# NUR 590 Topic 4 DQ 2 Identify which statistical test you would use in conjunction with your selected research design from DQ 1 to evaluate the outcomes for your evidence-based project proposal and explain why you selected this test

## NUR 590 Topic 4 DQ 2 Identify which statistical test you would use in conjunction with your selected research design from DQ 1 to evaluate the outcomes for your evidence-based project proposal and explain why you selected this test

NUR 590 Topic 4 DQ 2 Identify which statistical test you would use in conjunction with your selected research design from DQ 1 to evaluate the outcomes for your evidence-based project proposal and explain why you selected this test

Click here to ORDER an A++ paper from our Verified MASTERS and DOCTORATE WRITERS: NUR 590 Topic 4 DQ 2 Identify which statistical test you would use in conjunction with your selected research design from DQ 1 to evaluate the outcomes for your evidence-based project proposal and explain why you selected this test

NUR 590 Topic 4 DQ 2

Identify which statistical test you would use in conjunction with your selected research design from DQ 1 to evaluate the outcomes for your evidence-based project proposal and explain why you selected this test. What kind of information will this test provide about your outcomes?

According to Parab & Bhalerao, “statistical tests are mathematical tools for analyzing quantitative data generated in a research study” (2010). There are a number or test that researchers can use which can also become overwhelming and cause confusion for the research, and that can lead to sabotaging and tainting their study. Selecting the statistical test helps the researcher understand what to look for in the study as well as help organize their data. Parab & Bhalerao (2010) stated that “Before selecting a statistical test, a researcher has to simply answer the following six questions, which will lead to correct choice of test:”.

1. How many independent variables covary (vary in the same time period) with the dependent variable?
2. At what level of measurement is the independent variable?
3. What is the level of measurement of the dependent variable?
4. Are the observations independent or dependent?
5. Do the comparisons involve populations to populations, a sample to a population, or are two or more

samples compared?

1. Is the hypothesis being tested comparative or relationship?

Statistical analysis can help you understand the conclusions of a study. The t-test is what I would use. T-tests are inferential statistics used to determine whether there is a significant difference in the means of two groups that may be related by certain features” (Investopedia, n.d.). By displaying the typical nurse-to-patient ratios, this test would assist me in determining if low or high staffing has a positive or negative effect on patient health outcomes.

Statistical tests can be chosen using independent variables and other project designs. I’m seeking for evidence that training caregivers about correct PPE use increases compliance as part of my research. At a minimum, the effects of staff PPE usage models have been identified as a confounding variable. According to Siebert et al., staff modeling and education had a significant influence on visitor compliance (2018). However, there is a test that takes into consideration participant differences.

Because each group contains a diverse set of people, I’ve decided to employ an ANOVA with a mixed design. A mixed design includes “change through time, differences between groups, and the interaction of time and group effects” (Tappen, 2016). This will show the differences between and within groups (e.g., educated vs. uneducated). This tool can be used to compare before and after educational interventions. It will be easy to keep track of how many people are in each category. It could be used to measure the change over time from several points in time if necessary.

Also Read: NUR 590 Topic 4 DQ 1 What are some of the obstacles or barriers to implementing evidence-based practice (EBP) in nursing?

Seibert, G., Ewers, T., Barker, A. K., Slavick, A., Wright, M. O., Stevens, L., & Safdar, N. (2018). What do visitors know and how do they feel about contact precautions? American Journal of Infection. 46(1): 115–117.

Tappen, R. (2016). Advanced Nursing Research. Jones & Bartlett.

When conducting research, it is critical to select the appropriate statistical test because research must maintain validity. Two key points should be considered when performing quantitative data statistical analysis: One is to identify the type of experimental design correctly, and the other is to check whether data meets the preconditions of the parameter test (Liang & Wang, 2019. If these are not taken into account, data can be misused and false conclusions drawn. I thought the Paired T- Test would be the best fit for my project proposal. The Paired T-Test examines the relationship between two variables in the same population. For instance, pre and post test scores. This would allow for a comparison of performance before and after the organizational change implementation was completed. The first variable would be the amount of hands off time during cardiopulmonary resuscitation, while the second variable would be the amount of hands off time during CPR with the implementation of continuous compressions during defibrillation. When these two variables are compared, the conclusion should be that continuous compressions during hands-on defibrillation reduce hands-off time during CPR and improve patient outcomes. Ultimately this test would determine the amount of “hands-off” during CPR comparing standard CPR and continuous compressions during defibrillation.

Click here to ORDER an A++ paper from our Verified MASTERS and DOCTORATE WRITERS: NUR 590 Topic 4 DQ 2 Identify which statistical test you would use in conjunction with your selected research design from DQ 1 to evaluate the outcomes for your evidence-based project proposal and explain why you selected this test

Liang, G., Fu, W., & Wang, K. (2019). Analysis of t-test misuses and SPSS operations in medical research papers. Burns & trauma7.

Quantitative data come from measurements that yield data in numeric form ranging from binary to continuous numeric expressions(Polit, 2017).The statistical test that I would use is a paired T-test. This is a type of Parametric test which is applied when data is normally distributed not skewed (Najmi et al., 2021). The data should be normally distributed and quantitative. This is appropriate for my project which is a quantitative design. The paired T-test is used when one group serves as its own control group. It is used to compare the two means and is used in small samples(Najmi et al., 2021). My project is to reduce CAUTI rates by using patient/family engagement and empowerment. I would use a T-test to compare pre and post intervention CAUTI rates to determine if the intervention was successful in reducing incidence.

