It is generally accepted amongst social scientists who collect information or measure phenomena that the combination of quantitative and qualitative methods yields the richest data. The information collected on a survey, in which many of the questions are close-ended can be contextualized by the material from the qualitative part of the study. In the field of mixed methods there are a variety of techniques to execute these measures such as collecting both kinds of data at the same time or obtaining the information sequentially, giving yourself time to evaluate the initial findings to strengthen your (and ultimately the readers’) understanding, interpretations and recommendations based on the findings.
Another important component to understanding results is the use of graphs. Many statistical packages provide ways to produce bar charts, line graphs, box plots and other similar ways to visualize information. These can also increase understanding the information. A picture can really be a thousand words.
But what about data/findings/visualizations to support decision making?
Perhaps an even better way to conduct mixed method research is to include a third component, a visualization that represents both the quantitative and qualitative findings. In particular, the ways in which information can be used to support decision making. For example, the web site Patients Like Me provides graphs for quantitative information such as age, gender, top treatments. It also provides forum postings, which contain qualitative information about the patients’ experiences. But all of this data is separate from each other. You cannot cross tabulate age with gender within an illness.
What if these were combined into a graph so that a 29 year old woman, recently diagnosed with MS, experiencing fatigue and considering taking steroids, could find a way to a way to help make this decision? Wouldn’t this make for a better collaboration?
