# NURS 8201 Week 5 Discussion t-Tests and ANOVA in Clinical Practice ANSWERS

## Sample Answer for NURS 8201 Week 5 Discussion t-Tests and ANOVA in Clinical Practice ANSWERS Included After Question

Statistics provide a variety of information that can shape healthcare. Statistics can indicate disparity in care, effectiveness of treatments plans, and predict future outcomes. As a future DNP-prepared nurse, understanding how to analyze and interpret statistics will provide you the opportunity to utilize research in directing patient care and implementing procedures to ultimately improve patient success.

When comparing patients, treatment methods, or healthcare practices, it will be important to consider differences amongst groups. Statistics give us the opportunity to explore and determine these differences to properly analyze the data, make recommendations, or determine treatment options. As a DNP-prepared nurse, using statistics to determine differences may assist you in making the best decisions for your patients and practice.
This week, you will examine the use of inferential statistics in research. You will also consider the strengths and weaknesses of using both t-tests and ANOVA.

## Students will: • Analyze the use of t-tests, ANOVA, and inferential statistics in research and evidence-based practice • Evaluate strengths and weaknesses of inferential statistics in supporting evidence-based practice • Interpret results and output from t-tests and ANOVA • Summarize ANOVA Statistics ________________________________________ Learning Resources

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)

Donovan, L. M., & Payne, C. L. (2021). Organizational commitment of nurse faculty teaching in accelerated baccalaureate nursing programs. Nursing Education Perspectives, 42(2), 81–86. doi:10.1097/01.NEP.0000000000000764

Gray, J. A., & Kim, J. (2020). Palliative care needs of direct care workers caring for people with intellectual and developmental disabilities. British Journal of Learning Disabilities, 48(1), 69–77. doi:10.1111/bld.12318

Hilvert, E., Hoover, J., Sterling, A., & Schroeder, S. (2020). Comparing tense and agreement productivity in boys with fragile X syndrome, children with developmental language disorder, and children with typical development. Journal of Speech, Language and Hearing Research, 63(4), 1181–1194. doi:10.1044/2019_JSLHR-19-00022

Document: Week 5 ANOVA Exercises SPSS Output (PDF)

## ________________________________________ Discussion: t-Tests and ANOVA in Clinical Practice

You are the DNP-prepared nurse responsible for overseeing staffing for the telehealth services provided at your practice. To determine the number of nurses that you might need for these services, you must determine how many patients might be interested in using the telehealth services versus the traditional clinical practice setting. For a week, you ask each patient visiting the practice his or her interest in setting up a visit via telehealth services. At the conclusion of the week, you use this data and reasoning to develop a statistic of the population interested in telehealth services. You have successfully used inferential statistics to help guide your decision-making for your practice.

Photo Credit: fizkes / Adobe Stock
The scenario outlined provides a random sampling and assumptions to develop a conclusion. With assumptions, and in this case, a small random sampling, this scenario is ripe with the possibility of error. However, how might inferential statistics be used in a valid and credible way?
The design of a study determines the validity of the results, and if done following appropriate techniques, inferential statistics can determine clear differences and help researchers to form conclusions. In your Discussion, you will focus on two forms of identifying differences in groups: t-tests and analysis of variance (ANOVA).
For this Discussion, review the Learning Resources and reflect on a healthcare issue of interest to find a research article in which to analyze the use of inferential statistical analysis. Reflect on how the study was comprised, the validity of the findings, and whether or not it increased the study’s application to EBP

## To Prepare:

• Consider some of the important issues in healthcare delivery or nursing practice today. Bring to mind the topics to which you have been exposed through previous courses in your program of study, as well as any news items that have caught your attention recently. Select one topic to focus on for this Discussion.
• Review journal, newspaper, and/or internet articles that may provide credible information on your selected topic. Then, select one research article to focus on for this Discussion that used inferential statistical analysis (either a t-test or ANOVA) to study the topic.
• With information from the Learning Resources in mind, evaluate the purpose and value of the research study discussed in your selected article and consider the following questions:
o Who comprised the sample in this study?
o What were the sources of data?
o What inferential statistic was used to analyze the data collected (t-test or ANOVA)?
o What were the findings?
• Ask yourself: How did using an inferential statistic bring value to the research study? Did it increase the study’s application to evidence-based practice?

