Data Analysis Plans
The present section proposes a data analysis plan for a study dedicated to the interactions between nurses and patients with a focus on the patients with heart failure and their readmissions. The following research question is the central one: how can nurses improve the level of caregiving for patients during the pre-discharged period? The study will collect the opinions of about ten nurses, and it will use interviews with open-ended questions to gather their perspectives on the research questions, as well as some demographic data. The specifics of the study define its approach to data analysis: it is proposed to use descriptive statistics for the demographic variables and thematic analysis for the rest of the data.
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The demographic variables that will be gathered will include the nurses’ education and working experience. They will be identified to determine the nurses’ expertise on the topic; their association with the themes that may be discovered during the thematic analysis will also be checked. The demographic data will be analyzed with the help of descriptive statistics; in particular, it seems reasonable to offer frequency distributions for a detailed presentation of the information. They will also be arranged into histograms for their graphic display (Polit & Beck, 2017; Simpson, 2015). Thus, the use of descriptive statistics will help to present the information to the reader.
The rest of the data will be gathered during interviews and will be qualitative. As a result, it is proposed to analyze it appropriately with the help of thematic analysis. The latter is a relatively common and well-established approach to qualitative analysis, which involves the identification of patterns in the data (Holloway & Galvin, 2016; Polit & Beck, 2017). This way, the study will be able to respond to its key research question, as well as the additional ones.
The primary topics that will be identified in the data will be concerned with readmissions, pre-discharge interactions between nurses and patients, transitional programs, and the various interventions employed by nurses, especially educational tools and follow-up activities. All these topics were chosen to respond to the research questions. If discrepancies in the nurses’ perspectives are encountered, they will be analyzed while keeping in mind the differences in their expertise to check if more experienced nurses are evidenced to employ any specific tools.
Regarding the use of inferential statistics, the proposed research does not need this approach since qualitative analyses do not employ it (Polit & Beck, 2017). Still, if an opportunity to test certain patterns is encountered, inferential statistics will be introduced. For example, if the educational tools used by the nurses are similar and can, therefore, be reviewed in connection with the readmissions of the patients of those nurses, they will be tested. Similarly, if any significant discrepancies can be tied to the expertise of nurses, this connection will be tested as well.
The test will be chosen based on the type of data identified, as well as the sample specifics (Simpson, 2015). Most definitely, the situation will involve the comparison of independent groups with small samples, which calls for non-parametric independent group tests (Polit & Beck, 2017). However, the currently planned sample is rather small, which will limit the ability of the study to produce generalizable results. Therefore, it is more reasonable to focus on the qualitative data and employ it to gain useful insights into the topic as planned.
Holloway, I., & Galvin, K. (2016). Qualitative research in nursing and healthcare (4th ed.). Chichester, UK: John Wiley & Sons.
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Polit, D.F., & Beck, C.T. (2017). Nursing research: Generating and assessing evidence for nursing practice (10th ed.). Philadelphia, PA: Lippincott, Williams & Wilkins.
Simpson, S. H. (2015). Creating a data analysis plan: What to consider when choosing statistics for a study. The Canadian Journal of Hospital Pharmacy, 68(4), 311–317.