Hypertension, stroke, and diabetes are some of the most frequent diagnoses for elderly persons in the US. As it stands, healthcare professionals are favoring medical interventions over educational ones in managing these diseases. However, these practices are expensive and often inefficient without the follow-up educational intervention to ensure proper use of exercise, diet, and training regime. The following section presents the sampling strategies and tools proposed for this research.
Sampling Basic Information
Patients selected and invited to participate in this study would need to adhere to the following criteria:
- Age: According to the international definition of elderly patients, as provided by the World Health Organization (WHO), individuals with a chronological age of 65 or older are considered elderly (WHO, 2018).
- Gender: Both genders would be welcome to participate in this study.
- Race: No strict requirements in regards to race. A quota of minimum 15% African-American, 10% Hispanic, and 5% Asian-Americans must be observed in order to ensure inclusion.
- Additional eligibility criteria: All patients participating in the study must be diagnosed with hypertension, be capable of reading, writing, and performing self-care operations.
- Socio-economic background: Any socio-economic background is welcome, so long the criteria mentioned above are met.
Sample Size and Appropriateness for the Study
Based on estimations and calculations for education-centered interventions provided by Esserman, Zhao, Tang, and Cai (2013), the sample size for a 1-month educational intervention is 78 individuals. These estimations are based on the number of repetitions. Tests will be taken before and after the intervention, with a follow-up observational period of 6 months. Individuals will be split into groups of 13 people, in order to conduct educational and testing interventions. Reliability of data collection processes and measurement tools will be done through test-retest sequences and internal consistency reliability checks.
Reliability
Data Collection Process
In order to ensure consistency and reliability of data collection, this study will use internationally recognized measures utilized in similar researches. The tools chosen for the task are MINICHAL, which is a short form of quality of life questionnaire for arterial hypertension, recommended for use in order to test the results of the intervention during the follow-up period (Carvalho et al., 2012). Patient Activation Measure (PAM) and Health Education Impact Questionnaire (HEIQ) will be used to test the quality of the educational intervention and the patients’ capability of understanding and utilizing these instructions (Turner, Anderson, Wallace, & Bourne, 2015). These measurement tools are internationally accredited and are considered suitable for this type of research.
Validity
Sampling validity is calculated using this formula:
(a) = 1 – Sampling Error = 100% – 1% = 99% confidence interval (Esserman et al., 2013). It is the standard confidence interval used in the majority of nursing researches to ensure the accuracy of provided data. The validity of the measurement tools is a judgment made based on evidence regarding the applicability of the tool to the situation. As such, the tests included have good face validity, content validity, criterion validity, and discriminant validity, which justifies their use in the scope of this research.
Conclusion
The choice of samples and tools to conduct measurements with is an important part of any research. Samples and measurement instruments alike are to be tested for reliability and validity and be backed by academic sources. The choice of both in this section reflects on the previous experience and utilizes statistical formulas to determine these key parameters.
References
Carvalho, M. A., Silva, I. B., Ramos, S. B., Coelho, M. F., Goncalves, I. D., & Figueiredo, N. J. A. (2012). Quality of life of hypertensive patients and comparison of two instruments of HRQOL measure. Arquivos Brazilieros de Cardiologia, 98(5), 442-451.
Esserman, D., Zhao, Y., Tang, Y., & Cai, J. (2013). Sample size estimation in educational intervention trials with subgroup heterogeneity in only one arm. Statistics in Medicine, 32(12), 2140-2154.
Turner, A., Anderson, J. K., Wallace, L. M., & Bourne, C. (2015). An evaluation of a self-management program for patients with long-term conditions. Patient Education and Counseling, 98, 213-219.
WHO. (2018). Ageing and life course. Web.