## By Day 3 of Week 5

Post a brief description of the topic that you selected for this Discussion. Summarize the study discussed in your selected research article and provide a complete APA citation. Be sure to include a summary of the sample studied, data sources, inferential statistic(s) used, and associated findings. Then, evaluate the purpose and value of this particular research study to the topic. Did using inferential statistics strengthen or weaken the study’s application to evidence-based practice? Why or why not? Be specific and provide examples.

## By Day 6 of Week 5

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 5 Discussion Rubric

Post by Day 3 of Week 5 and Respond by Day 6 of Week 5

To Participate in this Discussion:
Week 5 Discussion

## ________________________________________ Assignment: t-Tests and ANOVA

You are a DNP-Prepared nurse tasked with evaluating patient care at your practice compared to patient care at affiliated practices. You have noticed that a key complaint from your patients concerns the wait times associated with each patient visit. Based on these complaints, you have decided to compare the wait times at your practice to the wait times at affiliated practices. After recording the wait times at each practice, for 50 individual patients at each practice, you are now prepared to analyze your data. What approach will you use to analyze the data?

Photo Credit: Dave and Les Jacobs / Blend Images / Getty Images
In the scenario provided, you might decide to use, the Analysis of Variance (ANOVA) approach. “ANOVA is a statistical procedure that compares data between two or more groups or conditions to investigate the presence of differences between those groups on some continuous dependent variable” (Gray & Grove, 2020). ANOVA is often a recommended statistical technique, as it has low chance of error for determining differences between three or more groups.
For this Assignment, analyze the ANOVA statistics provided in the ANOVA Exercises SPSS Output document. Examine the results to determine the differences and reflect on how you would interpret these results.
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 Week 5 ANOVA Exercises SPSS Output provided in this week’s Learning Resources.
• Review the Learning Resources on how to interpret ANOVA results to determine differences.
• Consider the results presented in the SPSS output and reflect on how you might interpret the results presented.
The Assignment: (2–3 pages)
• Summarize your interpretation of the ANOVA statistics provided in the Week 5 ANOVA Exercises SPSS Output document.
o Note: Interpretation of the ANOVA output should include identification of the p-value to determine whether the differences between the group means are statistically significant.
o Be sure to accurately evaluate each of the results presented (descriptives, ANOVA results, and multiple comparisons using post-hoc analysis)
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.

### By Day 7

Submit your Assignment by Day 7 of Week 5.
To submit your completed Assignment for review and grading, do the following:
• Please save your Assignment using the naming convention “WK5Assgn+last name+first initial.(extension)” as the name.
• Click the Week 5 Assignment Rubric to review the Grading Criteria for the Assignment.
• Click the Week 5 Assignment link. You will also be able to “View Rubric” for grading criteria from this area.
• Next, from the Attach File area, click on the Browse My Computer button. Find the document you saved as “WK5Assgn+last name+first initial.(extension)” and click Open.
• If applicable: From the Plagiarism Tools area, click the checkbox for I agree to submit my paper(s) to the Global Reference Database.
• Click on the Submit button to complete your submission.

Week 5 Assignment Rubric

Check Your Assignment Draft for Authenticity

To check your Assignment draft for authenticity:
Submit your Week 5 Assignment draft and review the originality report.

Submit Your Assignment by Day 7 of Week 5

To participate in this Assignment:
Week 5 Assignment

### ________________________________________ What’s Coming Up in Week 6?

Photo Credit: [BrianAJackson]/[iStock / Getty Images Plus]/Getty Images
Next week, you will continue your exploration of quantitative data. You will explore correlations and consider when it is best to utilize this statistical approach for quantifying relationships between variables.
Next Week

## Title: NURS 8201 Week 5 Discussion t-Tests and ANOVA in Clinical Practice ANSWERS

The research chosen for this discussion was conducted to evaluate the intensive care nurse attitudes on evidence-based nursing. Nurse introduction forms and evidence based-questionnaires were used to collect data on 70 nurses in public hospitals. Evaluation of the data r using ANOVA revealed that “ the mean score based on the questionnaires was 57.20±9.06, while the highest score of attitudes was (26,97±5,50) is in the sub-dimension of beliefs and expectations towards evidence-based nursing” (Dikmen et al., 2018).

