Research design-response

                                                                               Qualitative vs. Quantitative

Qualitative research collects subjective, non-numerical data through observation and interviews, while quantitative analysis involves concrete evidence such as numerical data, statistics, and experiments (Koenig, 2023). Qualitative research aims to understand social aspects and examine the lived experiences of individuals. It involves open-ended data collection methods, such as interviews, participant observation, and document analysis. Qualitative data analysis usually involves identifying themes, patterns, and meanings from the data (Schoonenboom, 2023). This approach is suitable for research and can provide an understanding of the participants’ perspectives. However, its findings may be subjective, and the sample size may not represent the population.

On the other hand, quantitative research establishes a relationship between variables using numerical data. It involves collecting data through structured surveys, questionnaires, and experiments (Koenig, 2023). Data analysis involves statistical tests and models, and the findings are usually presented using graphs and tables (Schoonenboom, 2023). However, it may not capture the complex nature of social aspects, and the data collected may not reflect the views and experiences of the participants.

                                                                  Developing A Research Study

When studying my PICOT question, “In heart failure patients discharged from the hospital, does implementing a multidisciplinary team-based intervention, compared to usual care, decrease the 30-day readmission rate?” using qualitative and quantitative research designs would be most beneficial. A mixed-method plan can provide a comprehensive understanding of the problem by combining the strengths of both qualitative and quantitative approaches (Schoonenboom, 2023). The qualitative findings can inform the development of the multidisciplinary team-based intervention by identifying the needs and preferences of heart failure patients and the challenges that need to be addressed. The quantitative component can provide numerical evidence of the effectiveness of the intervention in reducing the 30-day readmission rate.

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