The major focus of the proposed research is the prevention of nausea and vomiting in patients with gastric cancer who are undergoing chemotherapy. It is important to research this problem because the effectiveness of the treatment options for chemotherapy-induced nausea and vomiting tends to differ due to a variety of factors, some of which pertain to the nature of treatment (Boccia, 2016). The research question of this study is as follows: In Hispanic patients with gastric cancer, does the prevalence of chemotherapy-induced nausea and vomiting differ in patients treated with conventional medicine compared to patients who receive herbal treatment in the form of ginger?
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The proposed study is expected to include a sample of approximately one hundred people who will be selected from three different hospitals located in the LA area: the LAC Medical Center, the Norris Comprehensive Cancer Center, and the Keck Medical Center. The inclusion criteria for the sample will incorporate the participants’ ethnic background (only patients from the Hispanic population will be included as per the requirements of the research question) and the patients’ current treatment of chemotherapy (FOLFOX) for gastric cancer.
The criterion for exclusion will include the ending of the patient’s chemotherapy for any reason. Moreover, the size of the sample is dictated by the expected method of data analysis, the t-test, which requires a certain number of subjects (preferably, 15 or more) in each of the assessed and compared groups (Warner, 2012). Thus, the proposed sample will be comprised of 30 to 50 patients from the selected medical centers in LA.
Since the chosen study design is quantitative, the small sample size is not the most desirable option. However, it is the preferred option because the measures of the t-test should be maximally accurate for the highest level of reliability of the findings. The sampling method chosen for this study will be non-probability purposive sampling; partly, this method is driven by a set of predetermined characteristics of the participants (such as their ethnic background, gastric cancer diagnosis, and chemotherapy treatment).
Moreover, the proposed study will have an experimental design that is particularly suitable for settings in which the research sample is divided into two similar groups whose assignment is completely randomized and whose results are compared and differences measured (Gray, Grove, & Sutherland, 2013). In the proposed study, the sample will be divided into control and intervention groups, one of which will receive the conventional medicine for treating chemotherapy-induced nausea and vomiting and the other of which will receive an herbal treatment based on ginger. This study design was chosen due to one of its main benefits, a high degree of internal validity, which is critical in medical research that aims, first of all, at precision, reliability, and transferability of results (Gray et al., 2013).
As per the requirements of ethics, the participants’ consent to take part in the research will have to be gained prior to starting the experiment and assigning the subjects to groups. However, it is possible that upon learning about the research question and the problem targeted by the researchers, some of the participants may decide not to receive one of the treatments. Due to this possibility, the random assignment of participants to control and intervention groups will be limited, and the study design will thus shift to a quasi-experimental one. In other words, the experiment will remain largely the same, but the absence of random assignment to groups will transform it into a quasi-experiment (Gray et al., 2013).
Boccia, R. V. (2016). Chemotherapy-induced nausea and vomiting: Identifying and addressing unmet needs. JCOM, 20(8), 377-384.
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Gray, J. R., Grove, S. K., & Sutherland, S. (2013). The practice of nursing research – e-book: Appraisal, synthesis, and generation of evidence. Amsterdam, The Netherlands: Elsevier Health Sciences.
Warner, R. M. (2012). Applied statistics: From bivariate through multivariate techniques. New York, NY: SAGE.