When analyzing or conducting scholarly research, clinical professionals should address qualitative and quantitative methods of assessing data, as these two approaches are fundamental to evidence evaluation. Thus, the primary difference between these methods is the type of data they are designed to analyze. Quantitative data analysis deals with numerical data that can be statistically allocated and calculated. This method is mostly used in empirical studies that seek to prove a certain hypothesis or theoretical framework. For example, in the clinical context, quantitative evidence evaluation is frequently applied in randomized controlled studies that gather tangible data from the participants and then present a statistical analysis based on these data (Streefkerk, 2022). Quantitative evidence collection approaches include surveys with close-ended questions and experiments.
On the other hand, a qualitative approach to evidence evaluation addresses the process of analyzing more abstract, non-numerical data. Frequently, qualitative analysis is used to present more insights into the statistically justified data or to present a foundation for a new hypothesis of a theory that needs to be proved statistically (Streefkerk, 2022). Examples of the qualitative evidence collection tools include in-depth interviews, focus groups, and literature reviews. Essentially, qualitative evidence assessment helps obtain a better understanding of the concept or theory, whereas quantitative evaluation seeks to systematize the data. In order to create a meaningful data assessment, it is recommended to employ both methods during the research. The phenomenon is known as a mixed-method approach that usually combines literature review and statistical analysis of the raw data. Hence, it may be concluded that both qualitative and quantitative approaches to evidence evaluation provide exceptional value to the data analysis and evidence-based practice for clinical professionals.
Streefkerk, R. (2022). Qualitative vs. quantitative research | Differences, examples & methods. Scribbr. Web.