The setting of data collection will occur in a hospital acute-care unit, outpatient facilities such as a practitioner’s office, and via telephone follow-up at the end of the study. Since the research focuses on patient education, the primary inclusion criteria would be admittance to a hospital with a diagnosis of congestive heart failure (CHF). The settings are appropriate to evaluate the effectiveness of inpatient educational practices in comparison to outpatient education, thus determining the influence of the environment on the final dependent variables.
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The age inclusion would be patients aged 55 and older as elderly patients are considered high-risk for CHF readmission and have much more limited access to technology or other methods to monitor their condition and improve overall health literacy. Patients with comorbidities that are risk factors for repeated occurrences of CHF complications are significantly valuable for qualitative analysis in this research. Co-morbidities may include obesity, diabetes, and high blood pressure (Centers for Disease Control and Prevention, 2016).
The sampling strategy utilized for this study will be non-probability population sampling. Specific parameters such as diagnosis and age are put in place to identify appropriate patients. Furthermore, this sampling technique is fast and inexpensive to implement. The sampling would occur over a period of two weeks to collect enough patients to warrant statistical analysis. Since this is a small case study, a sample size of approximately 30 patients would meet the research needs.
The research would follow a quasi-experimental design as it aims to determine the relationship between a target population and a specific intervention by comparing outcomes of experimental and control groups. A quasi-experimental design is valid for medical research and small case studies, particularly due to ethical reasons of randomly re-assigning patients to groups that may not be conducive to health. The quasi-experimental approach helps to overcome various constraints by creating logical test groups and creating artificial scenarios for study (Center for Innovation in Research and Teaching, n.d.).
Centers for Disease Control and Prevention. (2018). Childhood obesity facts. Web.
National Academies of Sciences, Engineering, and Medicine. (2016). Assessing prevalence and trends in obesity: Navigating the evidence. Washington, DC: The National Academies Press.