Statistical data analysis can be beneficial in a variety of ways, not only in the corporate world, but also in the healthcare sector, particularly in research. To be able to analyze or accurately interpret the data that comes from the results, one must first understand what statistical procedures are and what the concepts underlying them are (Wienclaw, 2021). Regression analysis is the statistical test that I would use to evaluate the outcomes in the evidence-based practice (EBP) project proposal. This is regarded as a trustworthy approach of determining which variables influence the result of the issue of interest. There are various types of regression analysis that can be utilized, with linear regression being one of them.

The specific statistical test that I would apply for my research would be linear regression analysis. This test was chosen because I wanted to see what effect my independent variables (education and lack of education) have on the outcome of my dependent variable (cervical cancer screening rates). The statistical test of linear regression analysis is used to “estimate the correlation of greater than or equal to one independent (predictor) variable with a continuous dependent variable” (Schober & Vetter, 2021, p. 108). An estimate of the effect of my independent variables (education and no education) on my dependent variable is the type of information that this test will reveal concerning my project’s outcomes (cervical cancer screening rates). This will aid in determining the influence of education vs. no education on the rising cervical cancer screening rates among ethnic minority women in my demographic. The use of linear regression analysis can also give me with information on how my two independent variables interact and whether one’s effect is dependent on the value of the other (Schober & Vetter, 2021).

Reference:

Schober, P., & Vetter, T. R. (2021). Linear regression in medical research. Anesthesia & Analgesia, 132(1), 108-109. https://doi.org/10.1213/ANE.0000000000005206

Wienclaw, R. A. (2021). Statistics and data analysis. Salem Press Encyclopedia. https://lopes.idm.oclc.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=ers&AN=89163982&site=eds-live&scope=site&custid=s8333196&groupid=main&profile=eds1

Predictive analytics is a type of data science that goes beyond ordinary predicting or estimating (What is predictive analytics?). The PAW Resource Guide (PAW Resource Guide, 2021). Big data is all about prediction, and the whole goal of data is to learn from it in order to make predictions. Organizational and operational decisions are driven and rendered by predictions. A predictive model creates a prediction score for each individual, which directly drives or informs decisions for that individual, such as whether to apply a specific medical treatment, rather than just presenting insights. Budgets can be allocated based on per-person estimates, supporting health leaders with the resource allocation dilemma (Giga, 2017). Early detection is aided by a predictive model, which allows preventative measures to begin sooner while potentially reducing the need for invasive investigative procedures later in the care continuum.

The mission of Predictive Analytics World (PAW) is to foster breakthroughs in the value-driven operationalization of established deep learning methods (What is predictive analytics? The PAW resource guide, 2021). Their mission aligns for this evidence-based practice (EBP) project, and to process the pilot implementation data before deciding whether the change is appropriate for adoption into practice and if the process should be hard-wired and integrated system-wide. Ultimately, producing better patient outcomes by helping to target and treat high-risk patients is the goal (Giga, 2017). Predictive analytics technology learns from the data to predict or infer an unknown, resulting in improved outcomes, lower costs, and higher patient satisfaction. The data will determine if the unknown, whether conducting routine sleep screening increases the discovery and treatment of obstructive sleep apnea (OSA). From this starting point, the data collection will build on evaluating the potential rewards against expenditures while providing high-value patient outcomes (Giga, 2017).

References

Giga, A. (2017). How health leaders can benefit from predictive analytics. Healthcare Management Forum30(6), 274–277. https://doi.org/10.1177/0840470417716470

What is predictive analytics? The paw resource guide. Predictive Analytics World. (2021, March 2). https://www.predictiveanalyticsworld.com/predictive-analytics/.

The type of Study I chose for my project is a quantitative study, this study requires gathering data from a reliable verifiable source. Once the data is collected a statistical analysis of the data would be required to help present the data. When interpreting the data, a statistical test can also help decrease bias by helping the clinicians consider how multiple explanations for a report study can be presented(Melnyk & Fineout-Overholt, 2019).

My evidenced based project goal is to view how will education of nurses about QBL improve their awareness and start earlier treatment of Postpartum hemorrhage. The Statistical test I choose is the t-test this test is used to analyze the population and compare to means to different populations. The T-test will help to analyze the data pulled from the chart review and compare the post-implementation data to the pre-implementation data(Fitzpatrick, 2017). The T-test is a simple test that compares the differences between two groups and find a significant statistical occurrence. The data will be utilized to show how the education of the process increased the usage of QBL and increased awareness of how to use the tool will improve patient care. The T-test will compare the pre and post data with  hopes it will reveal how the implementation of this test improved awareness. My other hopes will show how this implementation of the project gives the nurses the why behind the project and increase buy in.

Fitzpatrick, J. J. (Ed.). (2017). Encyclopedia of nursing research (4th ed.) [ebook]. Springer Publishing Company. https://doi.org/10.1891/9780826133052

Melnyk, B. M., PhD, RN. APRN-CNP, FAANP, FNAP, FAAN, & Fineout-Overholt, E., PhD, RN, FNAP, FAAN. (2019). Evidence-Based Practice in Nursing& Healthcare A Guide to Best Practice (4th ed.). Wolters Kluwer.