A positive correlation between the data variables using ANOVA analysis suggested that nurses positively affect intensive care. However, a comparison between nurse education and duration in the intensive care unit had no significant difference.
Nurses constitute the largest group of professionals in the healthcare industry. Research on their attitudes towards evidence-based nursing in intensive care is essential to evaluate the best practices and adapt them to their practice (Liyew et al., 2020). Determining the nurse attitudes facilitates developing strategies that raise evidence-based nursing practice in the areas (Dikmen et al., 2018).

Additionally, nurses need to keep updated through regular journals of scientific research methods to maintain a positive attitude towards evidence-based nursing.
The inferential statistics in the paper played a significant role in examining the rate of nurses who are positive towards evidence-based nursing practices in the intensive care unit. The use of inferential analysis helps generate a solid explanation of the situation.

Conclusions are drawn based on extrapolation using descriptive statistics of the data collected. Therefore the inferential statistics strengthened the study application on evidence-based practices by identifying the relationship between the data variables collected (Hare, 2020). Evaluation of the data collected through the forms and the questionnaires suggests that nurses are positive towards evidence-based nursing in intensive care units.

## Reference

Dikmen, Y., Filiz, N. Y., Tanrıkulu, F., Yılmaz, D., & Kuzgun, H. (2018). Attitudes of intensive care nurses towards evidence-based nursing. International Journal of Health Sciences and Research, 8(1), 138-143.
Hare, K. A. (2020). Evidence-based end-of-life care education for intensive care nurses (Doctoral dissertation, Walden University).
Liyew, B., Dejen Tilahun, A., & Kassew, T. (2020). Knowledge, attitude, and associated factors towards physical assessment among nurses working in intensive care units: a multicenter cross-sectional study. Critical Care Research and Practice, 2020.https://doi.org/10.1155/2020/9145105

## Title: NURS 8201 Week 5 Discussion t-Tests and ANOVA in Clinical Practice ANSWERS

Statistics play an important role in analyzing the primary data collected to examine a problem in clinical practice. Despite its complexity, it allows the researcher to deduce the meaning of the data to support evidence-based practice (Weaver et al., 2017). The precision required in nursing studies has led to a demanding task among nursing scholars. These demands have compelled them to use inferential statistical analysis to achieve the accuracy and dependability of the results.

My topic of interest is to examine the prevalence of obesity among children. The increase in cases of childhood obesity has been drawing more attention from scholars because of its negative effect on health outcomes among children (Smith et al., 2021). The number of children with obesity has doubled in the last two decades, calling for effective intervention that would counter this menace. The increased rate of children with obesity calls for accurate studies that would reveal the underlying problem and propose an effective EBP practice that would act as an effective intervention for the problem.

## Article Summary

The study authored by Katzmarzyk et al. (2019) focuses on the effect of lifestyle behavior and environment on childhood obesity. The study’s primary objective was to examine the relationship between lifestyle behaviors and obesity. The study termed as ISCOLE was a multi-national study carried out on children aged 9-11 years from 12 countries across the continent. The primary focus of the study was on the result gained from the primary data collected for this study. 7372 children aged between 9-11 years participated in the study. The study used ISCOLE design and methods, which was a multi-national study done in 12 countries.

Inferential statistics separated the data from countries where the reading on the Human Development Index (HDI) produced a range of 0.509 in Kenya to 0.929 in Australia (Katzmarzyk et al., 2019). The descriptive statistics effectively organized data from each country and showed how the variables considered in the study changed in each country. The study also went further to correlate obesity and lifestyles behavior at different levels, where it found that children with active school transport had lower chances of becoming obese. For instance, the odds ratio was 0.72 at a 95% confidence interval. In essence, inferential statistics was important in breaking down the data from the 12 countries into meaningful pieces that readers could easily understand.

