Hypertension in elderly people is a risky health condition that is associated with the development of other diseases that affect the quality of people’s life. The purpose of this research project is to determine whether interventions based on modifying a diet and exercising can influence the health state of elderly people with hypertension. In order to analyze the collected quantitative data on possible changes or the absence of changes in blood pressure levels of elderly people selected for the study, it is necessary to design an appropriate plan and strategies for data analysis.We will write a custom Hypertension in Elderly People: Data Analysis Plan specifically for you
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Definitions of Variables
In this study, independent variables are a healthy diet and exercising that are measured according to the nominal scale. These independent variables have such categories as the presence of a diet and exercises and the absence of a diet and exercises. In the context of this research, the presence or absence of a diet and exercising in the proposed intervention is expected to directly affect blood pressure levels in elderly people participating in the study. The dependent variable is the level of blood pressure that is assessed while resting in a sitting position in order to determine possible hypertension. Three measures are identified for the purpose of this study: hypertension (> 140/90 mm Hg), prehypertension (120–139/80–89 mm Hg), and normal blood pressure (<120/80 mm Hg).
Depending on the research questions created for this study, it is necessary to formulate the null and alternative hypotheses that will be tested with the help of a certain statistical analysis tool:
- H0: The application of a healthy diet and exercising as the part of the intervention for elderly people with hypertension does not differ in outcomes in comparison to the absence of the intervention.
- H1: The application of a healthy diet and exercising as the part of the intervention for elderly people with hypertension differs in outcomes in comparison to the absence of the intervention.
The Type of Analysis, Rationale, and Significance Level
In order to test the stated hypothesis with the help of using the collected data before and after interventions, it is necessary to apply such a statistical test as the two-way factorial ANOVA (analysis of variance). This type of statistical analysis is appropriate for this particular research because the purpose of this study is to identify whether there is a difference in patients’ state before and after implementing the intervention, as well as with or without any intervention. Thus, ANOVA is helpful to demonstrate this type of a difference if there is any (Lee et al., 2018). The necessity of working with two independent variables indicates that the two-way factorial ANOVA can be used for this study because the one-way ANOVA is not applicable to this case (Safdar, Bertone-Johnson, Cordeiro, Jafar, & Cohen, 2015). As a result, using this specific type of ANOVA, it is possible to determine how two independent categorical variables, including a healthy diet and exercising, can influence any changes in such a dependent variable as the blood pressure level.
The significance level that can be set for a statistical test should be 0.05 instead of 0.01 or 0.10. The reason is that it demonstrates a 5% risk of determining that there is no difference, and this percent is discussed by researchers as realistic to achieve and expect (Bendzala et al., 2015; Lee et al., 2018; Safdar et al., 2015). Therefore, this significance level is usually applied in quantitative studies based on testing evidence and findings with the help of ANOVA.
It is expected that the study results will indicate statistically significant differences in the findings for the test and control groups of elderly patients with hypertension in terms of changes in their blood pressure levels. In order to support the research hypothesis, it will be important to notice lower blood pressure levels for the test group of patients who participated in the intervention in comparison to the control group of participants whose diet was not changed and who did not do any exercises. Furthermore, statistically significant differences should be observed while comparing blood pressure levels before and after applying the intervention. If there are statistically significant differences (p-value < 0.05) in blood pressure after the intervention, it is possible to support the stated research hypothesis and reject the null hypothesis.
Data analysis is the most important part of any research project because the results of analyzing the collected quantitative information indicate whether hypotheses are supported or rejected and how it is possible to answer the set research questions. For this study involving elderly patients with hypertension, the data analysis is based on the application of the ANOVA statistical test. The selection of the statistical analysis depends on the types of independent variables chosen for this research, as well as on the number and type of dependent variables. It is also important to note that the significance level in 0.05 can also be viewed as appropriate for this specific study. The selected data analysis method guarantees testing the proposed hypotheses.Get your
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Bendzala, M., Kruzliak, P., Gaspar, L., Soucek, M., Mrdovic, I., Sabaka, P.,… Takazawa, K. (2015). Prognostic significance of dipping in older hypertensive patients. Blood Pressure, 24(2), 103-110.
Lee, C. J., Kim, J. Y., Shim, E., Hong, S. H., Lee, M., Jeon, J. Y., & Park, S. (2018). The effects of diet alone or in combination with exercise in patients with prehypertension and hypertension: A randomized controlled trial. Korean Circulation Journal, 48(7), 637-651.
Safdar, N. F., Bertone-Johnson, E. R., Cordeiro, L., Jafar, T. H., & Cohen, N. L. (2015). Dietary patterns and their association with hypertension among Pakistani urban adults. Asia Pacific Journal of Clinical Nutrition, 24(4), 710-719.