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
Statistical tests can be chosen based on independent variables and other project designs. My study seeks to establish whether PPE training is effective.
DQ Determine and you would use in conjunction with the research design you selected for DQ 1 to analyze the findings of your proposed evidence-based project.
encourages informal caregivers (family) to use PPE One of the complicating variables I’ve identified is the effects of staff members’ PPE usage modeling. Staff instruction and modeling, according to Siebert et al. (2018), was a key determinant in visitor compliance. However, there is a test that takes into consideration participant differences.
A hybrid design I picked the ANOVA test since each group comprises a diversity of people. A mixed design examines “change across time, group differences, and the impact of time-group interaction” (Tappen, 2016). This will show the differences within and between groups (educated vs. uneducated). It can be used to compare the changes that occur before and after an educational intervention. It will make it easier to account for the differences in the individuals in each intervention group. It may, if necessary, measure the change over a number of time points.
NUR 590 Topic 4 DQ 2
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:”.
- How many independent variables covary (vary in the same time period) with the dependent variable?
- At what level of measurement is the independent variable?
- What is the level of measurement of the dependent variable?
- Are the observations independent or dependent?
- Do the comparisons involve populations to populations, a sample to a population, or are two or more
samples compared?
- Is the hypothesis being tested comparative or relationship?
Statistical testing is used explain the results of a study. The test that I would use would be the t-test. “A t-test is a type of inferential statistic used to determine if there is a significant difference between the means of two groups, which may be related in certain features” (Investopedia, n.d.). I would used this test because of show the averages of nurses to patient ratios to help determine the correlation between low staffing and high staffing and whether each has a positive or negative effect on patient health outcomes.
Reference:
Investopedia. (n.d.). T-Test. Retrieved from https://www.investopedia.com/terms/t/t-test.asp
Parab, S. & Bhalerao, S. (2010). Choosing Statistical Test. International Journal of Ayurveda Research. 1(3): 187-191. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2996580/
Independent factors and other project designs can be used to select statistical tests. My experiment aims to determine if PPE education enhances informal (family) caregiver compliance with PPE use. I’ve detected at least one confounding variable: the effects of staff PPE usage models. According to Siebert et al. (2018), staff modeling and education played a significant role in visitor compliance. However, there is a test that takes into consideration participant differences.
Due to the utilization of different participants in each group, I have chosen a mixed design ANOVA test. A mixed design assesses “change over time, differences between groups, time interaction, and group effects” (Tappen, 2016). This will demonstrate the differences between groups (educated versus no education) as well as within groups. It can be used to compare the difference between before and after an educational intervention. It will aid in controlling for the various participants in each intervention group. It could measure the change from many time points if required.
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.
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: The first is to correctly identify the type of experimental design, and the second is to ensure that the 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 compare standard CPR to continuous compressions during defibrillation to determine the amount of “hands-off” during CPR.
Liang, G., Fu, W., & Wang, K. (2019). Analysis of t-test misuses and SPSS operations in medical research papers. Burns & trauma, 7.
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.
Najmi, A., Sadasivam, B., & Ray, A.(2021). How to choose and interpret a statistical test? An update for budding researchers. Journal of Family Medicine and Primary Care, 10(8), 2763-2767.
ALSO CHECK OUT:
Pilot, D.F.(2017). Data collection methods. J. Fitzpatrick(ed.), Encyclopedia of nursing research (4th ed.). Springer Publishing Company.
Using statistical data analysis can be used in many ways and be of benefit in not only the business world, but in the healthcare world as well, especially research. One would need to understand what statistical methods are and the principles behind them to be able to analyze or correctly interpret the data that comes from the results (Wienclaw, 2021). The statistical test that I would use in the evidence-based practice (EBP) project proposal to evaluate the outcomes would be that of regression analysis. This is considered a reliable method of being able to identify which variables have an impact on the outcome of the topic of interest. There are different types of regression analysis that can be used in which one type is linear regression.
Linear regression analysis would be the specific statistical test that I would use for my project. The reason why I selected this test was because I want to determine what impact my independent variables (education and no education) have on the outcome of my dependent variable (cervical cancer screening rates). Linear regression analysis statistical test is used to “estimate the association of greater than or equal to 1 independent (predictor) variables with a continuous dependent variable” (Schober & Vetter, 2021, p. 108). The kind of information that this test will provide about my outcomes on my project would be an estimate of the effect of my independent variables (education and no education) on my dependent variable (cervical cancer screening rates). This will help determine the impact of education versus no education on the increasing cervical cancer screening rates in my population of ethnic minority women. The use of linear regression analysis can also provide me with information on the interaction of my two independent variables and whether the effect of one depends 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.
Predictive analytics is a type of data science that goes beyond standard forecasting or estimating (What is predictive analytics? 2021). The PAW resource guide Prediction is at the heart of big data, and the entire purpose of data is to learn to predict. Predictions influence and direct organizational and operational decisions. A predictive model generates a predictive score for each individual, which directly drives or informs decisions for that individual, such as whether to apply a specific medical treatment. Decision-makers can allocate budgets based on per-person projections, assisting health leaders with the resource allocation challenge (Giga, 2017). A predictive model promotes early detection, allowing preventative interventions to begin earlier and potentially reducing the need for invasive investigative procedures later in the care continuum.
PAW’s mission is to foster breakthroughs in the value-driven operationalization of established deep learning methods (What is predictive analytics? 2021). The PAW resource guide Their mission is to process the pilot implementation data before deciding whether the change is appropriate for adoption into practice and whether the process should be hard-wired and integrated system-wide for this evidence-based practice (EBP) project. The ultimate goal is to improve patient outcomes by assisting in the identification and treatment of high-risk patients (Giga, 2017). Predictive analytics uses data to predict or infer an unknown, resulting in better outcomes, lower costs, and higher patient satisfaction. The data will reveal whether routine sleep screening increases the detection and treatment of obstructive sleep apnea (OSA). From here, data collection will focus on weighing 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 Forum, 30(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.
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.