This study was important in revealing how various factors such as average income in a country affect the lifestyle behaviors in families that further relay more information on childhood obesity. The analysis of the big sampled data from the countries resulted in reliable information that could be applied to all the countries included in the study (Katzmarzyk et al., 2019). Inferential statistics in the study strengthened the results by revealing the relationship between dependent variables and multiple independent variables considered in the study. The analysis used in the study strengthened the application of the evidence-based practice as it showed the effect that lifestyle changes had on childhood obesity. For example, the study proved that increasing physical activity among children during school hours and at home reduces their chances of becoming obese. Therefore, if children and parents in the selected countries with high childhood obesity could adopt the EBP practice of increasing physical activity, then the prevalence rates in those countries could decrease drastically.

The importance of inferential statistics could also be evident in the correlation of the variables that had a greater effect on childhood obesity and those variables that had a comparatively lower impact on obesity. For example, the study found a high correlation between physical activity and obesity. On the other hand, the study found that school transport and obesity did not differ by country or sex.

## Reference

Katzmarzyk, P. T., Chaput, J. P., Fogelholm, M., Hu, G., Maher, C., Maia, J., … & Tudor-Locke, C. (2019). International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE): contributions to understanding the global obesity epidemic. Nutrients11(4), 848. https://dx.doi.org/10.3390%2Fnu11040848

Smith, H. J., Piotrowski, J. I., & Zaza, S. (2021). Ethics of implementing US Preventive Services Task Force recommendations for childhood obesity. Pediatrics148(1). https://doi.org/10.1542/peds.2020-048009.

Weaver, K. F., Morales, V. C., Dunn, S. L., Godde, K., & Weaver, P. F. (2017). An introduction to statistical analysis in research: with applications in the biological and life sciences. John Wiley & Sons.

## Title: NURS 8201 Week 5 Discussion t-Tests and ANOVA in Clinical Practice ANSWERS

### Topic: Risk and factors of nursing burnout among ICU nurses

Since entering the career of nursing, I believe that most nurses would like to gather as much experience as they can to become a proficient and well-rounded staff in this profession. Being a nurse for about six years now, I have spent the last two and a half years working my way up to become an intensive care unit (ICU) nurse. Being an ICU nurse is a specialty in itself that provides many nursing with the competitive pay, comprehensive benefits, and extensive learning experience in critical level of care. As the ICU can be a stressful environment for patients and families, with established long term consequences, the impact that this unique environment can have on healthcare professionals is increasingly being recognized.

What I have noticed while being a nurse in the critical care environment, I have noticed a significant increase in our nurse turnover rates for both local and traveling nurse staff. For as long as I have been working in this hospital (in a different unit at the time), many nurses are either not trained properly and/or experiencing burnout early on in their career due particularly in the ICU unit. The exposure of  nurses within a high acuity nursing environment without the proper support from our management has led to burnout. Furthermore, I have noticed that the ICU unit is the only unit with the least amount of local nurses that stay employed for at least two years into their career life.

Most of the staff nurses that I have worked with have expressed the desires to leave off-island in search for better opportunities or change in nursing career. Our hospital is going through a constant battle with recruiting and retaining their nursing staff, specifically more significant in the ICU unit. Our medical director is currently working alongside the hospital administrators about looking for ways to address the increase burnout that the staff nurses are experiencing and construct a resilient healthcare system. For as long as I have been working in this hospital (in a different unit at the time), many nurses are either not trained properly with the advanced skills needed dealing with life threatening illnesses and/or lack the skills to tackle critically ill conditions. As a result overall, burnout causes decrease in quality of care, poor performances, increase mortality in patients, and errors in the healthcare environment.

The impact that this unique environment can have on healthcare professionals is increasing therefore, as a DNP prepared nurse, to gain a more complete understanding of critical care well-being requires commitment to measure, develops interventions, and re-measure them. An analysis variation or ANOVA tests done for each survey or experimental results are significant and help us figure out if the studies prove our hypothesis. Inferential statistics takes data from samples and make generalizations about a population. Experimental analysis using t-test, to compare the means of two groups or ANOVA (analysis of variance) to analyze the difference between the means of more than two groups, would help make estimates about the population at study (nurses) and testing hypothesis to draw conclusions (Bhandari, 2020).

