psychological traits and their inclination to stop the spread of Ebola. Nonparametric tests such as the post hoc Dunn-Bonferroni and Kruskal-Wallis H tests are used to assess the demographic and PMT construct data. The nonparametric Kruskal-Wallis H test was used to determine whether there was a statistically significant difference between the sexes. According to Dunn-Bonferroni post hoc tests, respondents who were male showed higher levels of self-efficacy; nevertheless, the response cost for female nurses was higher. In terms of perceived vulnerability, response cost, and passive protection motivation, the results also differ significantly throughout the age range that was studied. For this study’s statistical analysis, non-normal data means that nonparametric procedures (tests and ANOVA) are out of place. The study utilized nonparametric tests such as Kruskal-Wallis and Spearman’s rho correlation, which are chosen because they conservatively identify relationships without presuming normalcy. Given that some of the study’s variables are ordinal, parametric tests are likewise improper. While tests like the Wilcoxon rank-sum test are used to compare continuous variables across groups, chi-square, and Fisher’s exact tests are used to analyze the significance of a relationship between categorical variables(Gray, Grove, & Sutherland, 2020)

## Strength and Weaknesses

The study’s various aspects include its use of a modified version of the partial-merit theory (PMT) model to analyze the psychological elements that affect emergency nurses’ desire to take precautions during outbreaks. A high sample size helps this research since it can more precisely represent the population. One drawback of the study is that it is cross-sectional, which makes inferring causal relationships challenging. Since the study exclusively examined 2015 enrollees in the Emergency Nurses Association, its conclusions may not be generalizable to the profession as a whole (ENA). Ten demographic and construct-specific components make up the survey, which is validated by subject-matter specialists and a focus group. Furthermore, a three-phase mailing approach is employed in the study to enhance the quantity of replies. The likelihood that the sample of nurses in this study is not representative of all emergency nurses in the US is one of the study’s shortcomings, which would limit how broadly the results can be applied. Given the date of the Ebola epidemic, nurses may have been more careful when treating patients, which could have contributed to the slower-than-usual response time.

## Utilizing Statistical Method/Conclusion

The findings and recommendations of the study offer insight into the psychological elements that influence nurses’ motivation to defend themselves against Ebola patients, potentially advancing evidence-based nursing practice. Proactive protection motivation was revealed to be affected by nurses’ self-efficacy and response efficacy, but passive protection motivation was found to be affected more by nurses’ perceived vulnerability, response cost, and knowledge. According to the study’s authors, hospitals and clinics should establish protocols for admitting Ebola patients, train and observe nurses, stockpile respirators, impermeable disposable gowns and coveralls, extended cuff disposable examination gloves, boot covers, disposable aprons, and more.

## 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. Chapter 25,”Using Statistics to Determine Differences” (pp. 687-698)

Leigh, L., Taylor, C., Glassman, T., Thompson, A., & Sheu, J. J. (2020). A cross-sectional examination of the factors related to emergency nurses’ motivation to protect themselves against an Ebola infection. Journal of Emergency Nursing, 46(6), 814-826.

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