One of the chosen inferential articles that describe the prevalence of burnout in the ICU healthcare assessed in the included analysis of variance study (ANOVA) through PubMed, Medline, and a web of sciences article reviews and observational study designs. Within the articles, the most commonly used instruments for data collection include the Maslach burnout inventory (MBI), professional quality of life scale, work related behavior, and experience patterns. According to a 4 large scale research study reported that the burnout prevalence rates ranges between 28%-61%; this study suggests that ICU workers were slightly (about 20%) more prone to burnout than the average healthcare (Chuang, Tseng, Lin, Lin & Chen, 2016). The following risk factors reported include: age, sex, marital status, personality traits, work experiences, work environment, workload, shift work, ethical issues, and decision making choices.

In another article review done by Kerlin, McPeake & Mikkelsen (2020), being that ICU can be a stress environment for both patients and families; the impact that this environment can have on healthcare environment is being increasingly recognized. Challenging situations, exposure to high mortality and daily difficult workloads can lead to excessive stress and resultant in moral distress, leading to burnout syndrome. This cross-sectional study, most critical care nurses experience about 81% of one or more burnout symptoms. The framework presented in this article implies that multidisciplinary and coordinated cares are essential components to high quality critical care delivery. The publications are assessed for relevance to using data to support observational study designs that examine associations between any risk factors and burnout in the ICU setting.

In a systematic meta-analysis done by Ramirez-Elvira et.al. (2021), the ANOVA is  carried out with different articles and journals from Medline and CINAHL following the PRISMA (preferred reporting item for systematic reviews and meta-analysis), with a sampling of N= 1989; there was an estimate of about 31% prevalence for high emotional exhaustion, 18% high depersonalization, and 49% low personal achievement (p.2). Furthermore, in an inferential statistical cross-sectional total population study among N=60 nurses using a self-administered MBI questionnaire resulted into a high burnout percentage of about 62% (Cishahayo, Nankundwa, Sego, & Bhengu, 2017). Burnout is measured through high emotional exhaustion (48%), high depersonalization (25%), and low personal accomplishment (50%).

On a much larger and international scale, in study done by Bhagavathula et.al. (2018), an institution based teaching hospital with a cross-sectional study conduced among healthcare providers N=500 serving about >50,000 population in Ethiopia; a questionnaire with sociodemographic details using descriptive analysis using correlation and multivariate logistic regression studied ANOVA using survey questionnaires of MBI scale. The overall prevalence of burnout is about 14%, respondents with debility was 53%, increase self criticism of about 56%, and depressive symptoms of about 46%. As a result, the nursing profession was a significant determinant for emotional exhaustion and burnout.

In conclusion, most inferential studies summarized above strengthens the application of evidenced based practices in promoting recruitment and retention policies in decreasing the risk of burnouts. Critical care courses and educational programs should be established by the support faculty to meet the needs of critical care assessments and criteria. Practice variability that necessitates changing for better conditions in a resource limited setting may excavate the underlying factors associated with nursing burnout.

## Reference(s):

Bhagavathula, A., Abegaz, T., Belachew, S., Gebreyohannes, E., Gebresillassie, B., & Chattu, V.

(2018). Prevalence of burnout syndrome among healthcare professionals working at Gondar University Hospital, Ethiopia. Journal of Educational Health Promotion 7(145). Retrieved from https://www.jehp.net/article.asp?issn=2277-9531;year=2018;volume=7;issue=1;spage=145;epage=145;aulast=Bhagavathula

Bhandari, P. (2020). An introduction to inferential statistics. Scribbr Statistics. Retrieved

https://www.scribbr.com/statistics/inferential-statistics/

Chuang, C., Tseng, P., Lin, C., Lin, K. & Chen, Y. (2016). Burnout in the intensive care unit

Cishahayo, E., Nankundwa, E., Sego, R., & Bhengu, B. (2017). Burnout among nurses working

in critical care settings: A case of a selected tertiary hospital in Rwanda. International Journal of Research in Medical Sciences. 5(12). Retrieved from https://www.msjonline.org/index.php/ijrms/article/view/4101

Kerlin, M., Mc Peake, J., & Mikkelsen, M. (2020). Burnout and joy in the profession of critical